Insights, tutorials, and best practices for secure development
Anthropic's Model Context Protocol makes AI agents more capable, but its security model delegates critical protections to implementors. Here's what's missing and why it matters.
When your AI agent gets compromised, every minute counts. A ready-to-use incident response playbook for prompt injection, data leaks, and runaway agents.
How to red team AI agents for prompt injection, tool abuse, data leakage, and more. Actionable test scenarios you can run today.
Reference architecture for securing AI agents with layered controls: auth, secrets handling, sandboxing, I/O filtering, rate limiting, and audit logging.
AI agents hallucinate commands, misparse tool outputs, and loop destructively. Learn to design for model unreliability before it costs you.
AI agents bridge language and action, creating attack surfaces at every trust boundary. Learn to threat model LLM-driven systems before attackers do.
ChatGPT exposed user conversations through cache bugs. Learn how to architect AI agent systems with bulletproof tenant isolation.
Malicious plugins, backdoored models, and compromised dependencies threaten AI agent security. Learn to vet and isolate third-party components.
AI agents accidentally expose API keys, credentials, and PII through outputs, logs, and memory. Learn zero-trust architecture for secrets in AI systems.
AI agents with excessive tool permissions create catastrophic risks. Learn how to scope agent access using least privilege and prevent destructive actions.
Prompt injection enables attackers to hijack AI agents through malicious instructions. Learn how these attacks work and proven defenses to protect your systems.
We analyzed Open Claw, an AI agent controlling 12+ messaging platforms. Here's every vulnerability class we found and how to fix them.
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