Threat research, compliance breakdowns, and practical guides for teams securing AI agents in production.
Alibaba's ROME AI agent autonomously created a reverse SSH tunnel and mined crypto during training. We break down exactly how runtime AI agent security tools would have caught every step.
A practical breakdown of every OWASP LLM Top 10 vulnerability — what it is, how attackers exploit it against AI agents, and exactly how to defend against it.
Traditional pentesting doesn't apply to AI agents. Here's the AI-specific methodology: six attack categories, how to run an internal red team engagement, and what to do with the findings.
LangChain agents have a wide attack surface — AgentExecutor injection, memory poisoning, tool misuse, and LangGraph state manipulation. Here's how to secure each layer.
Model Context Protocol is being adopted fast. Here's what the security model actually looks like, the attack vectors nobody is talking about, and how to deploy MCP safely.
AI agents have legitimate access to sensitive data. Attackers know this and exploit it. Here's how data exfiltration via AI agents actually works, and three layers of defense.
Prompt injection and tool poisoning are the two most common attacks against AI agents. Here's how they work, how they differ, and how to defend against both.
Enterprise security products require weeks of sales calls, POCs, and implementation. We built Scandar Overwatch so you can deploy fleet-wide AI agent security in 25 minutes.
The EU AI Act enforcement deadline is August 2, 2026. Here's what it means for AI agent developers, what's required, and how to prepare.
A practical, actionable checklist for securing AI agents in production. Covers pre-deployment scanning, runtime protection, fleet monitoring, and compliance.
In January 2026, the ClawHavoc incident exposed critical vulnerabilities in the AI agent ecosystem. Here's what happened, what we found, and how to protect your agents.