For two years, enterprise AI meant chatbots and copilots. That era is ending. Organizations are now deploying AI agents that don’t just respond to prompts but take action autonomously—managing workflows, executing code, sending emails, all with your credentials and permissions. Traditional security can’t protect against an agent that has authorized access but drifts from your intent. Every action passes the permissions check. The credentials are valid. The behavior, however, may have nothing to do with what you asked the agent to do. Agent Integrity is the framework for addressing this problem, shifting the security question from “can this agent access this resource?” to “should this agent be accessing this resource right now, for this task?”
The Clawdbot Dumpster Fire: 72 Hours That Exposed Everything Wrong With AI Security
This past weekend, security researchers discovered over 1,000 exposed Clawdbot servers, demonstrated credential theft via prompt injection in under five minutes, and documented supply chain attacks reaching seven countries. Here’s what enterprises deploying AI agents need to know.
The “Double Agent” Problem: Why Your AI Agents Can’t Be Trusted by Default
When you deploy an AI agent with access to your enterprise systems, you’re not granting access to static software—you’re granting access to a reasoning system that decides, moment by moment, what actions to take. The agent’s loyalty to your intent isn’t architectural. It’s inferential. And nothing in the architecture guarantees it stays aligned with what you actually asked for.
Semantic Privilege Escalation: The Agent Security Threat Hiding in Plain Sight
Traditional access controls check whether an agent has permission to act. They don’t check whether the action makes sense for the task at hand. Semantic privilege escalation is the emerging AI security threat that exploits this blind spot—and most enterprises aren’t equipped to detect it.
2025: The Year AI Security Became Non-Negotiable
TL;DR: A comprehensive look at the AI security landscape in 2025, from critical LLM vulnerabilities and shadow AI risks to agentic AI threats, new OWASP frameworks, and what enterprise security leaders should prioritize in 2026. — AI security as a discipline…
AI Security News: Jailbreaks, Agent Exploits, and MCP Supply Chain Flaws
Week ending December 8, 2025 This week’s news spans novel jailbreaking techniques, browser agent vulnerabilities, and emerging supply chain risks in the protocols connecting AI systems to the outside world. Perplexity Tackles Browser Agent Security with BrowseSafe AI browser agents can…
ChatGPT Turns 3: What Have We Learned?
OpenAI launched ChatGPT three years ago. Since then, security researchers have discovered vulnerabilities in plugins, memory features, and autonomous agents that challenge traditional security models.
Agentic AI is Already Running the Kill Chain – Inside Anthropic’s Latest Threat Report
Anthropic’s latest threat report documents the first confirmed case of an agentic AI executing the majority of a cyber-espionage kill chain through MCP servers and standard tools, underscoring the need for real-time visibility, control, and enforcement across all AI-driven workflows.
The EU AI Act: What It Means for Companies Developing and Using AI
The European Union’s Artificial Intelligence Act (EU AI Act) is a recent regulatory framework set to reshape how AI is developed and deployed in Europe and beyond. Often compared to the GDPR in its scope and impact, the AI Act introduces…
Inside Your Haunted Infrastructure: The Hidden Cost of Shadow AI
Shadow AI is creating hidden risk across enterprises as unapproved tools, copilots, and agents handle sensitive data beyond security oversight. Learn how invisible AI endpoints and persistent model memory expose organizations and why visibility and governance are now critical.