Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Report: Social Engineering Remains a Central Part of AI-assisted Attacks

Threat actors continue to rely on social engineering as AI is incorporated into their attacks, according to ESET’s Threat Report for the first half of 2026. ESET’s Director of Threat Prevention Labs, Jiří Kropáč, stated, “Rather than relying on entirely new methods and tools, attackers are quickly adapting established techniques to new platforms, technologies, and user behaviors.

The Permission Boundary Myth: Why Authorized Doesn't Mean Appropriate for Coding Agents

Coding agent security has a framing problem. Most security conversations around these tools center on the wrong question. 'Did the agent have permission to do that?' is a reasonable place to start, but in the context of autonomous AI systems, it's not where the risk actually lives. In Zenity Labs' research into the coding agent threat model, the pattern that keeps surfacing isn't that agents are doing things they aren't allowed to do.

AI Man-in-the-Middle: The Trust Problem Hiding in Plain Sight

I remember the days when merely saying “AI” was enough to earn glares for bringing up such a taboo subject, almost equivalent to saying “Voldemort.” Now, AI is at the center of many people’s daily lives and certainly at the center of business operations. I find myself using AI for everyday tasks. Unfortunately for security teams, the bad guys are using it too.

What Is Dark AI? How Scammers Are Using Artificial Intelligence Against You

AI isn't just being used for good. Dark AI — artificial intelligence weaponized for malicious purposes — is behind a new wave of scams, phishing attacks, deepfakes, and cybercrimes that are harder than ever to detect. Scammers are now using AI to clone voices, fake video calls, impersonate people you trust, and generate convincing phishing messages at massive scale — all powered by dark GPTs built without safety restrictions.

The background agent that outgrew me

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Agentic AI vs. Generative AI: What Enterprises Need to Know

Agentic AI and generative AI both build on large language models, but they behave in fundamentally different ways once deployed. Generative AI produces content in response to a specific prompt and then stops. Agentic AI receives a goal, then autonomously plans, decides, and executes multi-step workflows to accomplish that goal, often across systems and tools the enterprise runs. That difference is the difference between an AI that helps a human do work faster and an AI that does the work itself. ‍

The Agentic Attacker: One Objective, One Prompt, Forty Minutes, Domain Admin - Game Over

In a controlled enterprise lab, we tested how far an agentic attack stack could go by harnessing a frontier model with an agent platform, MCP-enabled tooling, operational context, and enough autonomy to execute a complete attack path.

AI Traffic Security: The Hidden Risk of Unstructured Data Leakage #aisecurity

Understanding the nuances of AI Traffic Security is critical because traditional firewalls and API gateways are fundamentally ill-equipped to inspect unstructured natural language. In the past, enterprise data remained safely within the corporate perimeter. Today, employees are pasting highly sensitive information directly into external models, creating a massive vulnerability where the risk lies in the meaning and content, rather than syntax or connections.

AIDR: How CrowdStrike Is Defining the Next Era of Cybersecurity

Every foundational shift in computing has created a new security category. The internet created network security, the rise of workstations created the need for endpoint detection and response (EDR), and cloud computing created the need for cloud security. Each technology transition has moved faster than the one before it. None has moved faster than AI.

AI is moving fast. Exploits are right behind.

Chris Luft and Matt Bromiley cover four stories in this week's Intel Chat that all point to the same trend: attackers are keeping pace with how fast AI tools are being built and deployed. They break down a chatbot pipeline vulnerability in Google Dialogflow CX, a phishing technique that hides malicious content until it renders in the browser, four newly exploited vulnerabilities added to CISA's KEV catalog, and an attack that exploits AI coding assistants' tendency to hallucinate fake repository names.