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AI Security

技能 已验证 活跃

Use 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.

目的

To provide AI/ML system developers and security professionals with a specialized tool for assessing and mitigating risks in AI models and agents.

功能

  • 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

使用场景

  • 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

非目标

  • General application security testing (OWASP Top 10)
  • Infrastructure threat detection
  • Performing live model inversion attacks
  • Real-time behavioral anomaly detection in inference APIs

工作流

  1. Run `ai_threat_scanner.py` with target type and access level
  2. Provide test prompts via `--test-file` or use built-in seeds
  3. Review scan results for identified threats and risk scores
  4. Map findings to MITRE ATLAS techniques
  5. Implement recommended guardrails based on findings

实践

  • Security assessment
  • Threat modeling
  • Adversarial robustness
  • Guardrail design

先决条件

  • Python 3.x interpreter
  • Optional: JSON file with custom prompts

安装

请先添加 Marketplace

/plugin marketplace add alirezarezvani/claude-skills
/plugin install engineering-team@claude-code-skills

质量评分

已验证
97 /100
1 day ago 分析

信任信号

最近提交1 day ago
星标14.6k
许可证MIT
状态
查看源代码

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