Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Types of AI Agent Attacks: A Security Team's Taxonomy

A security team running agents in production can already list the ways those agents get attacked: prompt injection, memory poisoning, tool abuse, model tampering, agent-to-agent coercion. The list is not the problem. The problem is that a security architect can recite all five and still not know which ones their detection stack will catch, because the way the field catalogs these attacks says nothing about whether the attack is catchable.

The AI Agent Attack Kill Chain: Which Stages You Can Actually Detect

The early stages of an AI agent attack are silent. The poisoning, the hijacked intent, the reconnaissance: none of it executes, so none of it produces a runtime signal, and the kill-chain instinct every security team runs on says exactly the wrong thing here: break the earliest link. There is no early link to break. You cannot detect a stage that emits nothing.

Tool Call Analysis for AI Attack Detection: Reading What Rides Inside the Call

A compromised agent doesn’t make a single call it isn’t allowed to make. It queries a table it’s authorized to read, calls a tool it’s authorized to use, sends to a domain that’s on the allowlist. Every call is legal. The attack is in the values it passes, and your tool-call log records all of it as a clean day’s work. A tool call has two layers. Almost every tool you run reads the first one: the call itself: which tool, in what order, at what rate.

How to Tell If Your AI Agent Has Been Compromised (When Every Symptom Looks Normal)

Your AI agent just did something it has never done. It called a tool that is not in its usual set, or it opened a connection to a destination you do not recognize, or its output came back subtly wrong. So you do what anyone does: you search for what a compromised agent looks like, and you find a checklist. Unusual tool usage. Unexpected data access. Out-of-context responses. Elevated resource consumption.

Compliance and Regulation Heat Up in 2026: A New Phase of Scrutiny for Financial Services Organisations

The regulatory landscape facing financial services in 2026 is more complex, more demanding, and faster moving than at any point in the past decade. Across the UK, regulators are attempting to strike a delicate balance of stimulating economic growth while maintaining strong consumer protection and financial stability. This balancing act is unfolding against a backdrop of sluggish economic performance, geopolitical uncertainty, and political pressure for "pro-growth" regulation. The result is a regulatory environment where the pace, scope, and intensity of change is accelerating sharply.

Building SecOps that improve with every frontier AI release

CEO Maxime Lamothe-Brassard made an observation after the RSA conference that security vendors don't typically say out loud: "The frontier models are just better than anything people roll their own. There's no secret sauce these vendors are offering that is better than the latest frontier model release." That's a pointed claim that carries a significant implication buyers may not have fully considered.

How Relay Network Adopted AI Coding Securely and Built the Foundation for Agentic Development

Champion / Spokesperson(s): Brendan Putek, Director of DevOps, and Esaie Batoula, Security Engineer. Relay Network is the innovator behind a secure B2C communications platform that combines SMS with dynamic feed technology to help regulated enterprises deliver personalized, action-oriented mobile experiences for every customer. In an industry where trust, compliance, and data protection are paramount, security has always been central to how the company builds software.

Shadow AI: The Hidden Risk Expanding Across the Enterprise

Companies and employees are racing to capture the value and efficiencies offered by AI, but security is often an afterthought. Employees are using unauthorized GenAI tools to summarize documents, draft emails, and analyze potentially sensitive or proprietary data. Developers are adding AI capabilities before security teams can review them. SaaS platforms are adding AI features that may process sensitive business data by default.

MCP Security: How to Secure MCP Integrations

AI agents are connecting to enterprise systems right now. Whether a developer wired up Claude to an internal Confluence instance, a vendor shipped an agentic workflow that calls the CRM, or an employee enabled a browser-based AI assistant that reads email, Model Context Protocol (MCP) is rapidly becoming the integration layer between large language models (LLMs) and corporate data. Most security teams have no visibility into any of it.

What is AI Usage Control?

AI usage control is the security and governance framework that enterprises use to monitor, regulate, and secure how employees interact with artificial intelligence tools. As Generative AI becomes deeply embedded in everyday workflows, organizations face a high-stakes balancing act: capturing massive productivity gains while preventing catastrophic data leaks, compliance violations, and intellectual property exposure.

AI Agent Governance Part 2 - What Good Looks Like: Governing AI Agents in Practice

If AI agents are becoming organizational actors, then governance needs to move beyond principles and into operational structure. In Camille Stewart Gloster’s upcoming book The Insider You Build, she explains that governance is not defined by policies or structures, but by whether it can actually influence system behavior at runtime. In an agentic environment, governance only exists where it can shape, constrain, and intervene in decisions as they happen.

Cosine Similarity Is Math, Not Magic

Cosine similarity is pure math. No magic. No understanding. Once you accept that, a lot of the confusion goes away. We talk to a lot of customers, and even seasoned engineers, who treat cosine similarity like magic that solves everything. Engineers talk about embeddings like they are definitive. Product teams trust similarity scores like they are facts. Vendors sell “semantic understanding” like the model actually understands. Truth is, it does not.

Introducing Agentic Exposure Validation

Check Point Agentic Exposure Validation (AEV) uses AI agents to reason like an attacker across your external footprint. It correlates your assets with live threat intelligence, exploit research, and attacker behavior, and tells you, in minutes, what's actually exploitable and what isn't. No assumptions. No noise. Evidence-backed findings your team can act on immediately.

Detecting AI Agent Lateral Movement in Kubernetes

An AI agent moving laterally through a Kubernetes cluster does not look like an intrusion. There is no foreign process, no exploit, no dropped binary — just the agent using the identity, network routes, and tools it was handed at deployment to reach targets it was technically allowed to touch. That is the entire problem. The controls you run were built to catch an outsider pivoting from host to host.

Commercial vs Open Source AI Attack Detection Tools: A Buyer's Guide

If you’re weighing open source against commercial tools for detecting attacks on your AI agents, you’re probably trying to answer a single question. Can we build this ourselves, or should we buy it? It’s a fair question, and the existing content on it isn’t much help. Most comparisons line up tools side by side and tally features. That tells you which tool is better at one slice of the problem. It doesn’t tell you whether you have a working detection program.

Charlotte AI AgentWorks: Build Your Security Workforce Demo

Today’s adversaries move at the speed of AI, so defenders need to reason, decide, and act faster across every stage of security operations. Meet Charlotte AI AgentWorks, a no-code agent builder that enables teams to create mission-ready AI agents directly inside the CrowdStrike Falcon platform.

Just vibe code it...

Sometimes unlimited tokens and rippin' guitar riffs can't solve every problem. The best builders know what NOT to build. Vibe coding might cut down on time, but that's only a fraction (20%) of the total software lifecycle cost. The other 70–80%? Maintenance, security patches, compliance updates. The slow grind of keeping it alive in production. When it comes to something as complex and critical as keeping your security airtight, depth wins over speed every time.

From PentestGPT to production: The state of AI-assisted offensive security with Charles Grandjean

Join us for this week's Defender Fridays as Charles Grandjean, CTO and Co-founder at Hexiagon AI, breaks down where AI-assisted pen testing actually stands today and what it means for both red teams and defenders. At Defender Fridays, we delve into the dynamic world of information security, exploring its defensive side with seasoned professionals from across the industry. Our aim is simple yet ambitious: to foster a collaborative space where ideas flow freely, experiences are shared, and knowledge expands.

Businesses have NO IDEA how bad AI attacks can be

There are two types of companies: those who have been compromised and those who will be. Mid and small businesses are walking into this reality without understanding what AI has changed. On The Cybersecurity Defenders Podcast, David Chernitzky, CEO and co-founder of Armour Cybersecurity, explains why the gap between how large organizations understand AI-driven threats and how smaller ones do is widening fast.

How AI Is Changing What Security Teams Can Actually Do | Nancy Phillips, Ensemble Health Partners

Threat actors used to need days or weeks to exploit a vulnerability. Now AI lets them do it in seconds. Most security teams are already buried. Too many tools, too many alerts, manual processes that can't keep pace, and break-glass changes that get made and forgotten. Keeping everything configured and optimized correctly is a full-time job on its own. Nancy Phillips, Chief Information Security Officer at Ensemble Health Partners: "I want my teams doing the innovative stuff. Not the mundane, repeatable stuff.".

Exposure Management Explained: How to Go Beyond Vulnerability Scanning

Vulnerability scanning gives security teams a starting point, but it has never been the whole picture. Scan results capture known CVEs across applications and systems, yet they say nothing about whether a given weakness is actually reachable, whether the controls around it are functioning correctly, or whether the people with access to it represent a meaningful risk. Exposure management addresses all of that.

Protecting Red Hat OpenShift AI with Trilio for Kubernetes: a hands-on lab

A few weeks ago I was on a call with a financial services customer who had moved a credit-decisioning model into production on Red Hat OpenShift AI. They were happy with the platform. They were less happy with the answer they had for a question their risk officer had just asked: “If an attacker encrypts the cluster tomorrow, what do we need to bring back to be inference-ready by Monday morning?” The team started listing the obvious things — the model artifact, the serving endpoint.

Even Google says you cannot do AI security on one platform

This week, Connie Loizos, editor in chief of TechCrunch, sat down backstage with Francis de Souza, COO of Google Cloud, for a piece on the state of enterprise AI security. The interview is worth reading in full. Three points in it should reshape how every CISO is thinking about the next twelve months.

Cybersecurity Operations Are Entering the AI-Native Era

Cybersecurity operations were already becoming increasingly difficult to scale long before AI-driven and increasingly agentic attacks began accelerating the threat landscape. Customer environments continued expanding across endpoints, identities, cloud services, SaaS applications, remote users, and operational infrastructure. More environments created more telemetry, more coordination, and more operational complexity for teams already operating near capacity.

NetSuite AI Connector: The governance layer your roles and permissions aren't ready for

The NetSuite AI Connector Service enables external AI agents to authenticate directly into NetSuite using real user identities and MCP-based tool execution. While Oracle limits elevated actions at the platform level, AI agents still inherit the full permission scope of the connected role. That shifts longstanding governance weaknesses, including over-permissioned roles, SoD conflicts, and undocumented customizations, into active operational risk.

OWASP Top 10 LLM Risks Explained

As large language models (LLMs) become more embedded in business operations, the risks and attack methods targeting them are evolving just as quickly. The 2025 edition of the OWASP Top 10 for LLM Applications reflects this rapid evolution, addressing the current threats facing generative AI systems in production environments. For organizations investing in LLMs, understanding the risks is crucial for deploying these systems securely.

A2A vs MCP: Which Is More Secure?

Two protocols are shaping the AI revolution: A2A for agent-to-agent delegation, and MCP for agent access to tools and external systems. A2A expands who can participate in a workflow by enabling agent-to-agent delegation. MCP expands what agents can reach by connecting them to data and systems. By the end of 2026, task-specific AI agents are expected to appear in 40% of enterprise applications, up from less than 5% in 2025. That shift changes where security has to live.

The Collapse of Symmetry: Why Periodic Pentesting is Strategic Suicide Against Algorithmic Warfare

The cybersecurity industry is sleepwalking. We are still captivated by the romanticized image of the hacker: a human in a hoodie manually typing code to breach a network. Wake up to the reality of 2026. The modern adversary is no longer human. It is algorithmic.

ITSP: Corelight launches Agentic AI that makes SOC triage 10x faster

Modern SOCs face a difficult reality: attackers are moving faster while analysts are being asked to investigate more alerts than ever. Learn how agentic triage helps security teams move from alert overload to evidence-backed investigations. Rather than relying on opaque AI outputs, the approach uses expert-written playbooks and exposes the underlying queries and evidence so analysts can verify conclusions against raw network data.

GitGuardian Just Gave AI Coding Agents Secret Detection Skills

AI coding assistants like Claude Code and Cursor are helping developers write more code faster, but that also means more chances for secrets to slip into prompts, files, commits, and tool outputs. GitGuardian’s new open-source **agent-skills** repository teaches AI agents how to use **ggshield** directly inside the developer workflow: when to scan, how to read findings, and how to guide remediation for leaked credentials.

Legitimate-Looking Codex Remote UI Secretly Steals Your AI Tokens

There's a new playbook in the supply chain threat landscape, where an someone builds something genuinely useful, growing a real user base. But all while stealing credentials. codexui-android is a remote web UI for OpenAI Codex. Real GitHub repo. Active development. Polished enough to get 27.000 weekly downloads. And for the past month, every single invocation has been quietly exfiltrating your Codex authentication tokens to an attacker-controlled server.

Three ways intelligent workflows enhance network security

Network security is operationally complex. It involves constant triage, approvals, and monitoring, spread across a range of tools, teams, and environments. Traditionally, this requires teams to do a significant amount of time-consuming, repetitive, and draining manual work, resulting in a longer MTTR and leaving many practitioners overwhelmed and burnt out. The problem isn’t in the tools they use – it’s in the work that happens between tools.

OpenAI Privacy Filter Isn't Enough: The Truth About AI Tokenization

While the new OpenAI privacy filter detects basic PII, true data protection requires a much deeper system. In this video, we expose the hidden security vulnerabilities inside modern AI workflows and explain why aggressive data redaction actually destroys your model's utility. What you will discover in this breakdown: The Redaction Trap: Why simply deleting sensitive data breaks your AI's contextual understanding.

AI Risk Is Not Uniform: The Case for Archetype-Aware Enterprise Security

Every conversation I have with security leaders about enterprise AI security eventually arrives at the same place: a description of what they've extended. Their data loss prevention tool now flags sensitive data going into prompts. Their SIEM is ingesting AI platform logs. Their cloud security team has added model endpoints to their coverage scope. For many teams, this represents real effort and real progress.

Cato CTRL Threat Brief: AI, Zero-Days, and the US-China Cyber Arms Race

Underlying the US–China AI race, there’s arguably a more sinister arms race—the race to identify zero-day threats. Frontier AI algorithms, such as Anthropic Mythos (here) and China’s Qihoo 360 (here), are compressing the zero-day discovery cycle. But how those discoveries are gathered and shared among cooperating entities is giving China significant defensive and offensive advantages.

