agent-opfor
Validates AI agent robustness against adversarial inputs before production deployment, reducing risk of exploitation, prompt injection, or unexpected failure…
Open-source adversary emulation for AI agents and MCP servers.
- Test Claude's security by simulating adversarial attacks on your AI agent systems.
- Identify vulnerabilities in MCP server implementations before production deployment.
- Generate adversarial prompts to verify your agent's robustness against malicious inputs.
Validates AI agent robustness against adversarial inputs before production deployment, reducing risk of exploitation, prompt injection, or unexpected failures in critical workflows.
Development teams building Claude-based agents or MCP servers needing security validation and resilience testing.
https://github.com/KeyValueSoftwareSystems/agent-opfor
By KeyValueSoftwareSystems
How to Get It
claude plugins install KeyValueSoftwareSystems/agent-opfor
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me test Claude's security by simulating adversarial attacks on my AI agent systems
Trust Signals Auto-scanned
Community Pulse New
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 565 GitHub stars; 18 contributors; last commit 2d ago; license no license.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 565 GitHub stars; 18 contributors; last commit 2d ago; license no license.