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: 84/100
Skill Content
Details
- Author
- seb1n
- Repository
- seb1n/awesome-ai-agent-skills
- Created
- 6 months ago
- Last Updated
- 1 weeks ago
- Language
- Python
- License
- MIT
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
redteam-an-agent
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.
red-team-eval-desk
plan and analyze adversarial AI testing for jailbreaks, prompt injection, data exfiltration, harmful instructions, over-permissioned tools, and policy evasion.
red-teaming-multi-agent-systems
Test a system of multiple cooperating AI agents for attacks that exist only because agents message, spawn, and delegate to each other. Covers agent-to-agent injection (agent-in-the-middle), delegation abuse and recursive loops, orchestrator injection, confused-deputy across a trust boundary, identity spoofing between agents, capability collusion, and denial-of-wallet. Use when reviewing an orchestrator, a crew or swarm, agent-to-agent messaging, or any pipeline where one agent's output becomes another agent's input. Every internal edge where output becomes instruction is an injection channel.