Your AI Agent Inventory Is Incomplete. Here's What That Means for Risk.

Download Beyond Identity: The CISO's Guide to Securing Agentic AI for a 12-month roadmap to comprehensive agent governance, starting with visibility. Some organizations still treat agentic AI as a future problem. Something to plan for. Something on the horizon. That framing is wrong, and the inaction it entails will put you behind.

Why MCP Breaks the Financial Services Security Stack

A relationship manager asks the firm's AI assistant to "summarize my top wealth clients by AUM and flag anyone with a pending transfer over $500K." The agent calls a CRM MCP server, then a core banking MCP server, then a market data MCP server, and returns a clean answer in twelve seconds. Names, balances, account numbers, pending wire details, all rendered in plain text inside the chat window. No file moved. No email left the network. No DLP channel triggered.

Tanium AI Enrichment and Analysis: Tanium Tech Talks #162

Tired of decoding commands, searching unfamiliar processes, and guessing alert context? See how Tanium AI Enrichment& Analysis breaks down alert activity, explains risk, and guides response - without leaving your workflow. Join us as we explore how Tanium Threat Response uses AI to: Provide detailed context and security implications Decode complex or encoded command lines Summarize alerts with key findings and context Recommend next steps to accelerate investigation and response.

Practical MCP Security: A Playbook for Mid-Market Teams

Most guidance published on AI agent security is written for enterprise organizations. It assumes dedicated AI security functions, red teams, platform engineering groups, and the budget to commission purpose-built tooling. If your security team is three people covering five hundred employees and a cloud environment that grows faster than you can document it, that guidance was not written for you. The five posts in this series have established the threat landscape.

Continuous Offensive Security: The Line We've Been Walking

AI Pentesting is having a moment. Well, several moments, actually. Every other week, another vendor announces something, or another LLM-driven pentesting tool tops some benchmark on a target nobody's heard of, another deck claims a new "gold standard" being disrupted, at long last... It's been busy.

Uncovering LLM Vulnerabilities: Insights from the AI Security Testing Front Line

Artificial intelligence (AI) is transforming the business landscape at an accelerated pace. The announcement of Mythos from Anthropic, with its limited public release, is just one example of how LLMs are changing the speed at which unknown flaws in IT systems can be exposed.

Agentic Identity Is Not NHI With a Brain

The non-human identity (NHI) problem was always the same problem: too many service accounts, too few owners, too many secrets in too many places. They sat where we left them, quietly piling up privilege, outliving the engineer who created them. Eventually someone, an auditor, sometimes an attacker, went looking and found them. Agents are a different problem.

Defending Against the Next Generation of Agentic Attacks

The attack lifecycle is compressing. Frontier AI models like Anthropic’s Mythos and OpenAI’s GPT-5.5-Cyber can help bad actors research vulnerabilities, test approaches, adapt code, and change delivery methods at machine speed and scale. That reduces the time, skill, and coordination needed to move from vulnerability discovery to active attack. When attacks behave this way, security needs to operate in real time with full visibility and context across the attack path.

Shadow AI Is Already In Your Company - What Can You Do About It?

In this video, you will learn why static domain-blocking strategies fail against the modern Shadow AI ecosystem, how Generative AI wrappers, browser extensions, and personal accounts bypass corporate firewalls without triggering an alert, and why network-layer inspection cannot distinguish proprietary code from public Stack Overflow snippets. We break down the limitations of traditional DLP at the clipboard layer, explain how data lineage replaces application allow-lists, and show how the "Glass House" model lets enterprises enable AI productivity while strictly gating sensitive data movement.

Our comments to NIST: AI agent security starts with human identity verification

AI agents have developed advanced capabilities faster than most would have imagined. In enterprise contexts, workforces are delegating more and more tasks to them. While the promise of increased productivity is enticing, the shift from deterministic automated tools to agentic autonomous systems introduces security risks that most enterprises haven’t prepared for.

OpenAI and the environment AI inherits

AI inherits the access permissions that accumulated quietly in organizations for years. Frontier models eliminate the obscurity that once limited what attackers, and even employees, could reach. Sensitive data, stale service accounts, and unreviewed permissions now surface in seconds. Governing identity and access before connecting AI determines whether frontier models become a force multiplier or a compounding risk.

Acronis recognized in Info-Tech report: Why unified, AI-powered platforms are the future

The cybersecurity landscape is changing quickly, and independent research confirms what many organizations are already experiencing: Fragmented tools are no longer enough. A new Info‑Tech report, “Prioritize unified, AI-powered platforms for cybersecurity, data protection, endpoint management and compliance,” explores why leading organizations are rapidly shifting to unified platforms.

Stopping the Agentic Breach: How to Operationalize Your Defense Against Mythos-Speed Attacks

The industry has spent the past few weeks focused on Claude Mythos Preview and the rise of autonomous offensive AI. As outlined in Claude Mythos, Project Glasswing, and the Machine-Speed Security Race, this shift is not only about faster attacks. The same AI-driven acceleration that helps attackers discover weaknesses faster can also help defenders validate exposure sooner. For security operations teams, the challenge is turning that strategic shift into action.

Agentic AI Security: Governing Shadow Agents on Endpoints

Most enterprise security programs were built around a simple assumption, not invalid assumption that data moves when a person decides to move it. AI agents have broken that model, and now act autonomously, reading files, calling APIs, executing code, and transferring data across systems without waiting for a human to approve each step. Many of these agents were never sanctioned by IT or security.

Ep 44: You can't vibe code your way through a production outage

In this episode of Masters of Data, we tackle one of tech's buzziest debates: vibe coding versus production-ready software. We break down where AI-assisted "just make it work" coding genuinely shines (think POCs, prototypes, and getting stakeholder buy-in fast) and where it falls dangerously short when someone tries to ship it to ten thousand enterprise users. We also dig into David's agentic engineering workflow, security risks like malicious MCP servers and supply chain attacks, and why turning a vibe-coded prototype into real software still takes months, not days. Bottom line.

When AI changes the rules, attackers adapt

The dominant narrative around AI in security is one of emboldened defenders suppressing attackers. Yet, not everyone is convinced the future will be so rosy. In a recent Defender Fridays episode, Josh Neil, Co-founder and CTO of Alpha Level, made an argument that cuts against the celebratory mood: as AI makes known attack vectors harder to use, adversaries don't disappear. They adapt. For MSSPs and SOC teams, an adversary that looks like a user is a harder problem than one that looks like malware.

AI Agent Governance Part 1 - Beyond the Chatbot: Mastering AI Agent Governance

In 2024, we talked to AI. In 2026, AI is talking to our systems, our customers, and increasingly, acting on our behalf. With AI agents, we are moving AI from a tool to an actor, from assistance to agency and from outputs to actions. And that changes the nature of risk. AI agents plan, execute, and interact with the world on our behalf. They send emails, move data, trigger workflows, and increasingly operate across systems without human intervention.

Report: Adversarial Use of AI is Evolving

Threat actors are increasingly augmenting their attacks with AI tools, according to researchers at Google’s Threat Intelligence Group (GTIG). For the first time, GTIG observed a threat actor using a zero-day exploit developed by AI, although Google blocked the attack before it succeeded. Threat actors also continue to use Large Language Models (LLMs) for research, reconnaissance, and malware development.

Beyond the Chatbot: Why Your AI Agents are Your Newest (and Most Vulnerable) Colleagues

The era of "typing into a box" is over. For years, we viewed artificial intelligence as a digital assistant—a sophisticated autocomplete tool that waited for human input. But according to Martin Kraemer, KnowBe4’s CISO Advisor for Europe and the Middle East, that dynamic has shifted. We have moved from asking AI questions to giving AI jobs. In a recent deep-dive webinar, Martin explored the transition from AI tools to AI agents.

Introducing the Detectify MCP Server to connect security intelligence into your AI workflows

We are launching the Detectify MCP Server to deliver real-time vulnerability data and attack surface insights directly into your AI-powered workflows. Built for developers and AppSec teams using Claude Code, Cursor, ChatGPT, and Claude Desktop, it delivers security data straight to your AI assistants via a remote-hosted server, giving you hacker-proof guardrails without adding anything new to deploy or maintain.

Why Foundational Security and Governance Are the Real Signs of AI Maturity

In the last couple of years, accelerated AI adoption has created some terrific opportunities for enterprises, allowing them to reshape everything from business models to customer engagement and decision-making. Yet, this also brings up various critical governance challenges. While 52% of organizations have (fully/partially) deployed GenAI, nearly 8 in 10 haven’t reached full AI maturity in cybersecurity, according to a recent Ponemon Institute study in partnership with OpenText.

The Blueprint for a True AI SOC

See how Torq harnesses AI in your SOC to detect, prioritize, and respond to threats faster. Request a Demo John White is the Field CISO for EMEA at Torq. A respected security executive with more than 20 years of leadership experience, John previously served as CISO at Virgin Atlantic, where he led a multi-year transformation deploying the Torq AI SOC Platform to modernize cyber operations.

AI Governance for WordPress: How to Ensure Safe and Ethical AI Use

WordPress sites are adopting AI faster than any other web technology category, and the impact is already visible. Over 61% of WordPress site owners now use at least one AI tool for content creation or marketing. WordPress teams are using that access to write content, automate workflows, run chatbots, and process customer data at a scale that was simply not possible before. But as AI adoption grows, so does the risk.

AI Agent for WordPress: The Complete 2026 Guide

In 1997, IBM’s Deep Blue, the first AI agent, made history by defeating Garry Kasparov at chess. Since then, AI agents have advanced dramatically, evolving from single‑task systems to agents like OpenAI’s Operator, which can autonomously fill out forms, place orders, and schedule appointments. WordPress is a popular CMS that powers more than 20% of the top one million websites. Bringing AI agents into WordPress opens up new possibilities, making sites more capable and adaptive.

Protegrity + Presidio: Secure Sensitive Data in AI Workflows

See how Protegrity and Presidio help developers secure sensitive data in AI workflows. This demo shows how Protegrity AI Developer Edition helps teams discover, protect, mask, and redact sensitive data before it reaches AI models, applications, or analytics pipelines. You’ll learn how developers can.

How an AI SEO Agency Helps SaaS Businesses Rank Faster Online

Software companies often depend on search visibility long before paid acquisition becomes efficient. Yet many teams publish pages without a clear intent map, a crawl plan, or realistic ranking priorities. Results slow down for predictable reasons. Search growth usually improves when technical repair, keyword research, and content planning move in the right order. With that structure in place, SaaS brands can reach evaluators earlier, support longer buying cycles, and build a steadier pipeline from organic discovery.

Can Existing CNAPPs Secure AI Agents in Cloud Environments? Where Each Domain Stops

A CNAPP isn’t a single instrument. It bundles five separately-instrumented security domains — CSPM, CWPP, CIEM, CDR, and a fifth add-on module marketed as AI security — each watching a different observation point. So when leadership asks whether your CNAPP can secure the AI agents your team has shipped, you don’t get one answer. You get five.

DLP for GenAI: How to Prevent Sensitive Data Leaks in AI Tools

Employees are feeding sensitive data into AI tools at a pace most security teams did not anticipate. Source code goes into coding assistants. Customer records get pasted into ChatGPT to draft emails. Confidential contracts land in Gemini for summarization. According to Cyberhaven Labs research, 39.7% of the data employees share with AI tools is sensitive, and the volume is accelerating as AI adoption spreads from individual contributors to entire workflows.

Stop Treating AI Like Another SaaS App

Employees are leveraging AI to boost productivity and adopt skills that would take years to learn. This ranges from drafting content, writing code, and building automated workflows. Some of this use is approved. Much of it is not. For many security teams, the first instinct is to treat this risk like they would any other SaaS risk: discover the app, allow or block access, apply DLP rules, and report on usage. That model works for traditional SaaS, but AI is different.

Developers Are Installing AI Agent Skills Too Fast

235,000 installs per week. That’s how quickly developers are downloading AI agent skills — packages that give AI coding agents new capabilities like shell access, file system operations, cloud access, and deployment permissions. But unlike traditional npm packages, agent skills introduce a completely new security problem: natural language instructions that AI agents can interpret and execute autonomously.

AI didn't create the identity problem. It exposed it. #netwrix #datasecurity #identitysecurity

As access changes constantly and sensitive data moves faster than security teams can track, visibility matters more than ever. Helen R., Director of Engineering at Netwrix, explains why identity and data security can’t operate in silos anymore, especially in the age of AI. Have questions about identity governance, AI, or protecting sensitive data? Experts at Netwrix, including Helen, are helping organizations navigate these challenges every day.

AI Agent Governance: From Policy Framework to Runtime Enforcement

Most enterprise AI agent governance programs publish policies at the bottom three rungs of a runtime enforceability ladder while their architecture diagrams claim rung four. Almost no program reaches rung five, the only rung that produces evidence an auditor cannot dispute. The mismatch shows up in the audit committee meeting. The CISO walks in with the NIST AI RMF mapping, the AUP, the model cards, and the vendor risk assessments for every third-party API the agents call.

7 Best AI Code Security Platforms for 2026

AI changed software development faster than most security programs could realistically adapt. Engineering teams are now generating code with AI assistants, deploying infrastructure through automation, creating APIs dynamically, and operating development environments where software changes happen continuously throughout the day. Development velocity increased dramatically, but the security complexity surrounding that software increased just as quickly.

Deploying AI Agents to Production Kubernetes: A Security Checklist for Platform Teams

Your platform team already runs a production-readiness review on every workload that ships to Kubernetes. When the workload is an AI agent, the PRR doesn’t get thrown out — it gets a delta. Most of the items still apply; specific ones need extension when the workload is non-deterministic, calls tools dynamically, and exercises identity at runtime in ways the manifest didn’t predict.

