Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

NIST CSF 2.0 and Agentic AI: Building Profiles for Autonomous Systems

AI agents are likely already running inside your infrastructure. They triage alerts, remediate incidents, provision resources, and make decisions without waiting for a human to approve each step. For teams aligned to NIST’s Cybersecurity Framework (CSF) 2.0, this creates a problem: the framework assumes human actors, human-speed decisions, and human-readable audit trails. Autonomous systems break all three assumptions. The good news is that CSF 2.0 was designed to be adapted.

Torq Leads Every Category in the 2026 KuppingerCole Analysts Leadership Compass: Emerging AI SOC

See how Torq harnesses AI in your SOC to detect, prioritize, and respond to threats faster. Request a Demo The security automation market just got its definitive evaluation and its new name. KuppingerCole Analysts is the global analyst firm that sets the benchmark for cybersecurity technology evaluations.

Attacking the MCP Trust Boundary

Every secure API draws a line between code and data. HTTP separates headers from bodies. SQL has prepared statements. Even email distinguishes the envelope from the message. The Model Context Protocol (MCP), the fast-growing standard for connecting AI agents to external services, inherits that gap from the models it sits on top of.

AI Guardrails - DSPM Enters a New Era of Control and Visibility

You cannot turn a corner without entering the world of AI. I was in a big box home improvement store the other day and there was a manufacturer touting the AI built into their refrigerator! Children’s toys, personal electronics, and even cat litter boxes are now selling AI-assisted products. I am a technology early adopter, and where I’ve seen good uses of AI, we are in the phase of “throw AI into everything” mode, as we do not know what will stick.

Why AI Security Needs More Than One Tool #shorts #ai

Why AI security needs more than one tool Most teams believe a single cybersecurity tool—like WAF, EDR, or API security—is enough to protect their AI systems. But that approach is outdated. AI security is not one layer—it’s a full stack problem. Discovery – Identify Shadow AI and unknown AI usage Build-Time Security – Prevent data poisoning & model risks (MLSecOps) Runtime Security – Stop real-time AI attacks and agent misuse Governance (AISPM) – Ensure visibility, compliance, and policy control.

AI Penetration Testing: Protecting LLMs From Cyber Attacks

88% of organizations now regularly use artificial intelligence (AI) in at least one business function. While adoption of AI technologies has accelerated rapidly, security measures often lag. The rush to roll out AI has, in many cases, overshadowed essential testing and safety protocols. This is particularly a worry when AI and Large Language Models (LLMs) become deeply embedded within organizational workflows and systems in a way that most software isn’t.

Introducing Decipio: A Community Tool to Catch Credential Theft in the Act with Defense First AI

Today, Arctic Wolf is announcing Decipio, a new community‑shared cybersecurity tool designed to help defenders catch attackers while they’re trying to steal credentials inside a network. Credential theft is one of the most common ways cyber attacks begin and one of the hardest to detect early. In many cases, there’s no alert, no obvious warning, and no immediate sign that anything is wrong.

What we learned using AI agents to refactor a monolith

AI agents are increasingly used to refactor large codebases, but many teams lack a clear understanding of where they succeed and where they fail. At 1Password, we applied agentic tooling to a multi-million-line Go monolith, and in this blog we'll share what worked, what broke, and what it means for teams adopting AI in production systems.

AI Workload Security on GKE: Evaluating Google Cloud Native vs Third-Party Solutions

A CISO running AI agents on GKE has watched three Google product launches in eighteen months — Model Armor, expanded Security Command Center coverage for AI workloads, additions to Chronicle’s curated detection content — and is being asked whether the GCP-native stack is now sufficient. The vendor demos and the Google Cloud blog say yes. The 2 AM analyst experience says something different.