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Afrexai Ai Safety Audit

AI Safety Audit

1kalin0 来源安装数☆ 0 仓库 Stars

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

SkillHub CLI

skillhub install 1kalin/afrexai-ai-safety-audit

打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

AI Safety Audit

Comprehensive AI safety and alignment audit framework for businesses deploying AI agents. Built around the UK AI Security Institute Alignment Project standards (2026), EU AI Act requirements, and NIST AI RMF.

What This Skill Does

When activated, the agent performs a structured safety audit of your AI deployment:

  1. AI System Inventory — Catalogs all AI models, agents, and automated decision systems in use
  2. Risk Classification — Maps each system to EU AI Act risk tiers (Unacceptable/High/Limited/Minimal)
  3. Safety Controls Assessment — Evaluates 30 controls across 6 domains
  4. Gap Analysis — Identifies missing safeguards with severity and remediation cost
  5. Compliance Roadmap — Generates a prioritized 90-day action plan

6 Audit Domains (30 Controls)

1. Model Governance (5 controls)
  • Model registry with version tracking
  • Access control and deployment permissions
  • Update and rollback procedures
  • Vendor risk assessment for third-party models
  • Model retirement and data deletion policy
2. Data Protection (5 controls)
  • Data residency and sovereignty mapping
  • PII detection and handling in AI pipelines
  • Training data provenance documentation
  • Data retention aligned with AI lifecycle
  • Cross-border data transfer compliance
3. Output Safety (5 controls)
  • Hallucination detection and mitigation
  • Bias testing across protected characteristics
  • Content filtering for harmful outputs
  • Confidence scoring and uncertainty flagging
  • Human-in-the-loop for high-stakes decisions
4. Security (5 controls)
  • Prompt injection defense
  • Model extraction prevention
  • API rate limiting and abuse detection
  • Adversarial input testing
  • Supply chain security for AI dependencies
5. Monitoring & Observability (5 controls)
  • Real-time output quality tracking
  • Drift detection (data and model)
  • Incident logging and alerting
  • Performance degradation monitoring
  • Cost tracking per AI workflow
6. Organizationa...

来源信息

Source
github
Repository
openclaw/skills
Path
skills/1kalin/afrexai-ai-safety-audit
Version
—
Commit
1fd65fb362db3ef514f5138d845806b906f7edea
分类来源
rules
状态
active
可见性
public

这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。

README

AI Safety Audit

Structured AI safety and alignment audit for businesses deploying AI agents. 30 controls across 6 domains, scored against EU AI Act, UK AI Security Institute, and NIST AI RMF standards.

Run this skill to get a complete safety scorecard, gap analysis, and 90-day remediation roadmap.

Built for: Any company using AI models or agents in production — especially those selling to enterprise, government, or regulated industries.

Full details and industry packs →

来源内容

SKILL.md
# AI Safety Audit

Comprehensive AI safety and alignment audit framework for businesses deploying AI agents. Built around the UK AI Security Institute Alignment Project standards (2026), EU AI Act requirements, and NIST AI RMF.

## What This Skill Does

When activated, the agent performs a structured safety audit of your AI deployment:

1. **AI System Inventory** — Catalogs all AI models, agents, and automated decision systems in use
2. **Risk Classification** — Maps each system to EU AI Act risk tiers (Unacceptable/High/Limited/Minimal)
3. **Safety Controls Assessment** — Evaluates 30 controls across 6 domains
4. **Gap Analysis** — Identifies missing safeguards with severity and remediation cost
5. **Compliance Roadmap** — Generates a prioritized 90-day action plan

## 6 Audit Domains (30 Controls)

### 1. Model Governance (5 controls)
- Model registry with version tracking
- Access control and deployment permissions
- Update and rollback procedures
- Vendor risk assessment for third-party models
- Model retirement and data deletion policy

### 2. Data Protection (5 controls)
- Data residency and sovereignty mapping
- PII detection and handling in AI pipelines
- Training data provenance documentation
- Data retention aligned with AI lifecycle
- Cross-border data transfer compliance

### 3. Output Safety (5 controls)
- Hallucination detection and mitigation
- Bias testing across protected characteristics
- Content filtering for harmful outputs
- Confidence scoring and uncertainty flagging
- Human-in-the-loop for high-stakes decisions

### 4. Security (5 controls)
- Prompt injection defense
- Model extraction prevention
- API rate limiting and abuse detection
- Adversarial input testing
- Supply chain security for AI dependencies

### 5. Monitoring & Observability (5 controls)
- Real-time output quality tracking
- Drift detection (data and model)
- Incident logging and alerting
- Performance degradation monitoring
- Cost tracking per AI workflow

### 6. Organizationa...
README
# AI Safety Audit

Structured AI safety and alignment audit for businesses deploying AI agents. 30 controls across 6 domains, scored against EU AI Act, UK AI Security Institute, and NIST AI RMF standards.

Run this skill to get a complete safety scorecard, gap analysis, and 90-day remediation roadmap.

**Built for:** Any company using AI models or agents in production — especially those selling to enterprise, government, or regulated industries.

**[Full details and industry packs →](https://afrexai-cto.github.io/context-packs/)**

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