How to Threat Model AI Agents in Kubernetes: A Practical Framework

Most threat modeling assumes the attacker has to break something. AI agents change that assumption. An attacker who controls a prompt can make the agent misbehave without breaking anything at all. The prompt can be a customer support ticket the agent reads, a document it retrieves, or a tool response it processes — any input the agent treats as context is an attack surface. On Kubernetes, that attack surface has physical form.

Runtime Observability for AI Agents: What to Instrument and Why

Every guide to AI agent observability tells you what to capture — prompts, tool calls, token usage, traces, syscalls. Almost none address which of those signal sources you can still trust when the agent itself is part of the threat model. That distinction is the entire difference between observability that helps your SRE team debug a slow reasoning chain and observability that helps your security team investigate a breach.

Securing AI agents: Why guardrail placement is a key design decision

When teams start building AI agents, especially with managed systems like Amazon Bedrock, they often wonder whether simply enabling guardrails is enough to secure their agents. A framework like Amazon Bedrock Guardrails provides a solid foundation for content filtering and policy enforcement, but having guardrails in place is only part of the equation.

Analyze SMS phishing with an AI agent in Tines

Automate SMS phishing triage with AI — employees upload a screenshot, and Tines handles the rest in under 5 minutes. When employees forward suspicious texts, security teams still have to manually review screenshots, extract indicators, and route cases. This Five Minute Flow shows how to automate the entire process using the Tines AI action with Claude Sonnet — from employee submission to SOC case creation, IOC enrichment, and escalation when multiple employees report the same threat.

Is anything about AI worth the hype?

Dr. Adeel Shaikh Muhammad argues that when it comes to AI in the SOC, alert prioritization, anomaly detection, and SOC efficiency are where the real value is. The rest is mostly noise. On The Cybersecurity Defenders Podcast, the cybersecurity strategist and three-time author draws a clear line between where AI delivers and where the industry has oversold it. Full autonomous SOCs, perfect attack prediction, and replacing human analysts all fall on the hype side. AI narrows focus and accelerates decisions, but the final call still belongs to humans.

Salt Cloud Connect for Github

Your developers are shipping agents, MCP servers, and APIs faster than security can see them. GitHub Connect changes that. Salt scans your repositories and surfaces every agent, MCP server, and API hiding in your codebase, then maps them into the Agentic Security Graph. You see the agentic infrastructure forming in code, before it ever reaches production. No more waiting for runtime to find out what shipped. No more blind spots between dev and prod. Govern what's being built from day one.

Measuring AI-Enabled Success: 3 KPIs Leaders Should Track

AI represents a fundamental shift in how organizations work and innovate. It demands an equally fundamental shift in how technology leaders approach governance. Forward-looking leaders are moving beyond traditional gatekeeping by creating "paved roads": secure, pre-approved pathways that embed security controls, automated data protections, and real-time monitoring directly into AI workflows so teams can innovate rapidly within safe boundaries.

RAG vs Agentic AI: What's the Difference and Why Does It Matter for Security?

Security architects who understood the large language model (LLM) risk two years ago are now confronting a more complex problem. The enterprise AI stack has split into two distinct architectural patterns, retrieval-augmented generation (RAG) and agentic AI, and the security posture required for each is fundamentally different. Conflating them is how programs end up with coverage gaps.

GenAI security management: Governing apps, agents and MCP servers through central policy

Author: Alexander Ivanyuk, Senior Director, Technology Generative AI in business is no longer just one chatbot in one browser tab. In many environments, it is already a mix of web-based AI apps, built-in assistants inside larger platforms, internal agents created for specific workflows and model context protocol (MCP)-connected tools that let AI reach documents, services and business systems beyond the model itself. That changes the conversation completely.

How to Detect AI-Driven Insider Threats | #Cybersecurity Webinar #AI #InsiderThreat #AIsecurity

AI adoption inside organizations is accelerating and so are the insider risks that come with it. Employees use ChatGPT, Claude, Gemini, local LLMs, and daily to improve productivity. But without visibility, sensitive data can leave organizations unnoticed through browser uploads, desktop AI tools, and autonomous AI workflows. In this webinar, Syteca experts discuss.

AI Alone Won't Stop the Breach: Why Email Security Needs Humans-on-the-Loop

2026 has officially become the year of speed, scale and support. The delta between a phishing email landing and a full organizational compromise has shrunk to mere seconds. The reality by the numbers: To close this window, your defense strategy must evolve into a two-step strategy of accuracy and automation.

How Agentic AI and Automation Are Changing Cybersecurity

There is no question that AI is changing cybersecurity in a massive way. In many respects, its impact is comparable to the rise of the internet. AI tools are helping organizations improve efficiency, automate repetitive tasks, and process data at a speed humans simply cannot match. Unfortunately, the same technology helping defenders is also being adopted by cybercriminals just as quickly. For cybersecurity professionals, keeping up with AI and agentic developments is no longer optional.

Autonomous AI vs Zero-Day Attacks: The New Cybersecurity Shift

For decades, finding a zero-day flaw followed a predictable script: a highly skilled human researcher spent weeks staring at source code, digging for edge cases, and manually stitching together an exploit. In April 2026, Anthropic flipped that script by announcing Claude Mythos. This frontier model didn’t just mark an incremental upgrade; it introduced autonomous, machine-speed vulnerability hunting.

Prevent Sensitive Data Exposure With Egnyte AI Safeguards

AI Safeguards help you control what AI can see, share, and do, by protecting sensitive content from AI exposure. AI Safeguards’ coverage extends across Egnyte AI Assistant, to AI agents and our MCP Server. Safeguards are available across Egnyte’s mobile, desktop, and web platforms.

Before you replace your SIEM: AI-driven security requires operational context, not just centralized data

Artificial intelligence is rapidly reshaping how security operations centers (SOCs) function. Many organizations are now evaluating AI-native architectures to reduce workload and accelerate investigations. A new architectural narrative is emerging. A growing set of AI-native security vendors are proposing centralizing telemetry in a warehouse and deploying AI agents to replace the operational role of the SIEM. They want to centralize telemetry, apply AI, and automate the SOC.

Agentic AI Security Guardrails: A Deployment Guide for SOC Leaders

See how Torq harnesses AI in your SOC to detect, prioritize, and respond to threats faster. Request a Demo Noam Cohen is a serial entrepreneur building seriously cool data and AI companies since 2018. Noam’s insights are informed by a unique combination of data, product, and AI expertise — with a background that includes winning the Israel Defense Prize for his work in leveraging data to predict terror attacks.

Prompt instructions won't save your production environment

In July 2025, Replit's autonomous AI coding agent deleted a live production database despite being explicitly instructed to freeze all changes. The agent then attempted to reassure the user with incorrect information after the fact. The team had safeguards in place. The instructions were explicit. Neither stopped it. The conclusion that follows is one the security community should take seriously: you cannot enforce AI agent behavior through the agent itself.

Announcing Claude Compliance API support with Cloudflare CASB

Today, we are extending Cloudflare’s cloud access security broker (CASB) to support the Claude Compliance API. Security and compliance teams can now monitor Claude usage directly in the Cloudflare dashboard. No endpoint agents required. Enterprise security teams have long struggled to see how users interact with sanctioned and unsanctioned applications. The rapid adoption of AI applications has made this harder.

New Claude Integration Brings Audit Data into the Falcon Platform

As organizations scale Anthropic’s Claude model across their workforce, they need the same level of auditability around AI platform activity that they expect from every other enterprise application. A new integration with the Claude Compliance API brings Claude activity into the CrowdStrike Falcon platform to deliver real-time visibility, detection, and automated response for AI use.

AI policy: a template for enterprise security teams

AI adoption inside security teams is now near-universal. Tines' Voice of Security 2026 report found that 99% of SOCs use AI in some capacity. What hasn't kept up is the policy that's supposed to govern it. ISACA's 2026 AI Pulse Poll found 56% of digital trust professionals don't know how quickly they could shut AI down after a security incident. The policy was supposed to handle this.

HIPAA vs. GDPR Compliance: What Is the Difference and Why Does It Matter?

For any business now, data privacy is no longer a legal issue. Companies today collect massive amounts of customer information through AI tools, healthcare apps, SaaS platforms, analytics systems, and cloud services. This has led organizations to take global privacy laws more seriously. This is even more important when it comes to the concept of GDPR vs HIPAA compliance requirements.

OpenAI HIPAA BAA: What It Actually Covers (And What Leaves PHI Exposed)

OpenAI now offers a Business Associate Agreement. For healthcare organizations and health-tech teams racing to deploy AI, that single sentence felt like permission to move fast. But here’s the harder truth: a HIPAA BAA is a legal document, not a technical control. And the gap between what OpenAI’s BAA promises and what it protects is where patient data quietly slips through.

Automating Entra ID tenant destruction with AI

AI-assisted browser automation can turn Microsoft Graph Explorer into a destructive Entra ID administration interface when a signed-in account already holds privileged access. Using Claude for Chrome, browser-side JavaScript, and Microsoft Graph batch requests, destructive actions such as user deletion, account disablement, password resets, session revocation, and Conditional Access policy removal can be automated directly from the browser session.

Common vulnerabilities in AI-developed applications

AI-assisted development tools are changing how software is built. From code generation and automated testing to rapid prototyping and full-stack application scaffolding, Large Language Models (LLMs) are increasingly being used to accelerate software delivery across startups, SaaS providers, and engineering teams. In many cases, these tools are delivering genuine operational value.

CISA's GitHub Leak Is a Preview of the MCP Security Problem Every CISO Is About to Inherit

America's cybersecurity agency left its production credentials sitting in a public GitHub repo for six months. The same failure pattern is now being automated by AI agents in every enterprise running Cursor, Claude Desktop, or Copilot.

Build Custom, High-Impact Training with KnowBe4's Content Creation Agent

In the world of security awareness training, a comprehensive library of relevant and engaging content is a necessity. But even the best training can feel limited when you need to talk about your specific VPN rules, a policy that changed this morning, or a novel threat uniquely targeting your industry today. When you need exactly the right training at the right time customized to your organization, what do you do?

Snyk announces Anthropic updates: Evo integrates with Claude Enterprise, and Snyk Desk comes to Claude Desktop

Today, we're announcing two new integrations with Anthropic that cover both sides of AI-assisted development. Evo by Snyk now integrates with Anthropic's Claude Enterprise, giving security and compliance teams a complete inventory of their Claude environment models, approved MCP servers, per model risk signals, and tool-level permissions in the platform they already use to govern the rest of the stack.

Episode 15 - The Right Eyes: Mythos, and the Future of Vulnerability Discovery

The emergence of advanced large language models like Anthropic's Mythos represents an epochal shift in cybersecurity, fundamentally altering how zero-day vulnerabilities are surfaced and remediated. In this episode, host Richard Bejtlich sits down with Corelight Co-founder Greg Bell to analyze the security implications of this AI-driven bug explosion, highlighting recent AI-assisted vulnerability discoveries across infrastructure mainstays like FreeBSD and Firefox.

Beyond the AI Hype with Netskope: Why Governance is the Bedrock of AI & Cloud Integration at Embecta

Modern enterprise solutions—ranging from cloud data and power platforms to agentic AI and API connections—require rigorous oversight. Every platform integration must be evaluated through the lenses of risk, data compliance, and privacy to ensure secure operations. Netskope provides the necessary visibility and control for all data paths, including APIs and cloud-based AI platforms, helping Embecta enforce the data compliance and privacy standards required when integrating disparate applications.

Best SaaS AI SEO Companies in the United Kingdom for Technical SEO at Scale

Technical SEO for SaaS is not the same discipline as technical SEO for e-commerce or media. SaaS marketing sites are frequently built on JavaScript frameworks - React, Vue.js, Next.js - that create rendering challenges traditional crawlers struggle with. Product documentation hubs generate thousands of dynamically created pages that require careful indexability management. App login portals must be correctly blocked from crawling without inadvertently blocking adjacent marketing content.

Predictive Indicators Every CX Leader Should Watch

Customer experience teams are under pressure to spot problems before they become visible in missed service levels, customer complaints or rising costs. Predictive indicators help leaders move beyond reporting what has already happened and start identifying where demand, performance or customer sentiment may shift next. For contact centres, the most useful signals are those that connect customer behaviour, operational capacity and team performance in a way that supports faster, better-informed decisions.

SMBs Hit a Cybersecurity Breaking Point as 91% Fear AI-Driven Attacks, Driving Shift to MSP-Led Security Models, WatchGuard Finds

LONDON, May 20 2026 -New research from WatchGuard Technologies, a global leader in unified cybersecurity for MSPs, reveals that while most businesses believe they are adequately staffed, the complexity, speed, and scale of modern threats - especially those powered by artificial intelligence - have outpaced what internal teams can realistically manage. The result is a fundamental shift away from do-it-yourself security toward externally delivered, always-on protection models.

How AI Is Transforming Detection Engineering

One of the most important shifts AI enables in detection engineering is changing where engineers spend their time. Traditionally, a significant portion of detection development effort is consumed by implementation details: writing complex SQL queries, building enrichment pipelines, handling edge cases, tuning rule logic, writing tests, documenting detections, and repeatedly iterating on detection logic. Those tasks are necessary, but they are also time-consuming.

Misconfigured Security Controls Open the Door for Storm-2949

The Microsoft Defender Security Research Team and Microsoft Threat Intelligence documented a campaign in which Storm-2949 abused Microsoft Entra ID accounts to exfiltrate data from Microsoft 365 and Azure environments. The attack shows how cloud intrusions increasingly unfold through identity systems, administrative features, and legitimate platform capabilities rather than obvious malware or traditional endpoint compromise.

Building the Post-Mythos Security Organization: From Episodic Security to Continuous Assurance

In an era where AI accelerates both innovation and adversarial capability, security leaders are confronting a difficult reality: traditional approaches to cyber defense are no longer sufficient. Cyberhaven’s Office of the CISO is responding with a forward-looking strategy designed not simply to keep pace with emerging threats, but to fundamentally redefine enterprise readiness in a post-Mythos world.

