ai-security
用于评估 AI/ML 系统或 LLM 智能体是否存在提示注入、越狱、模型反演、数据投毒或工具滥用问题。将发现映射到 MITRE ATLAS,并用 ai_threat_scanner.py 评估稳健性。
机器翻译查看英文原文
Use when assessing an AI/ML system or LLM agent for prompt injection, jailbreaks, model inversion, data poisoning or tool abuse. Maps findings to MITRE ATLAS and scores robustness with ai_threat_scanner.py.
适用对象:云服务、运维与安全。自动收录 · 待核查。
原作者说明节选
从固定版本的 SKILL.md 提取,保留原文语言。以下内容属于作者说明,本站尚未验证安装、兼容或运行结果。
查看英文原文
原文涵盖的主题
- AI Security
- Table of Contents
- Overview
- What This Skill Does
- Distinction from Other Security Skills
- Prerequisites
- AI Threat Scanner Tool
- Test File Format
AI and LLM security assessment skill for detecting prompt injection, jailbreak vulnerabilities, model inversion risk, data poisoning exposure, and agent tool abuse. This is NOT general application security (see security-pen-testing) or behavioral anomaly detection in infrastructure (see threat-detection) — this is about security assessment of AI/ML systems and LLM-based agents specifically. -- Overview AI Threat Scanner Tool Prompt Injection Detection Jailbreak Assessment Model Inversion Risk Data Poisoning Risk Agent Tool Abuse MITRE ATLAS Coverage Guardrail Design Patterns Workflows Anti-Patterns Cross-References -- This skill provides the methodology and tooling for AI/ML security assessment — scanning for prompt injection signatures, scoring model inversion and data poisoning risk, mapping findings to MITRE ATLAS techniques, and recommending guardrail controls. It supports LLMs, classifiers, and embedding models. | Skill | Focus | Approach | |-------|-------|----------| | ai-security (this) | AI/ML system security | Specialized — LLM injection, model inversion, ATLAS mapping | | security-pen-testing | Application vulnerabilities | General — OWASP Top 10, API security, dependenc
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- 来源仓库
- alirezarezvani/claude-skills
- 源文件
- engineering-team/skills/ai-security/SKILL.md
- 固定版本
- 8f082544116fc0d014188e521ca40304cdfc86b0
来源与内容状态
本条为自动发现的元数据,尚未完成人工文档核查;适用性与运行结果待核查。
原作者:alirezarezvani/claude-skills · 原作者仓库元数据。文档核查:未核查。最近来源检查:2026-11-09T14:01:46.397Z。
分类由名称、说明与路径规则生成,分类不代表已核实适配。
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MIT。第三方内容及版权归原作者,使用条件以原文为准。
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限制与注意事项
- 元数据收录不代表本站已经安装、适配、实测或进行安全审查。