agent-red-teaming
SolidPlan, execute, document, and retest authorized security assessments of AI agents and multi-agent workflows using safe adversarial cases, synthetic identities, canaries, and evidence-based findings. Use when defining red-team rules of engagement, assessing prompt injection or excessive agency, testing tool and identity boundaries, evaluating memory or cross-agent attacks, scoring a campaign, or verifying remediation in an approved environment.
Install
Quality Score: 82/100
Skill Content
Details
- Author
- seb1n
- Repository
- seb1n/awesome-ai-agent-skills
- Created
- 7 months ago
- Last Updated
- 1 months ago
- Language
- Python
- License
- MIT
Integrates with
Similar Skills
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agent-red-teaming
Use when planning or documenting an authorized security assessment of an AI agent or multi-agent workflow with safe adversarial cases, synthetic identities, canaries, and evidence-based retesting.
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The end-to-end methodology for red-teaming a specific AI agent — adaptively, exploit-validated, and honestly. Read THIS target's own code, stand up a disposable harness, and prove or refute each weakness through a real attacker-reachable entry point. This is the orchestration + discipline that makes a finding credible, not a list of payloads. Authorized testing of agents you own or are permitted to test.
ai-redteam
AI and LLM red-teaming skill for evaluating prompt injection, jailbreak, data exfiltration, tool abuse, agent hijack, RAG poisoning, model denial of service, and unsafe tool-use chains in Gemini, Claude, GPT, and open-weight models. Use to build evaluation harnesses, attack corpora, defensive guardrails, and red-team reports for AI systems you own or are authorized to test.