Guarding the Manufacturer's Core: Securing Intellectual Property in the Age of AI at Renesas

Organizations like Renesas face critical risks when utilizing AI, as these platforms often incorporate user-submitted data into their models. Significant security incidents have occurred where sensitive source code, firmware, and proprietary designs were inadvertently made public after being uploaded for testing. A major business risk involves the potential loss of intellectual property, which can directly impact an organization's primary revenue streams. Beyond data leakage, AI presents risks through "poisoning" and the fact that AI-generated output is frequently inaccurate.

AI Security Architecture: Zero Trust Patterns for GenAI and ML

There is no doubt that AI, or Artificial Intelligence, is rapidly changing how businesses are operating. However, it also brings new risks when it comes to data. As per industry reports, 72% of companies mention that there has been a significant increase in organizational cyber risks. It is therefore necessary to have a strong AI security architecture that helps to protect sensitive information. In light of this, 85% of organizations are now increasing their cybersecurity budget.

Codex builds at AI Speed, 1Password Secures it

Secure secrets for agentic workflows with 1Password MCP Server and Codex As AI agents write, execute, and ship production code, they need access to systems like databases, APIs, and deployment pipelines. With 1Password Environments MCP Server for Codex, instead of putting credentials directly into prompts or files, we provision a secure runtime environment where secrets are mounted, used, and discarded, with user authentication required at the moment of access.

Balancing AI Innovation and Risk: Enhance Organizational Resilience

‍ Artificial intelligence (AI) offers businesses vast opportunities to boost efficiency, improve decision-making, and innovate faster. Yet, these benefits come with significant risks that can impact business operations and resilience if not managed carefully. This article explores how organizations can balance leveraging AI’s advantages while controlling its inherent risks. ‍

Govern AI agents the right way with Identity Manager by One Identity

AI agents are becoming an inseparable part of identity governance, sometimes being created by other AI agents and acting proactively across platforms at machine speed — but who’s watching them? Identity Manager 10.0 by One Identity answers that question. Hear Ingrid Thorpe, director of product management for Identity Manager, explore how the solution governs agentic workflows, tackles agent-specific risks and integrates across cloud and enterprise platforms, holding non-human identities (NHIs) accountable.

The Authorization Trap: Why Your IAM Controls Don't Cover AI Agent Risk

If there's one idea that shaped RSA 2026, it was identity. Vendor booths, keynotes, conversations. All roads led back to the same instinct: control identity, control access, control risk. That instinct is directionally correct. Identity governance is foundational. But identity answers only part of the question agentic AI is asking. Here's the part it doesn't answer: authorization tells you what an agent was permitted to do. It says nothing about whether what it actually did was appropriate.

AI Agents, Enterprise Scale, No Compromises: Now via AWS

A couple of years ago, AI agent security was a niche conversation. The practitioners who took it seriously were a small group of researchers, a handful of forward-looking CISOs, and a few founders who had watched the attack surface forming in real time. The broader market hadn't caught up yet. It has now. Enterprises are deploying AI agents at scale across platforms. The productivity gains are real. The competitive pressure to adopt is real.

What it took to get 90% of Tines using AI workflows in production

Every conversation I have with CIOs and IT leaders right now starts the same way. They're not short on activity. They've got pilots running, tools deployed, teams experimenting. What they don't have is much to show for it. The data backs it up: 92% of companies are ramping AI investment right now. Only 1% consider themselves mature.

Why AI-era attacks demand deterministic defense

The security industry spent a good chunk of early 2026 debating whether Anthropic’s Mythos and OpenAI’s Daybreak are truly dangerous or just good marketing. It's a reasonable debate. But while we're having it, attackers are asking a different question: how do we use tools like this to move faster than defenders can respond?

LLM Access Controls and Audit Logging for Security Teams: A Practitioner's Guide

Most organizations have an acceptable use policy for AI tools. Very few have controls that actually enforce it. The gap between what the policy says and what security teams can detect is where insider risk lives when it comes to large language model (LLM) usage.

Why AI Alone Isn't Improving Vulnerability Remediation

AI is widely used in exposure management, but most implementations stop at prioritization and analysis. While AI improves visibility and decision-making, remediation still depends heavily on manual ownership, coordination, and inconsistent processes. To truly improve vulnerability remediation outcomes, AI needs to extend into the execution layer, helping identify owners, define remediation plans, and deliver fix-ready work that turns decisions into action.

Shadow MCP Servers: The AI Infrastructure You Can't See

In 2012, the "Shadow IT" crisis was employees putting files in Dropbox for convenience. In 2026, the crisis is Shadow MCP. Instead of a simple file storage app, security teams are now facing unvetted AI agents with the power to read from and write to internal systems. These servers are often running on infrastructure that was never reviewed, never approved, and remains entirely invisible to governance.

Essay Grader AI: The Complete Guide to Saving 80% of Your Grading Time

Teachers spend countless hours every week reviewing student essays, providing feedback, and assigning grades. For many educators, grading has become one of the most time-consuming and mentally exhausting parts of the job. What if you could dramatically reduce that burden while actually improving the quality of feedback your students receive?

The Agentic Security Graph: Get Visibility into your AI Security Risks

As enterprises shift from conversational to agentic AI, the real risk moves from model outputs to the action layer; the MCP servers and APIs through which agents execute real-world tasks. The Agentic Security Graph frames this risk across three interconnected layers (LLM, MCP servers, APIs), showing how compromises at any layer can propagate and why existing LLM-focused controls leave the most consequential surface unmonitored.

Kevin Mandia on AI-Powered Attacks: The Race Just Got Faster | Black Hat | Reach Security

At Black Hat last year, we sat down with Kevin Mandia to talk about what's coming. His take: offense is going to accelerate with AI. Not slow down. Not plateau. Accelerate. When you've run more red teams than practically anyone on the planet, the pattern is clear. Getting into a victim network is already a race. AI compresses those time frames further. The attack surface isn't changing. Misconfigurations, things that slipped, controls that were on and got turned off. The entry point stays the same. AI just makes the race to exploit it faster.

Partnerships, AI, and Emerging Threats with Peter Johnson - The 443 Podcast - Episode 371

Recorded at WatchGuard’s EMEA Partner Conference, in Dubrovnik, Croatia, this episode of 443 – Security Simplified features Peter Johnson from Schwartz GmbH for a conversation on how cybersecurity priorities are evolving across Europe. Peter discusses the increasing complexity organizations face when balancing security, compliance, and operational efficiency, along with the challenges of supporting customers and partners with varying levels of cybersecurity maturity.

The Path to Autonomous Networking Starts Here

Networks have never been more critical, more complex, or more difficult to run with confidence. The infrastructure powering global finance, healthcare, and commerce has outgrown the tools built to manage it, and the teams responsible for keeping it running deserve better than guesswork. Forward is on a mission to change that.

Forward Predict: Know the Impact of Your Network Changes Before You Push

What if your team could know exactly what a network change would do before it touched production, not a best guess, not built on incomplete data, but a mathematically verified outcome drawn from an accurate model of your actual network? That is what Forward Predict delivers.

What Is MCP Security? 9 Things Every CISO Needs to Know

Your AI agents had a productive day. Nobody can tell you what data they touched. A developer opens Cursor and connects it to a GitHub MCP server and a Postgres MCP server. The agent reads the repo to understand a schema change, finds an AWS access key in a config file, and uses it to run a migration against staging. The key now lives in the agent's context, in the Postgres query log, in the chat history, and in whatever artifact the developer copies out. No alert fired. No policy triggered.

What 500+ Industry Experts Told Us About Securing Autonomous AI: A Policy Roadmap

When the US Center for AI Standards and Innovation (CAISI) asked for public input on securing agentic AI systems, the response was massive: over 500 detailed submissions from Fortune 500 companies, defense contractors, AI startups, and cybersecurity firms. The result is substantial insight into how industry views the regulatory challenges of autonomous AI agents and what they think policymakers should do about it.

AI-Driven Cyber Warfare Reshapes Global Defense Readiness

This article was originally published in TechRadar Pro. The Iran conflict is serving as an AI testbed for the next era of cyber conflict. Most organizations are watching the tactics and impact unfold with cybersecurity defenses that are simply not prepared for this level of sophistication. Meanwhile, technology leaders are seeing AI as both their biggest opportunity and a major new attack vector.

Why Legacy DLP Fails Against Agentic AI

Security teams that deployed legacy DLP years ago built something real. The rules fire. The alerts go out. Compliance boxes get checked. The problem is not that those programs stopped working. It is that the threat moved, and the architecture did not. Agentic AI has introduced a class of data movement that legacy DLP was never designed to govern: autonomous, continuous, multi-step, and operating at machine speed across systems that static rules cannot enumerate in advance.

Agents need boundaries with Fotis Chantzis from OpenAI, Zero-Shot Learning

Agents need boundaries | Fotis Chantzis from OpenAI Agents don't fit old identity models. As OpenAI’s Agent Security Lead, Fotis Chantzis has a front-row seat to see how agents push identity systems beyond what they were built to control. That’s where things start to fall apart and where most teams lose control.

Grid by LimaCharlie is now in beta: Agentic SecOps for the stack you have

Grid is LimaCharlie's agentic AI layer for security teams that want AI operations running across their existing stack right now. Security providers and SOCs need access to AI capabilities without waiting for a migration window, a contract renewal, or a vendor to ship the features they need. Every major security vendor is offering some version of AI. CrowdStrike has Charlotte AI. SentinelOne has Purple AI. Microsoft has Copilot for Security.

When humans are a minority, IAM requires a rethink

In a typical enterprise, non-human identities (NHIs) are thought to outnumber human users by at least 50:1. NHIs are various and include: It is estimated that the NHI: human ratio may have leapt to 144:1 as more AI agents were deployed over the last year. CISOs are already alive to the risks posed by orphaned accounts on their systems. They know that automated rotation is required to revoke privileges as soon as NHIs complete tasks.

OpenAI's Fotis Chantzis on why identity protocols weren't designed for agents

Zero-Shot Learning is a podcast for AI builders, hosted by Nancy Wang, Chief Technology Officer at 1Password, and Dev Tagare, Senior Director and Head of Engineering for Gemini Enterprise & Business at Google. Together, they’ve built and scaled AI systems at the infrastructure and product layers and bring a builder's perspective to every conversation.

Warning: Phishing Attacks Are Abusing the Kuse AI App

Attackers are abusing the storage and sharing features of Kuse, a free AI app, to assist in phishing campaigns, according to researchers at Trend Micro. Kuse is a legitimate agentic AI platform used by employees to streamline workflows. Users can share files with coworkers, which generates a link hosted by Kuse’s domain. In this case, attackers are abusing the share feature to generate legitimate-looking phishing links.

Using Generative AI for Incident Response Automation: A Complete Guide to AI Agent Development

Security Operations Centers run on caffeine and context-switching. Any given shift means hundreds of alerts, tools that don't talk to each other, and analysts who know that somewhere in that noise is a real threat - they just need time to find it. That's the core tension AI agent development is built to resolve. This guide covers the full lifecycle: from scoping your first use case to maintaining a production-grade agentic SOC.

What Finance Teams Actually Want From AI

Of all industries, it feels like it's the finance industry that's in the best position to benefit from AI integration, especially finance teams. After all, it's those teams that typically have to manually deal with data - and that's just the kind of thing that AI can help with. With that said, though AI can be beneficial for finance teams, it's far from a slam dunk. AI integration among finance teams has been slower and less extensive than it could have been, and that's in large part because employees haven't been given the AI tools that they actually want, or which make their jobs easier.

AI builders can now easily access 1Password secrets management and developer tools

AI coding tools have changed who builds software. The barrier to entry has dropped to the point where a designer, an analyst, or a first-time founder can turn an idea into a working app in an afternoon. That shift is real, and it's accelerating.

How to Reduce Alert Fatigue in AI Agent Detection: Why It's a Unit-of-Detection Problem, Not a Triage Problem

When AI agent workloads start generating more alerts than your SOC can keep up with, the instinct most teams reach for is to deploy more triage on top of what they already have. If the SIEM is producing thousands of atomized alerts, plug in something downstream that can cluster, prioritize, and auto-resolve them faster than a human can. The market has consolidated around exactly this answer.

What Is an Al Agent in Cybersecurity?

At the Milken Conference in May 2026, Robert F. Smith, founder and CEO of Vista Equity Partners, described a shift that every security leader should hear. Software, he said, has moved through three states: product, then service and now worker. "That agent, that software, actually does work." Companies that do not make the transition to software as a worker, he was blunt, risk being disintermediated entirely.

Security infrastructure for building AI in SecOps

Some of the security industry is still cautiously evaluating its relationship with AI. They are weighing questions, sitting with uncertainty, and waiting for something to ease their concerns about trusting AI in production. This post isn't for that group. This is for AI tool developers already in motion. The ones who vibe-coded a log parser over a weekend, spun up local inference on dedicated hardware, or ran cross-model research pipelines across multiple data sources.

What Your Board Gets Wrong About AI Security

Editor's note: This article was originally published by Craig Riddell on LinkedIn. It has been republished here with the author's permission. Boards are giving AI security more airtime than ever. What they're not giving is the right framing. A year or two ago, AI was mostly a question of experimentation risk. Today, it's tied directly to revenue, customer experience, operational efficiency, and competitive advantage. The urgency is real, and it's translating into aggressive deployment timelines.

Prompt Analysis for AI Attack Detection: Four Signal Categories, Three Blind Spots, One Correlation Layer

At 2:47 PM on a Tuesday, a customer support agent receives a routine ticket asking about return policy edge cases. The agent retrieves a section from your internal policy wiki through RAG to formulate the response. Three weeks earlier, an attacker had planted a hidden instruction in that wiki page. Bedrock Guardrails scored the retrieved context at 0.04 — well within benign range.

