AI Security
Skill Verified ActiveUse when assessing AI/ML systems for prompt injection, jailbreak vulnerabilities, model inversion risk, data poisoning exposure, or agent tool abuse. Covers MITRE ATLAS technique mapping, injection signature detection, and adversarial robustness scoring.
To provide AI/ML system developers and security professionals with a specialized tool for assessing and mitigating risks in AI models and agents.
Features
- Detects prompt injection signatures
- Assesses jailbreak vulnerability
- Scores model inversion and data poisoning risk
- Maps findings to MITRE ATLAS techniques
- Analyzes agent tool abuse vectors
Use Cases
- Scanning LLMs for prompt injection before deployment
- Assessing classifiers for adversarial robustness
- Evaluating data poisoning risk in fine-tuned models
- Auditing AI agents for tool abuse vulnerabilities
Non-Goals
- General application security testing (OWASP Top 10)
- Infrastructure threat detection
- Performing live model inversion attacks
- Real-time behavioral anomaly detection in inference APIs
Workflow
- Run `ai_threat_scanner.py` with target type and access level
- Provide test prompts via `--test-file` or use built-in seeds
- Review scan results for identified threats and risk scores
- Map findings to MITRE ATLAS techniques
- Implement recommended guardrails based on findings
Practices
- Security assessment
- Threat modeling
- Adversarial robustness
- Guardrail design
Prerequisites
- Python 3.x interpreter
- Optional: JSON file with custom prompts
Installation
First, add the marketplace
/plugin marketplace add alirezarezvani/claude-skills/plugin install engineering-team@claude-code-skillsQuality Score
VerifiedTrust Signals
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