Home / sickn33 / agentic-awesome-skills · plugins/agentic-awesome-skills-claude/skills/ai-red-teaming/SKILL.md · GitHub

ai-red-teaming skillB

ai-red-teaming is agent-read markdown (skill) from sickn33/agentic-awesome-skills: Run structured AI red team exercises for jailbreak resistance, data exfiltration.

Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.

What the file says

# AI Red Teaming

Continuously test AI applications like an adversary to discover exploitable failure modes before attackers do.

## When to Use This Skill

Use this skill when:
- Launching a new LLM-powered feature or product
- Evaluating a third-party model before adoption
- Running periodic security assessments of existing AI systems
- Responding to a reported jailbreak or prompt injection incident
- Preparing for compliance audits requiring adversarial testing evidence

## Prerequisites

- Python 3.10+ with `openai`, `anthropic`, or equivalent SDK installed
- Access to the target model endpoint (API key or local deployment)
- A prompt management tool or spreadsheet for tracking attack payloads
- Familiarity with OWASP Top 10 for LLM Applications
- Isolated test environment that mirrors production config

## Program Design

- Define threat scenarios: jailbreaks, policy evasion, prompt injection, model abuse.
- Build reusable attack suites by domain (support bot, coding agent, RAG assistant).
- Include multilingual and obfuscated attack prompts.
- Track results in a risk register with severity and exploitability.

## Test Categories
…

Read the whole file at its exact version.

How to install

Latest version
mdr add sickn33/agentic-awesome-skills/ai-red-teaming@v1.0
Exact content
mdr add sickn33/agentic-awesome-skills/ai-red-teaming@sha256:176b9d7144e6ab29

Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_5tjsji3onws2xdvp.svg)](https://markdownregistry.com/a/art_5tjsji3onws2xdvp)

1 badge views in 30 days

Versions

versioncommittedcommitsizeaudit
v1.0 latest2026-09-20 46a58b4 15,383 BB view

Audit of the latest version

B  16 of 17 checks passed. Deterministic, no model, same answer every run.
  • fail: No prompt-injection phrasing (matched: Ignore all previous instructions)
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (15383 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

sickn33/agentic-awesome-skills · 46,848 stars · license MIT · pushed 2026-09-24 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_5tjsji3onws2xdvp
GET https://markdownregistry.com/api/v1/resolve?ref=sickn33/agentic-awesome-skills/ai-red-teaming
GET https://markdownregistry.com/api/v1/blob/176b9d7144e6ab29bd215eb4680ca3f2809f80dba7d07813a692c6927fec8ca5

Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

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