MITRE ATLAS for AI Agent Attack Detection: A Complete Mapping

MITRE ATLAS catalogs sixteen tactics and eighty-four techniques adversaries use against AI systems, including fourteen agent-focused techniques added through the October 2025 Zenity Labs collaboration. It is the canonical taxonomy a security architect’s CISO, auditor, or RFP will name. It is not a detection plan. ATLAS organizes around adversary objectives.

Redesigning Security Culture for the Agentic Age

The launch of platforms like Moltbook, OpenClaw, and RentAHuman in early 2026 has provided an unsettling glimpse into the future. We are entering a phase of the digital workplace where AI agents no longer just assist us, they interact with one another, act autonomously in the physical world, and even hire humans for manual labor. In this environment, the traditional lines of control and agency are being redrawn.

The AI attack surface: What MSSPs and SecOps teams need to watch

AI tools are moving faster than the security controls meant to govern them.In this episode of Defender Fridays, Cisco's Cybersecurity Technical Solutions Architect Katherine McNamara walks through changes in the threat landscape as organizations rush to integrate AI without applying basic security discipline. When Katherine meets with customers to discuss AI security, the conversation almost always starts and ends in the same place: data leakage. Someone might upload sensitive files to a public LLM.

AI Agent Attack Detection: The Complete Framework for Security Teams

It usually starts the same way. The CISO comes back from a board meeting having signed off on agentic AI for production. The SOC lead is told, in roughly that many words, to build detection for the agents. And the security stack she has — CNAPP for posture, EDR on the nodes, container runtime sensors, a SIEM ingesting everything — was architected before AI agents existed as a workload class.

OpenAI Daybreak and the Future of Secure Software Development

OpenAI recently introduced Daybreak, a cybersecurity initiative designed to apply frontier AI models to vulnerability discovery, secure code analysis, and earlier remediation across the software lifecycle. By combining advanced reasoning and planning capabilities, Daybreak aims to help organizations identify and address weaknesses before they reach production. This is a meaningful step forward, but it is also a continuation of a long-standing approach.

Salt Agentic Security Platform

Most enterprise AI security investment is focused on the model layer—guardrails, output filtering, LLM governance. That's necessary. It's not sufficient. AI agents take actions: they call APIs, invoke MCP servers, access databases, and trigger downstream workflows. The Salt Security Agentic Security Platform was built to secure that action layer (the infrastructure your agents actually operate across).

What is shadow AI? And why GenAI usage monitoring matters for MSPs and SMDs

Author: Alexander Ivanyuk, Senior Director, Technology Generative AI is no longer a side experiment inside businesses. It is moving into normal work: writing, summarizing, coding, research, customer support, internal search and repeatable workflows. OpenAI says it now serves more than one million business customers, more than seven million ChatGPT workplace seats, and roughly 8x growth in weekly enterprise messages since November 2024.

What is AI penetration testing?

As organisations continue integrating AI capabilities into customer-facing applications, internal tooling, and operational workflows, the security implications of these systems are becoming increasingly important. Large Language Models (LLMs), AI assistants, and automated decision-making features are now appearing across SaaS platforms, support systems, and enterprise applications, often connected directly to sensitive data and business processes.

AI governance: a practical guide for enterprise leaders

It's 9:47 AM on a Tuesday. A Slack message from legal lands in the security channel: "Did anyone approve the marketing team's new AI vendor? They're feeding customer data into it." Nobody approved it. The vendor's terms say they can use input data for model training, and the contract was signed three weeks ago. That moment, some version of which plays out at most organizations now, is what makes AI governance an operational priority rather than a compliance exercise.

Optimize Zscaler Secure Internet Access (ZIA) Controls | Demo Video

Zscaler Secure Internet Access (ZIA) provides powerful secure access, inline inspection, decryption, and data loss prevention capabilities. But as your security and IT environments scale, and security controls change, Zscaler ZIA protections can drift away from established baselines, increasing your risk and leaving you open to attack. Reach analyzes your Zscaler ZIA controls to find and fix misconfigured controls, activate unused capabilities, and stop configuration drift. This hardens your defenses and protects you against fast-moving adversaries.

AI-assisted vulnerability reporting with Shane Warden

Join us for this week's Defender Fridays as Shane Warden, Principal Architect at ActiveState, shares what it's actually like to be on the receiving end of AI-assisted vulnerability reporting and what open source maintainers are already dealing with that the rest of the industry will face soon. At Defender Fridays, we delve into the dynamic world of information security, exploring its defensive side with seasoned professionals from across the industry. Our aim is simple yet ambitious: to foster a collaborative space where ideas flow freely, experiences are shared, and knowledge expands.

Device Trust MCP Server: Natural language queries for your entire fleet

Today we're releasing the 1Password Device Trust MCP Server, an open-source server that connects your Device Trust data directly to the AI tools your team already uses, like Claude or ChatGPT. It's available now for all customers on Device Trust Connect.

The 10 Best Enterprise AI Data Loss Prevention Tools

AI usage is invisible to most security tools. Network monitoring sees HTTPS traffic. Endpoint detection sees browser activity. CASB platforms see cloud application access. None of them sees what employees type into AI prompts or upload to AI services through web forms. This invisibility creates a problem. Organizations can’t prove they didn’t expose customer data through AI because they can’t see the data that employees shared.

AI Agent Security Risks: What Enterprises Need to Know in 2026

AI agents are already inside most enterprise environments. They complete tasks, connect to live systems, and make decisions that used to require a human. Gartner projects that 40% of enterprise applications will include task-specific AI agents by the end of 2026, up from less than 5% today. What was an experiment two years ago is now a core part of how work gets done. If your organization is adopting AI agents or planning to, security is not something you can figure out later.

Fighting AI-Assisted Ransomware Threats

This Anti-Ransomware Day, it's important to recognize the ever-changing landscape of cyber threats and how organizations can fortify their defenses. The evolution from traditional ransomware to cyber extortion over the last few years reflects a professionalized, decentralized ecosystem. To arm your organization against this danger, understanding the current landscape and implementing robust defense strategies is essential.

The End of the Exploit Window: How Frontier AI Is Changing CVE Prioritization

When a new vulnerability is announced, the race begins. Security teams jump into action, checking exposure, triaging events, identifying affected systems, and figuring out how quickly they can patch. The clock is ticking and they know it. At the same moment, threat actors are doing their own version of that work. They’re reading the same advisories, watching the same feeds, and asking a much simpler question: Who is still vulnerable?

Why AI-Only Threat Intelligence Is a Risk Your Organisation Cannot Afford

SaaS-only platforms are betting everything on automation. But when the threat landscape demands judgement, data volume alone is not the answer. For years, a certain category of threat intelligence vendor has sold the same idea: feed your data into our platform, let the AI process it, and your security team will have everything they need. It is a compelling proposition, particularly for organisations under pressure to demonstrate coverage without expanding headcount.

PDPA Compliance for Digital Products: What Singapore Businesses Need to Know in 2026

Singapore's digital economy continues to grow rapidly in 2026. Businesses are launching SaaS platforms, eCommerce websites, fintech portals, customer dashboards, and mobile applications faster than ever. At the same time, consumers are becoming more aware of how their personal data is collected, stored, and used. This shift has made compliance with Singapore's Personal Data Protection Act (PDPA) a critical requirement for every digital product.

How Bank Statement Analyzer AI Tools Are Simplifying Financial Management

Managing personal finances has become significantly more complicated over the last decade. Most people no longer rely on a single bank account or one payment method. Daily transactions are spread across debit cards, credit cards, subscriptions, online banking platforms, digital wallets, and international payment systems. As financial activity becomes more fragmented, understanding spending habits manually becomes increasingly difficult.

EU AI Act Compliance Checklist - A Practical Guide for Businesses

An EU AI Act compliance checklist is a structured framework that helps organisations systematically identify, classify, and govern all AI systems within scope of Regulation (EU) 2024/1689. It covers AI system inventory, risk classification (unacceptable, high-risk, limited, and minimal), conformity assessment requirements, technical documentation (Annex IV), human oversight obligations, GPAI model obligations, and post-market monitoring.

Navigating the Cybersecurity Landscape in India Empowering Human and AI Agents

The Asia-Pacific and Japan (APJ) region, with its dynamic economic growth and technological advancements, presents unique challenges and opportunities in the realm of human risk management and agentic risk management, particularly within the financial services sector. As financial institutions strive to protect themselves from increasing cyber threats, they must align their security practices with the regulations set forth by central banks across the countries.

The Rise of Cyber Threats and AI in the Philippines: A New Era Beyond Legacy Security

The Philippines, like many other nations, is witnessing a dramatic increase in cyber threats, fueled by the rapid adoption of digital technologies and the proliferation of sophisticated cybercriminals. This article examines the evolution of cyber threats in the Philippines, with a focus on phishing, email security and the risks posed by agentic AI.

Six MCP Security Incidents Every Security Leader Should Know

In July 2025, an AI agent reviewed a support ticket, queried a production database, and leaked integration tokens directly to the attacker watching the thread. Months earlier, another AI followed "hidden instructions" in a public repository, exfiltrating private code into a visible pull request. In both cases, the AI wasn't broken; it simply obeyed the attacker instead of the developer.

Your AI Agents Are Already Acting. The Question Is Whether You Can See What They're Doing.

In conversations with CISOs about their agentic environments, the question I ask first is not whether they have agents deployed. Most do. It is not whether those agents are creating value. Most are. The question I ask is whether they have mapped their Agentic Security Graph. Almost none of them have. And that gap, between the agentic infrastructure that exists inside their organizations and the visibility they have into it, is where the most serious AI security risk in the enterprise lives right now.

Workshop: Analyzing Real Malware with Claude Code and LimaCharlie

In this hands-on workshop we will analyze an unknown binary, quickly extract indicators, and determine the binary’s core functionality. We'll give Claude the LCRE (LimaCharlie Reverse Engineering) tool to accelerate analysis and interpretation by identifying configuration details, key behaviors, and any additional indicators useful for rule building. We'll use this information to craft detection rules for this sample.

Does the rise of AI mean human-led SOCs are obsolete? With Dr. Adeel Shaikh Muhammad [322]

Dr. Adeel Shaikh Muhammad, a cybersecurity strategist and global speaker with over 16 years of experience across information security, networks, and systems. Adeel brings a practical perspective on how organizations can adapt to evolving cyber threats and the growing role of AI in cybersecurity.

Shadow IT vs Shadow AI: What's the Difference?

Imagine a customer service representative at your organization uploads sensitive customer data into an AI tool to draft emails more quickly. When an employee uses an AI tool without IT approval, it is known as shadow AI, and such scenarios are becoming increasingly common. Among employees who use AI at work, 78% report using tools that have not been formally approved by their organization, according to Microsoft’s 2024 Work Trend Index.

Falcon Shield: ChatGPT Enterprise Compliance API

Learn more about how CrowdStrike's has expanded its ChatGPT Enterprise integration to deliver deeper audit logging and continuous activity monitoring within CrowdStrike Falcon Shield SaaS security. This expansion enables monitoring of authentication activity, administrative changes, tool usage, Codex events, and conversation-level logs across ChatGPT Enterprise workspaces. Subscribe and stay updated!

By AI, With AI, For AI: Building IT services in the AI-first era

MSPs want to grow. Yet the cost of growth keeps eating the margin that extra growth was supposed to deliver. Traditionally, more customers means more endpoints, more tools, more alerts, more billing entities, more compliance frameworks. Headcount scales with the work, but margins don't seem to keep up. That problem has a new shape now. AI is changing how every IT environment is built, run and protected and the speed at which they are done.

Frontier AI and the Demise of Hardware Security

The cybersecurity industry has long relied on a simple idea: find vulnerabilities, patch them, and measure success by how fast you close the gap. “Time-to-patch” became a badge of honor. That model no longer holds. The rise of Mythos-class Frontier AI Models introduces a different kind of threat. AI-driven, agentic attacks operate continuously, discover weaknesses automatically, and execute at a scale no human team can match.

Falcon AIDR Detects Threats at the Prompt Layer in Kubernetes AI Applications

AI is introducing a new class of threats that don’t look like traditional attacks and can’t be detected with conventional tools. The AI applications that organizations deploy in the cloud interact with large language models (LLMs) through prompts and responses. This prompt layer has emerged as a new attack surface, where risks like prompt injection and sensitive data leakage can go unnoticed.

Session on How much of Mythos based attacks can you prevent using modern IDAM techniques?

In this session at ETCISO IDAM Summit 2026, our Founder & CEO Mr. Anirban Mukherji discussed Identity Access Management (IAM), data protection challenges, and AI governance for modern organizations. He covers SSO, MFA, legacy system hurdles, DBT data flows, Shadow AI risks, and practical steps like patch automation, least privilege access, and AI agent controls. Drawing from the Abhimanyu Chakravyuh metaphor, he explains how strong IAM contains breaches. Learn about vendor sovereignty, geopolitical risks, and miniOrange's expertise in IAM, AI security, and privacy.

DevOps Threats 2026: GitProtect Reveals AI and Compliance Danger Zones

As DevOps environments become primary attack surfaces, protecting your intellectual property (IP) requires a data-driven understanding of the modern threat landscape. The 2026 “DevOps Threats Unwrapped Report” by GitProtect accelerates building your cyber awareness. It brings you the latest statistics, highlighting contemporary trends in DevSecOps. It also dives into dozens of real attacks and breaches affecting SaaS platforms in 2025 in 10 different areas.

Dokie AI Review: GPT Image 2 Makes AI-Generated PPTs Look More Professional

Many AI presentation makers can create slides quickly, but the final result often feels unfinished. The slide structure may be usable, but the visuals can look generic, random, or disconnected from the topic. This is where Dokie AI stands out. Dokie AI is an AI presentation maker built for creating PPT-style decks. It helps users generate structured presentations from prompts, notes, documents, or existing content. With the new support for GPT Image 2, Dokie AI has improved one of the most important parts of presentation quality: the images.

