
Red Teaming AI Agents: A Testing and Validation Playbook
How to red team AI agents for prompt injection, tool abuse, data leakage, and more. Actionable test scenarios you can run today.
Insights, tutorials, and best practices for secure development

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.

Prompt injection is when a model treats untrusted text as instructions—a flaw with no full patch. Direct vs. indirect attacks, real examples, and defenses that work.

Everything you need to secure AI-generated code, vibe-coded apps, and AI agent systems. Organized by topic with direct links to deep dives, audits, and tooling.
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