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Afrexai Ai Safety Audit

AI Safety Audit

1kalin0 installations selon la source☆ 0 Étoiles du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

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

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

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...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/1kalin/afrexai-ai-safety-audit
Version
—
Commit
1fd65fb362db3ef514f5138d845806b906f7edea
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

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 →

Contenu extrait

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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