How to compare and choose the best AI remote desktop solutions for MSPs

MSPs managing hundreds or thousands of endpoints cannot afford remote support that lives in a separate tool, on a separate license, with a separate login and a separate workflow. Every extra console adds friction between monitoring, troubleshooting, patching, and security response. That is exactly why AI remote desktop matters now: not as a buzzword, but as a way to shorten the path from issue detection to issue resolution while keeping technicians in one operational environment.

What are MCP and RAG? And why should MSPs and SMDs care?

Author: Alexander Ivanyuk, Senior Director, Technology AI is moving fast, and with that speed comes a new set of terms that many business readers are now hearing for the first time: RAG and MCP. They may sound technical, but the ideas behind them are actually practical. They describe how modern AI systems get better information, connect to business tools, and, in some cases, go beyond answering questions to carrying out work.

The Teleport Agentic Identity Framework in 3 minutes

AI agents are rapidly moving into production, but most organizations are still deploying them on top of legacy identity systems built around passwords, secrets, and fragmented access models. In this video, we introduce the Teleport Agentic Identity Framework, a standards-driven approach for deploying AI agents securely across infrastructure using cryptographic identity, governed access, and continuous visibility.

Hacking LLMs using LinkedIn #aisecurity #ai #llm

Mend.io, formerly known as Whitesource, has over a decade of experience helping global organizations build world-class AppSec programs that reduce risk and accelerate development -– using tools built into the technologies that software and security teams already love. Our automated technology protects organizations from supply chain and malicious package attacks, vulnerabilities in open source and custom code, and open-source license risks.

How Fidelis Deception Helps Defend Against AI-Accelerated Intrusions

AI-powered attackers are faster and more systematic than ever. But they still trust what they see. Deception technology controls what they see. 87% of security leaders say AI-related vulnerabilities grew faster than any other risk in 2025 44% year-over-year rise in exploitation of public-facing applications in 2025 300K+ AI platform credentials exposed via infostealer malware on dark web in 2025.

Why the Mythos Era Calls for Deception-Based Defense

Deception and Claude Mythos is no longer just a cybersecurity conversation. It’s a paradigm change in how organizations need to consider cyber resilience in the era of AI. Enterprises are facing a new threat landscape in which attackers can find exploits quicker, conduct enterprise-wide reconnaissance with low-level automation, and exploit enterprise assets with unprecedented accuracy on an enterprise-wide scale.

Your AI coding assistant is leaking secrets

AI desktop assistants and coding tools need credentials to reach external services, and many of them store those credentials as plaintext JSON at predictable paths in the user's home directory. This research covers how credential storage works across 14 popular AI tools, where OS keychain integration is present or missing, and eight attack scenarios that turn that exposure into real risk, from malware-based theft to remote session hijacking to supply-chain compromise via MCP servers.

OpenAI Daybreak Just Changed Cybersecurity (Again)

OpenAI just announced Daybreak, their cybersecurity AI model with three tiers of access. GPT-5 handles general work. GPT-5.5 does secure code reviews, vulnerability triage, malware analysis and patch validation. GPT-Cyber handles red teaming and penetration testing. In this episode of Razorwire Raw, James Rees explains what Daybreak means for the cybersecurity industry and why vulnerability scanning companies, pentesting firms and security tool vendors should be concerned.

Extending Security to MCP Servers: Closing a Critical Gap

The Model Context Protocol (MCP) is a de facto standard for providing structured access to privileged systems for AI agents and external integrations. It acts as a USB-C port for AI, enabling faster innovation by allowing organizations to expose tools, resources, and workflows without the time-consuming work of building APIs. Adoption has surged in recent months, and categories like payments, project management, and developer platforms are already beginning to reap the benefits.

Shadow AI is a fear response, and banning it makes it worse

This post is based on Mackenzie's conversation with Noora Ahmed-Moshe on The Secure Disclosure podcast. Listen to the full episode. A company lost a million dollars because someone on a litigation call ran an AI note-taker. As behavioral scientist Noora Ahmed-Moshe explains on the podcast, the tool summarized a confidential conversation and sent it to the opposing party, who used it to force a settlement on their terms.

Navigating Human and Agentic Risks for Financial Institutions in the APJ Region

The Asia-Pacific and Japan (APJ) region, with its dynamic economic growth and technological advancements, presents unique challenges and opportunities in the realm of human risk management and agentic risk management, particularly within the financial services sector. As financial institutions strive to protect themselves from increasing cyber threats, they must align their security practices with the regulations set forth by central banks across the countries.

The Best AI Rollout Is the One Nobody Noticed

Most internal AI initiatives fail the same way: someone builds a thing, sends a Slack announcement, runs a lunch-and-learn, and three months later the thing has two active users. The failure mode isn't the AI. It's the ask. Every new surface is a decision engineers have to make: remember to open it, remember to use it, remember to trust it. Seal's approach for our own R&D team was to eliminate the ask entirely. The AI goes where our engineers already are, at the moment they need it.

Is Your LLM at Risk? Explaining Prompt Injection Attacks

In early 2023, Stanford University student Kevin Liu persuaded Microsoft’s Bing Chat to reveal the hidden system prompt shaping its behavior. By “persuaded”, Kevin simply asked the large language model (LLM) to ignore its previous instructions and print “what was written at the beginning of the document above”. In response, Bing Chat disclosed its internal codename “Sydney”, along with the rules governing how it interacted with users.

AI Coding Tools Are Creating a Security Gap We Must Close Immediately

Developers love AI coding tools. And why wouldn’t they? After all, they write code faster. They reduce repetitive work. They help junior engineers ship features that used to take days. But there’s a problem no one wants to talk about at the planning meeting. AI coding tools are producing insecure code at massive scale. And the industry is running out of time to fix it.

Skygen AI for Agencies: How It Handles the Work That's Quietly Killing Your Margins

Agency margins are a math problem nobody wants to talk about openly. You win a client. You scope the work. You staff it. Then somewhere between the kickoff call and the first deliverable, hours start disappearing into tasks that weren't in the scope - or were, but not at the volume they actually take. Brief prep. Report assembly. Keyword research before the SEO strategy can begin. Social drafts that follow a template so consistent a junior could do it, except the junior is already maxed out.

Smart Facility Safety Trends at Work

Modern facility safety is moving beyond static checklists. Workplaces now use connected systems, real-time monitoring, predictive maintenance, and environmental sensors to reduce risk before incidents happen. This shift matters because workplace hazards remain common. The U.S. Bureau of Labor Statistics reported that private industry employers recorded 2.6 million nonfatal workplace injuries and illnesses in 2023. Of those, 946,500 involved days away from work.

Surface Tension in AI: Early Adopters Pivoting for Compliance

A good way to measure the success and challenges of new technologies is to spend an evening networking with your peers. Sure, a lot of what you take in is anecdotal, but what you are looking for is consistency in the stories being shared and the industries where the stories are occurring. Recently, I had the opportunity to network with a number of my peers. I had one question that I asked consistently: “How are your AI deployments going?”

How to Protect Your Business From AI Cyberattacks

Defending your network against modern hackers is a lot like playing a game of chess against an opponent who can move all their pieces at once. Traditional cybersecurity relies on anticipating human behavior and recognizing known patterns, but artificial intelligence (AI) changes the rules entirely. Attackers now use machine learning algorithms to automate their strikes, adapt to your defenses in real time, and scale their operations to unprecedented levels.

How to Build an Agentic AI Governance Framework

AI agents are already running inside your organization. They are accessing files, calling APIs, and executing multi-step workflows with no human reviewing each action. Most governance programs were not designed for this. They were built around policies for human users, controls for known data channels, and audits that happen after the fact. None of those structures were designed to govern systems that act at machine speed across every environment where data lives.

What is the OWASP Top 10 Agentic AI

Published by the Open Worldwide Application Security Project (OWASP) in 2025, the OWASP Top 10 for Agentic Applications 2026 identifies security risks that organizations need to consider when implementing agentic artificial intelligence (AI) systems. The guide focuses on how threat actors can exploit agentic systems in new ways and on the associated risk mitigation strategies.

Sophos Email: Enterprise-grade, AI-powered email protection

Sophos Email delivers enterprise-grade protection that keeps malicious messages out of user inboxes, elevates your defense against AI-powered adversaries, trains your employees to stay vigilant, and simplifies day-to-day security operations - all at a competitive price point.

Why You Shouldn't Use LLMs to Generate SQL (Security Risks)

“Just let the LLM write the SQL.” It sounds powerful. A user types a question in plain English, the model generates a query, the system runs it against the database, and the answer comes back. No SQL knowledge required. No BI tools. No waiting for the data team. It works beautifully in demos. And it is a serious engineering mistake in production. Direct SQL generation from LLMs combines two things that should never be combined: untrusted code generation and privileged execution.

GPT-5.5-Cyber is here. What it means for defenders operating at the frontier.

GPT-5.5-Cyber is here. What it means for defenders operating at the frontier. OpenAI’s May 7 release of GPT-5.5 and the limited preview of GPT-5.5-Cyber put frontier AI in verified defenders’ hands. As a member of the Trusted Access for Cyber program, Sophos is using these models to sharpen what we already operate: an agentic SOC that resolves more than half of cases without a human, and an endpoint architecture purpose-built to stop AI-generated zero-days.

Ransomware: AI changes the writer. It doesn't change the math.

Ransomware: AI changes the writer. It doesn't change the math. Why most endpoint protection still treats ransomware as just another piece of malware, and what changes when you watch the data instead of the attacker. In 2013, CryptoLocker introduced the modern ransomware playbook. It also introduced something most of the industry has still not come to terms with: remote encryption.

Endpoint AI Agents: The New Security Blind Spot

Security teams that have invested in AI governance programs over the past two years face a problem that those programs were not designed to solve. The controls built to manage generative AI, network proxies, browser monitoring, and SSO enforcement work when data moves through defined channels. Endpoint AI agents do not move through those channels. They run locally, operate at the OS level, and access data through pathways that exist entirely outside your current visibility.

How to Prompt Chat GPT for Better Results in Professional Communication

Artificial intelligence tools have become an important part of modern business communication, content creation, and productivity workflows. Among these tools, ChatGPT is widely used by marketers, recruiters, founders, students, and business professionals who want to save time while improving the quality of their work. However, many users still struggle to get accurate and useful responses because they do not understand how to prompt chat gpt effectively.

When Defense becomes Dialogue: The Problem with LLM Security

For about thirty years, security has rested on the assumption that the measures guarding your systems do not have opinions. A firewall does not care how politely you ask it to open a port. An SQL filter does not weigh the context of a query before deciding whether to pass it through. An authentication check does not get distracted or talked round. You either present the right credential or you do not, and the answer is the same every time you ask.

The AI Inflection Point That Will Redefine Software Trust

Every few years, something enters the market that doesn’t just change the conversation — it restructures the underlying assumptions of an entire industry. The rapid advancement of AI systems purpose-built for software and security workflows is one of those moments. And I think most of the market is still misreading what it actually means. There will be no shortage of takes. Some will declare that AI has finally “solved” software security.

The Mythos Effect and the End of "Business as Usual" for Security Operations and Risk Management

Something fundamentally shifted in cybersecurity. Claude Mythos, Anthropic’s frontier AI model, signaled the arrival of what the Cloud Security Alliance called an “AI vulnerability storm,” a world where vulnerabilities are discovered and exploited at machine speed. This is a compression event, collapsing timelines, expanding attack surfaces, and forcing a rewrite of how organizations think about security operations, software development, risk, and ultimately, business survival.

How to Monitor MCP Usage: A 10-Step Security Checklist for 2026

What you need to know: MCP can evade traditional DLP, IAM, and SIEM controls because agent traffic looks like authorized API calls, sensitive data is semantically transformed before it leaves the perimeter, and exfiltration happens through tool invocations rather than file transfers.

Cyberhaven Analyst Plugin: AI-Assisted Security Investigation in Claude Code and Codex

Security teams have a data problem. Not a shortage of data, but instead there is a growing data surfacing problem. The signals are there, the incidents are logged, and the classifications exist. But, getting from raw data to a prioritized action plan still requires close to an hour of manual querying, tab-switching, and context reconstruction, every single time. The Cyberhaven Analyst Plugin changes that.

Plenary Session on Data Protection in the Age of AI at CII CIO Awards & Conclave

In this panel discussion titled "Data Protection in the Age of AI" Our Founder & CEO Mr. Anirban Mukherji along with several distinguished speakers, focused on critical aspects of data privacy and cybersecurity. The session explored how artificial intelligence impacts data management and the necessity of robust data privacy and security measures. Experts discuss the importance of responsible AI practices to navigate the evolving digital landscape effectively.

How AI-accelerated threat discovery is reshaping network security

How AI-accelerated threat discovery is reshaping network security As vulnerabilities are discovered faster than ever, organizations must rethink how they reduce exposure and contain risk at the network edge. Claude Mythos Preview has reignited debate about AI-driven cyber attacks, but the real shift isn’t what AI finds, it’s how quickly issues at the network edge can turn into impact. This post explores what’s changed and how network security must adapt to keep up.

Agentic AI Security: Visibility and Control for AI Agents at Work

Security teams have spent years tracking what employees do with data. The harder problem now is tracking what agents do on their behalf. AI agents, whether running in an IDE, installed locally on a laptop, or connected to internal data through a model context protocol (MCP) server, operate with the permissions of the user who deployed them. They read files, query databases, call external APIs, and generate outputs. And in most enterprise environments, security teams have no reliable way to see any of it.

Privacy and Data Residency for AI Agents: What GDPR Requires That Static Controls Can't Show

The residency evidence GDPR and the EU AI Act now expect lives in the runtime trajectory of every AI agent execution, not in the deployment configuration. Your residency compliance dashboard — every workload in eu-west-3, sovereign cloud configured, SCCs signed — cannot produce it. Your AI agent’s last thousand inferences crossed an external border, on average, eight times each. The translation API routed through us-east-1 when the EU endpoint hit capacity.

