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Test AI systems for safety and vulnerabilities.

AI Red Teaming Specialist

AI safety evaluation, adversarial testing

1 loadsintermediatev6.1

Best for

  • Adversarial testing of LLM chatbots to find prompt injection vulnerabilities
  • Building automated red team evaluation pipelines for AI safety assessment
  • Designing jailbreak prevention systems for customer-facing AI applications
  • Creating comprehensive safety benchmarks for LLM deployment readiness

What you'll get

  • Comprehensive attack taxonomy mapping OWASP LLM Top 10 vulnerabilities to specific test cases with automated probing scripts
  • Multi-layered defense architecture recommendations with prompt filtering, output monitoring, and behavioral anomaly detection
  • Structured safety evaluation report with quantified risk scores, evidence of successful attacks, and remediation priority matrix
Expects

Details about the AI system architecture, intended use cases, current safety measures, and specific threat scenarios to evaluate.

Returns

Structured vulnerability assessment reports with attack taxonomies, test results, remediation recommendations, and continuous monitoring frameworks.

What's inside

You are an AI Red Teaming Specialist. You conduct adversarial testing and safety evaluation of AI systems, identifying vulnerabilities in LLMs and AI-powered applications before they reach production. - **Map every finding to the OWASP LLM Top 10 (2025 revision).** Assign each vulnerability to a cat...

Covers

What You Do DifferentlyMethodologyWatch For
Not designed for ↓
  • ×Traditional cybersecurity penetration testing of networks or web applications
  • ×General software QA testing or functional testing of non-AI systems
  • ×Legal compliance reviews or regulatory assessment documentation
  • ×Training or fine-tuning AI models themselves

SupaScore

87.13
Research Quality (15%)
9.25
Prompt Engineering (25%)
8.75
Practical Utility (15%)
8.25
Completeness (10%)
9.25
User Satisfaction (20%)
8.5
Decision Usefulness (15%)
8.5

Evidence Policy

Standard: no explicit evidence policy.

ai-safetyred-teamingadversarial-testingjailbreak-preventionprompt-injectionbias-detection

Research Foundation: 6 sources (3 industry frameworks, 2 paper, 1 official docs)

This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.

Version History

v6.17/3/2026

content refresh 2026-07: freshness review findings fixed (stale claims, invented precision, missing 2026 practice)

v6.06/12/2026

v6.0 wave-1 repair: re-distilled from masterfile/v2 (truncation incident 2026-06, delta-first rules)

v5.03/25/2026

v5.5 final distill

v2.02/19/2026

Pipeline v4: rebuilt with 3 helper skills

v1.0.02/15/2026

Initial version

Prerequisites

Use these skills first for best results.

Works well with

Need more depth?

Specialist skills that go deeper in areas this skill touches.

Common Workflows

AI Safety Deployment Pipeline

Complete AI safety assessment workflow from governance setup through red teaming, guardrails implementation, and ongoing monitoring framework deployment

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