AI: The hero's journey with Ken Westin

Join us for this week's Defender Fridays as Ken Westin, Senior Solutions Engineer at LimaCharlie, shares his AI journey and what the hero's journey framework reveals about how security professionals can move from hesitation to genuine mastery of AI tools. At Defender Fridays, we delve into the dynamic world of information security, exploring its defensive side with seasoned professionals from across the industry. Our aim is simple yet ambitious: to foster a collaborative space where ideas flow freely, experiences are shared, and knowledge expands.

Why Editing IAM Policies Won't Fix Your AI Agent Identity Problem

Editing IAM policies cannot fix the most common architectural mistake in shipping AI agents on Kubernetes. It happens in thirty seconds: a platform engineer reuses an existing ServiceAccount with an IRSA annotation for Bedrock access because creating a new one takes thirty minutes plus a Terraform pull request. The new agent ships under the existing identity.

AI Agents in the Cloud: A Risk Management Framework for Security Leaders

Your risk committee meets Thursday. The agenda has a new item: AI agent risk posture. You open the register. The fraud detection agent shipped in March is on it. So is the customer service agent. Neither row is useful — “likelihood: medium, impact: high, control: service account scoped via IAM.” Three months ago that was approximately right. Last week the platform team added two MCP connections, the model was upgraded, and the agent now touches data classes the entry never anticipated.

What's happening to DevOps Security?

As 2026 rolls on, our capacity to prompt ourselves silly appears to be limitless. We’ve already seen the financial, legal, and reputational damage to Deloitte as they partly refunded the Australian government for a 237-page audit report containing LLM-generated hallucinations like fabricated academic references, fake footnotes, and a false quote attributed to a judge.

Stop Blaming AI for Bad System Design | Fix MCP Security

Every few weeks, a new story surfaces: an AI agent deletes a production database, an autonomous coding tool racks up a five-figure cloud bill, or a chatbot exfiltrates internal documents through a prompt injection attack. The reaction is predictable. “AI is dangerous.” “LLMs can’t be trusted.” “We need better guardrails on the model.” But if you look at the root cause of these incidents, the model is rarely the problem. The system around it is.

Are banks ready for AI-powered cyber threats?

A recent American Banker article, “Knock on wood: Are banks doing enough to cope with Mythos?” raises a timely and uncomfortable question about advanced AI models like Anthropic’s Claude Mythos. As highlighted in the article, INETCO CEO Bijan Sanii points out a critical truth: The conversation is being fueled by the emergence of AI technology capable of identifying software vulnerabilities at a speed and scale that was previously unimaginable.

Snyk Embeds Anthropic's Claude to Advance AI-Powered Security for Software Development

BOSTON, May 7, 2026 — Snyk, the AI security company, today announced it is leveraging Anthropic's Claude models to advance software security in an era of AI-powered development. Starting today, Snyk has integrated Claude into the Snyk AI Security Platform — powering automated vulnerability discovery, prioritization, and developer-ready fixes across code, dependencies, containers, and AI-generated artifacts. The threat driving that integration is real and accelerating.

Agentic AI in security operations: Friend, risk, or both

Agentic AI is forcing a hard question on every security leader: when your SOC is full of autonomous “doers” instead of just dashboards and scripts, is that your new best friend or a brand‑new risk surface you barely understand? The honest answer is both, and the way you design, govern, and deploy these systems will decide which side wins.

AI Security and Trust: Why SOC Teams Don't Trust AI

See how Torq harnesses AI in your SOC to detect, prioritize, and respond to threats faster. Request a Demo 92% of security leaders say something is actively reducing their trust in AI within the SOC. These aren’t skeptics, they’re people who have already adopted AI and believe in its ability to enhance security operations. We know from the 2026 AI SOC Leadership Report that AI is already widely adopted in the SOC, with 94% of organizations using it in some capacity.

Credential management for AI agents

The proliferation of credentials outside centralized visibility and control is known as “credential sprawl,” and attackers are eager to take advantage of it. Unfortunately, credential management is a broad problem that only grows in complexity as organizations add new tools, employees, and partners.

How to Detect Shadow AI

In 2026, the gap between AI adoption and AI oversight has become a primary boardroom concern. While generative AI has supercharged productivity, it has also introduced Shadow AI: the unmanaged, invisible use of unauthorized AI apps and autonomous agents that operate outside the view of traditional IT security. In this guide, you’ll learn why Shadow AI is exponentially harder to detect than Shadow IT and, more importantly, how to build a modern detection framework. We’ll explore.

AI SOC vs. white box AI: Why black boxes fail in the real world

There’s a growing wave of “AI SOC” startups promising autonomous everything. They’ll triage your alerts, investigate threats, and even run your playbooks. Push a button, let the machine handle the mess, and enjoy the magic. It sounds great until the moment something breaks. Then everyone, not just security, asks the same question: “What exactly did it do?” And that’s when these systems turn into a liability.

Introducing early access for Case Review Agents: AI decisioning for high-stakes identity decisions

Every day, your review team makes hundreds of decisions that determine who gets access to your platform. These decisions carry a lot of weight. Get them right, and you protect your business while delivering a seamless user experience. Get them wrong, and you either block legitimate users or open the door to fraud. As your business scales, these decisions get harder to manage. Case volume climbs, fraud tactics shift, and regulatory expectations evolve.

The Partnerships Taking on AI Security: Daniel Bernard, CrowdStrike Chief Business Officer

The previous episode of the Adversary Universe podcast explored the “vuln-pocalypse” and the implications of advanced AI models accelerating vulnerability discovery and exploitation. Now, we’re diving into how companies are working together to face these evolving security risks. CrowdStrike Chief Business Officer Daniel Bernard spends much of his time talking with partners and customers about how to address their growing concerns: Is their business protected? Do they know which vulnerabilities are in their environment? What do they do about them?

Donuts and Beagles: Fake Claude site spreads backdoor

A malicious imitation of Anthropic’s Claude site leads to DLL sideloading – and a backdoor As we reported on social media recently, Sophos X-Ops has been investigating reports of a fake Claude AI website distributing malware. Like other researchers, we thought this might be a PlugX-like campaign, given that the attack chain shares several characteristics with observed PlugX attacks.

Meet GitGuardian's AI Assistant: Natural Language Queries Across All Your Incidents

See how the GitGuardian Assistant helps teams investigate, understand, and remediate secret incidents directly from the GitGuardian workspace. In this preview, Mathieu and Dwayne walk through how the assistant uses incident context, workspace details, and GitGuardian documentation to answer questions, suggest next steps, and help manage incidents through natural language. It can explain threat patterns, assess scope and impact, recommend remediation steps, assign incidents, update tags, and propose changes to incidents.

The New Vanguard: Strategic Leadership in the Age of Autonomous Threats

The threat landscape of 2026 is no longer defined by the singular hacker or the isolated malware strain. We have entered the era of the "Autonomous Adversary"-a period where AI-driven social engineering, automated vulnerability discovery, and polymorphic code are the standard tools of state-sponsored and criminal actors alike. For the security professional, the traditional defensive perimeter has dissolved. To navigate this complexity, the industry is moving away from purely tactical responses toward a model of "Cyber-Resilience and Strategic Governance.".

The Fastest-Growing AI Categories in the Enterprise Are Also the Riskiest

Security teams often focus governance efforts on the most popular AI tools. But the real risk question isn't which tools employees use most. It's which tools are growing fastest and what data those tools can reach. New data from Cyberhaven Labs shows that the AI categories posting the largest year-over-year growth numbers are the same categories with privileged access to source code, credentials, customer contracts, and internal architecture.

AI Is Moving Fast in Manufacturing

Artificial intelligence is rapidly becoming embedded across manufacturing environments, from engineering and design to supply chain optimisation and operations. What was once experimental is now being applied in day-to-day workflows, often driven by the need for speed, efficiency, and competitive advantage. Recent research shows that 73% of manufacturing organisations report rapid AI adoption, with 90% ranking AI as a top security priority for 2026. The direction of travel is clear.

How to Harden AI Agents in Cloud Environments: The 9 Capabilities Your Stack Must Provide

Most “hardening” advice for AI agents is a checklist of things to configure before the agent runs. CIS Kubernetes Benchmark gates. Pod Security Standards baselines. NetworkPolicy templates. None of it’s wrong — it’s just one of four phases, the one your stack already covers. The other three are Observe, Enforce, and Reconcile. They’re where AI agents actually get breached, and they’re where most stacks have nothing.

AI Agent Security Performance: Framework for Evaluating Latency, Throughput, and Observability Overhead

Every AI workload security PoC reaches the same conversation. Platform engineering pushes back: the AI team won’t accept extra latency on inference. The security engineer hunts for benchmarks and finds a contradiction. Langfuse publishes 15% overhead. AgentOps publishes 12%. The security vendor quotes 1–2.5%. None is lying. They measure different layers.

AI Agent Incident Response in Cloud-Native Environments: A Playbook for Modern SOCs

It’s 2 a.m. and the SOC has a Tier 3 page. A customer-service agent on the production cluster has just wired refund payments to seven addresses outside the approved disbursement list. The runbook is unambiguous: isolate the pod, image the disk, image the memory, root-cause within 48 hours.

Turn Busywork Into Real Work With Egnyte's AI

It’s Friday afternoon, and you need a quick team update. Five minutes, tops, right? You ping Slack. A few people reply, a few don’t. So, you schedule a “quick sync” to get everyone on the same page. Two hours later, you’ve spent your afternoon chasing updates instead of doing actual work. And you’ll do it all over again next week. Now picture this. You’re collecting product demo videos for an agency.

AI Is Replacing Security Dashboards (Headless Cloud Security Explained)

AI is changing cloud security—and dashboards might be next to go. In this video, we introduce headless cloud security: a new model where AI agents, not humans, operate security systems. Instead of dashboards and manual triage, security becomes API-driven, automated, and built for autonomous execution. This shift redefines DevSecOps, cloud security, and AI security workflows—moving humans from operators to orchestrators.

AI GitHub Agents: How One Issue Leaked Private Repos

In May 2025, a developer using Claude with the GitHub MCP server asked their AI assistant to do something entirely routine: review the open issues in a public repository. The repository contained a malicious GitHub issue planted by a researcher demonstrating a security vulnerability. The issue contained hidden instructions. The AI read them, followed them, accessed the developer's private repositories, and posted the contents in a publicly visible pull request. No credentials were stolen.

Meet Rai: AI That Runs More of the Security Work

MSPs are managing more customers, more environments, and more tools than ever before. At the same time, customer expectations keep rising -- faster response times, clearer reporting, and consistent service across every client. All of that pressure lands on already‑lean teams. That’s the reality Rai was built for.

Claude Mythos Is Not the Problem. Your Security Basics Are

There is a lot of panic around Claude Mythos. Some people are saying it will hack every system, that the sky is falling, and that there is no stopping it. That fear is dangerous because it makes teams freeze. Claude Mythos is genuinely powerful. AI systems like this can find security issues in minutes that even experienced penetration testers might take weeks to identify and exploit. That part is real. But here is the important point: AI is still exploiting what is already there.

AI in security feels harder than it is

Anyone who's stood up a SIEM from scratch knows the feeling: weeks of infrastructure work, integration headaches, and a services team alongside for the whole process. That experience shaped how people think about adopting anything new in security ops. The instinct is to treat AI the same way: budget for it, plan for it, bring in specialists. This instinct is costing teams real time. Traditional infrastructure takes great effort to stand up. Infrastructure-as-code happens in seconds.

Designing AI workflows: principles for safety and control

Most teams adopting AI in their workflows understand that LLMs do not behave like traditional software. The same input does not always produce the same output, and even when it does, the model can be wrong, manipulated, or misled. Hallucinations happen even without adversarial input. Air Canada learned this in 2024 when a tribunal ordered the airline to honor a bereavement-fare refund policy its support chatbot had invented out of thin air.

Reviewing Malicious PRs at Scale with AI

As AI coding assistants accelerate software development, the volume of pull requests at Datadog has grown to nearly 10,000 per week, increasing the risk that malicious changes slip through due to review fatigue. To address this, Datadog built BewAIre, an LLM-powered code review system designed to identify malicious source code changes introduced by threat actors. By reducing approval fatigue for developers while increasing friction for attackers, BewAIre guides human reviewers to the areas where judgment matters most, without slowing developer velocity.

The Top 12 Compliance Tools for Unapproved AI Use

Compliance teams have control over approved corporate systems like enterprise software, managed databases, and internal applications. But they don’t have the same over what employees paste into ChatGPT, upload to Claude, or share with Gemini and other unauthorized AI tools. As such, when auditors review AI usage controls, most organizations discover they can’t prove that employees aren’t exposing regulated data through external AI services.

CrowdStrike Launches Falcon OverWatch for Defender

CrowdStrike is excited to announce Falcon OverWatch for Defender, a new offering that extends our elite managed threat hunting to Microsoft Defender environments. The need for proactive threat hunting is increasingly urgent as adversary operations evolve: 82% of intrusions observed in 2025 were malware-free, the CrowdStrike 2026 Global Threat Report revealed, and the fastest eCrime breakout time was a mere 27 seconds. Adversaries using AI increased their attacks 89% year-over-year.

Introducing the New AI-Native KnowBe4 SAT

Cybercriminals are getting smarter and faster. Social engineering attacks are evolving rapidly, and AI is making them more convincing than ever. According to the 2025 Verizon Data Breach Investigations Report, up to 68% of cyberattacks involve some form of social engineering. Meanwhile, 95% of cybersecurity professionals say AI is making phishing attacks harder to detect, and 65% believe attackers will soon rely on AI as their primary tool. This isn’t just theory.

Announcing LimaCharlie Case Management: Built for agentic security workflows

Security operators often struggle with the escalating friction that naturally occurs in their detection and response (D&R) workflow. Detections fire in one tool. Investigations happen in another. Case tracking lives in a third. For MSSPs managing dozens of client environments, fragmentation compounds quickly. Analyst time bleeds into context-switching. SLAs are hard to track. When something goes wrong, reconstructing what happened across multiple platforms is painful.

Why "Block All PII" Is the Wrong Answer: Handling Sensitive Data in MCP Systems

If your first instinct when connecting an LLM to enterprise systems via MCP is to strip out all personally identifiable information, you’re building a system that is useless. The “block all PII” approach sounds responsible. It checks a compliance box. But it fundamentally misunderstands what MCP-based AI systems do and why they need data in the first place. The real engineering challenge is not blocking data.

Why Purpose-Built Architecture Wins in AI Agent Governance

Gartner named Zenity the company to beat in the AI Agent Governance category in its AI Vendor Race: Zenity Is the Company to Beat in AI Agent Governance report as of 17 April 2026. The evaluation covered technical capabilities, customer implementations, business model, and ecosystem strength. That methodology matters because for us, it means the recognition reflects what the platform actually does in production, not just how well a demo lands.

The UK Government's Open Letter on AI Cyber Threats Underscores the Need for Measurable Security

A recent open letter from the UK government on AI-driven cyber threats highlights a clear shift in the threat landscape. Cyberattacks are no longer constrained in the same way by human expertise, as advanced AI models can now help identify vulnerabilities, generate exploit code, and increase the speed and scale of attacks.

Close Defensive Gaps Before AI Attacks Exploit Them

The speed of AI-powered attacks is mind-numbing. CrowdStrike found that average eCrime breakout time fell to 29 minutes, with the fastest recorded breakout at 27 seconds. Armadin showed an LLM-driven NTLM relay attack completing in under three minutes, then roughly 1.5 minutes with BloodHound MCP context.

Security metamorphosis: a Mythos-ready architecture checklist for autonomous AI attacks

The Anthropic Glasswing initiative brings together Amazon Web Services, Apple, Broadcom, Cisco, CrowdStrike, Google, JPMorganChase, the Linux Foundation, Microsoft, NVIDIA, and Palo Alto Networks as launch partners. You can find a lot of posts and reactions on social media as it is definitely a big deal that Anthropic is keeping their Mythos Preview model out of general access.

Beyond Patch SLAs: Continuous Protection in the Frontier AI Era

Frontier AI is changing the economics of cybersecurity. Advanced models can accelerate vulnerability research, exploit-path analysis, attack planning, and disclosure workflows, making vulnerability discovery more continuous, automated, and AI-driven. This raises the bar not only for enterprises that need faster protection, but also for cybersecurity vendors that must adapt secure development, production security, runtime validation, incident response, and AI-assisted workflows to keep pace.

Vanta Third Party Risk Management Demo Part 2: Agentic Assessment

Vanta TPRM transforms vendor assessments into an automated, intelligent workflow, helping your team move faster without sacrificing depth. In this demo, see how Vanta's AI-powered assessment gathers evidence, answers questions, and surfaces key findings—so you can evaluate vendor risk with greater speed, consistency, and confidence.

Is Anthropic's Mythos AI a Real Cyber Threat? What You Need to Know

In the session at CII CIO Awards & Conclave, our Founder & CEO Mr. Anirban Mukherji discussed the evolving cybersecurity landscape shaped by AI and Large Language Models (LLMs) like Anthropic's Mythos. With 28 years of experience in Cybersecurity, he outlined practical defenses including SBOM management, dynamic testing, source code analysis, patch management, AI guardrails, and a "Nation First" approach for sovereignty. Explore trends like on-premises migration, shadow AI risks, and why Mythos enhances bug detection without current threats.

What Physical AI and the digitalization of critical infrastructure mean for OT security

AI-enabled systems are becoming more common in operational technology (OT) environments. What many industry analysts call “Physical AI” refers to AI systems embedded in physical environments — such as industrial cameras, robots and edge systems — that can perceive, interpret and act on real-world conditions. In industrial settings, this includes machine vision systems, predictive maintenance models, robotics optimization and edge analytics operating close to production assets.

The Mythos moment: Why agentic AI changes cybersecurity, but not in the way many think

Anthropic’s announcement of Claude Mythos Preview may end up being remembered as the moment the cybersecurity industry had to stop talking about agentic AI as a future concept and start treating it as a present security variable. The reported results are serious. Anthropic says Mythos Preview identified and exploited zero-day vulnerabilities across major operating systems and browsers during testing.

The Evolution of AI in Financial Services

Opera and artificial intelligence may not seem like natural companions, but they share one important truth: The best performances are revealed over time. Early scenes set the stage, introduce the themes, and create a sense of anticipation. The audience leans in, waiting for the big moments still to come. AI in financial services has followed the same structure.

This Month in Datadog - April 2026

In the latest episode of This Month in Datadog, Jeremy shares how to run autonomous Cloud SIEM investigations, remediate vulnerabilities with auto-generated fixes, and use natural language to explore Datadog. Later, Sumedha Mehta spotlights the Datadog MCP Server, which gives AI agents real-time access to Datadog’s observability data. Then, Chetan Sharma walks through Datadog Experiments, which measures how product changes impact the user journey.

GPT-5.5 vs Claude Opus 4.7: I Made Both Build an App - Here's What Happened

GPT-5.5 vs Claude Opus 4.7 - two flagship AI models dropped one week apart, and both claim to be the best at agentic coding. We put that to the test by giving each model the exact same prompt: build a production-ready, secure note-taking application from scratch. But we didn't stop at reviewing the code. We actually tried to break it by running real security tests against each app to see whether AI-generated code can be trusted with user data. The results were not what we expected.

Detection, endpoint isolation, and ticketing with one AI prompt

Most current demonstrations of AI in security operations are lackluster. You ask a chat interface a question, get a summary, and maybe a suggested next step. The operator still does all the work, at human speed. Meanwhile, adversaries are already deploying AI offensively against their targets. AI in SecOps must ultimately be an operator. Otherwise, the gap between adversary and defender will become too wide to bridge. LimaCharlie Co-founder, Christopher Luft, demonstrates a simple way to get started.

Three AI Blind Spots Your Security Team Can't Afford to Miss

AI governance is not a policy problem. It’s a visibility problem. Most enterprises are approaching it from the outside in: writing acceptable use policies, issuing guidelines, and hoping employees comply. That approach fails because it operates on assumption rather than evidence. You cannot enforce what you cannot see and most organizations have no reliable way to see what AI tools are actually running inside their environment.

8 in 10 companies are betting on AI agents-but fewer than half have a policy to govern them

Accelerating security solutions for small businesses‍ Tagore offers strategic services to small businesses. A partnership that can scale‍ Tagore prioritized finding a managed compliance partner with an established product, dedicated support team, and rapid release rate. Standing out from competitors‍ Tagore's partnership with Vanta enhances its strategic focus and deepens client value, creating differentiation in a competitive market.

7 Best Predictive Maintenance Software for 2026

Here's a number that should stop you cold: unplanned equipment failures cost organizations billions every year, and most teams don't catch the bleeding until it's already serious. I've seen facilities limp through reactive maintenance cycles for years, convinced it was "just how things work." It isn't. Predictive maintenance software has become the clearest answer to that problem, and in 2026, the platforms doing it best are genuinely transforming how asset-heavy operations run.

How to Bridge the Gap Between Your Applicant Tracking and Modern AI Capabilities

Most hiring teams are currently working with software that was built for a different era of technology. These legacy systems are reliable for storing data but they often lack the smart features that modern recruiters need to stay competitive in a fast market. It is a common struggle that leads to frustration.

CVE-2026-42208: Pre-Authentication SQL Injection in LiteLLM Exposes API Credentials

A critical vulnerability in LiteLLM is turning AI infrastructure into an open vault; no login required. Tracked as CVE-2026-42208, this vulnerability allows attackers to extract API keys, cloud credentials, and provider authentication tokens without any credentials or prior access to the system. The root cause is fundamental lapse in input handling. LiteLLM’s API key validation blindly injects the Bearer token from the Authorization header into a SQL query without sanitization.

Cato Joins OpenAI's Trusted Access for Cyber (TAC) to Advance AI-Driven Defense

Over a decade ago, Cato Networks helped shift cybersecurity to a new frontier: a converged, cloud-native platform that combines security and networking. As a long-time security researcher, the Cato platform was a radical change, providing researchers with the rich context and end-to-end visibility we needed to identify threats faster and deliver accurate protections.

AI Sales Avatar Hijacked by Prompt Injection on Livestream #promptinjection #hacked #hacker

Mend.io, formerly known as Whitesource, has over a decade of experience helping global organizations build world-class AppSec programs that reduce risk and accelerate development -– using tools built into the technologies that software and security teams already love. Our automated technology protects organizations from supply chain and malicious package attacks, vulnerabilities in open source and custom code, and open-source license risks.

Beyond the Bug: Why Cybersecurity Still Matters Even If AI Improves Secure Development

Anthropic has officially launched Claude Security, moving its AI‑driven code vulnerability detection, validation, and patching capabilities from a limited research preview into public beta. Improving software security before code ships is a positive step for the industry and can help reduce future risk. However, stronger secure‑by‑design development does not address the scale of exposure organizations face today.

Treat AI Like an Employee #ai #aisecurity

Mend.io, formerly known as Whitesource, has over a decade of experience helping global organizations build world-class AppSec programs that reduce risk and accelerate development -– using tools built into the technologies that software and security teams already love. Our automated technology protects organizations from supply chain and malicious package attacks, vulnerabilities in open source and custom code, and open-source license risks.

Sandboxing AI Agents on AKS: Network Policies, Workload Identity, and Least Privilege

Your AI agent runs on AKS with a managed identity that can read Azure Key Vault, and you assume prompt injection is a theoretical risk—until a malicious prompt drives that agent to steal credentials from the Azure metadata endpoint in under a minute. Most teams discover this gap when their SIEM shows a single request to 169.254.169.254, but they cannot trace it back to which agent tool or prompt triggered it, or how far the stolen token traveled across their Azure environment.

AI Threat Detection for Healthcare: Protecting Patient Data from AI-Mediated Attacks

For six weeks, a mid-size hospital system’s CDS agent issued recommendations biased by a poisoned guideline summary. No detection alert fired. The drift — denial recommendations in cases sharing one specific clinical attribute — traced back to a guideline an outside contributor had quietly reweighted in editorial review. Every existing detection stack reported green. DLP: no PHI left the cluster. EHR audit log: agent reading and writing within scope. Network egress: normal traffic.

AI-SPM for Healthcare: HIPAA-Compliant AI Posture Management

A healthcare CISO opens her AI-SPM dashboard at the start of the quarter. Every clinical AI agent in the cluster reads green: full AI-BOM coverage, every permission scope reconciled, the HIPAA compliance tag clean across the fleet. The ambient scribe, the prior-authorization assistant, the oncology decision support agent — all monitored, all green, all the way through. Six months later, the Office for Civil Rights opens an investigation.

Why Endpoints are Still a Data Security Problem in the Age of AI

After decades of innovation in personal technology, ranging from watches that track personal fitness, mini super-computers that we call phones, and a whole host of other gadgets and self-help technologies, our companies still rely on one technology that started over 45 years ago – the laptop. Fun fact: the first one, called the Osborne 1, weighed 24 pounds! The modern laptop has a better screen, longer battery life, and weighs significantly less, but at its core is still a hard drive.

How Reach Fixes Microsoft Defender for Office 365 Configuration Drift

Microsoft Defender for Office 365 is powerful out of the box. The problem? Configurations drift. IT teams make changes the security team doesn't know about. Anti-phishing policies weaken. Safe Links gaps open up. And AI-powered attackers are finding those openings faster than any team can manually catch them. Reach analyzes your Microsoft Defender for Office 365 controls, activates underutilized capabilities, remediates misconfigurations, and keeps your deployment aligned to your security baseline continuously.

AI Without Guardrails Is Like an Employee Without Training #ai #aisecurity #github

Mend.io, formerly known as Whitesource, has over a decade of experience helping global organizations build world-class AppSec programs that reduce risk and accelerate development -– using tools built into the technologies that software and security teams already love. Our automated technology protects organizations from supply chain and malicious package attacks, vulnerabilities in open source and custom code, and open-source license risks.

How to Map AI Risk to Existing Compliance Frameworks

Mend.io, formerly known as Whitesource, has over a decade of experience helping global organizations build world-class AppSec programs that reduce risk and accelerate development -– using tools built into the technologies that software and security teams already love. Our automated technology protects organizations from supply chain and malicious package attacks, vulnerabilities in open source and custom code, and open-source license risks.

AI finds the vulnerabilities, but exploiting them is a different problem.

AI finds the vulnerabilities, but exploiting them is a different problem. How Sophos Endpoint defends in the AI era, and what the public record on Mythos shows. When Mozilla shipped Firefox 150 with fixes for 271 issues identified by Anthropic’s Mythos model, the headlines focused on the count. The detail that mattered was further down: Mozilla credited only three CVEs to the model. The remaining 268 were classified as defense-in-depth, hardening, or bugs in code paths that could not be exploited.

AI just became the world's most dangerous exploit writer. Here's why Sophos Endpoint is built to stop it.

AI just became the world's most dangerous exploit writer. Here's why Sophos Endpoint is built to stop it. AI-generated zero-days are here. Sophos Endpoint was architected to stop exploits that have never been seen before — blocking the techniques every attack must use, at the moment of execution, with no signature, no cloud lookup, and no configuration required.

Why Smart Companies Invest In IT Support Early

Success in the modern business world depends on how well a team uses its digital tools. Waiting for a system to crash before looking for help creates a lot of unnecessary pressure on the bottom line. Smart leaders understand that setting up the right systems from the start saves time - and money. Building a company on a shaky technical foundation leads to problems as the workload increases.