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name: redpincer version: 1.0.0 description: "AI/LLM red team testing skill. Point at any LLM API endpoint and run automated security assessments. 160+ attack payloads across prompt injection, jailbreak, data extraction, and guardrail bypass. 20 variant transforms. Adaptive attack engine analyzes weaknesses and generates follow-ups. Heuristic response classifier, vulnerability heatmaps, regression testing, and exportable pen-test reports. For authorized security testing only." author: rustyorb keywords: [security, red-team, pentest, prompt-injection, jailbreak, llm-security, guardrail-bypass, data-extraction, vulnerability, ai-safety] metadata: openclaw: emoji: "🦞" requires: bins: ["node", "npm"]

RedPincer — AI/LLM Red Team Suite

Automated security testing for language models. Point at any LLM API endpoint, select attack modules, and run assessments with real-time results and exportable reports.

⚠️ For authorized security testing and research only. Only test systems you own or have explicit permission to audit.

Quick Start

# Clone and install
git clone https://github.com/rustyorb/pincer.git {baseDir}/redpincer
cd {baseDir}/redpincer
npm ci

# Run
npm run dev
# Dashboard at http://localhost:3000

For production:

npm run build
npx next start -H 0.0.0.0 -p 3000

What It Tests

Category	Payloads	Description
💉 Prompt Injection	40	Instruction override, delimiter confusion, indirect injection, payload smuggling
🔓 Jailbreak	40	Persona splitting, gradual escalation, hypothetical framing, roleplay exploitation
🔍 Data Extraction	40	System prompt theft, training data probing, membership inference, embedding extraction
🛡️ Guardrail Bypass	40	Output filter evasion, multi-language bypass, homoglyph tricks, context overflow

Total: 160 base payloads × 20 variant transforms = 3,200 test permutations

Supported Providers

OpenAI  ·  Anthropic  ·  OpenRouter  ·  Any OpenAI-compatible endpoint

Features

Attack Engine

• 160+ payloads across 4 categories
• Model-specific attacks (GPT, Claude, Llama variants)
• 20 variant transforms (unicode, encoding, case rotation, etc.)
• Attack chaining with template variables ({{previous_response}})
• AI-powered payload generation — uses the target LLM to generate novel attacks against itself
• Stop/cancel running attacks instantly

Analysis & Reporting

• Heuristic response classifier with context-aware analysis
• Reduced false positives — detects "explain then refuse" patterns
• Vulnerability heatmap — visual category × severity matrix
• Custom scoring rubrics with weighted grades (A+ to F)
• Verbose 10-section pen-test reports with appendices
• Multi-target comparison — side-by-side security profiles
• Regression testing — save baselines, track fixes over time

Advanced Tools

Tool	What It Does
Compare	Same payloads against 2-4 targets simultaneously
Adaptive	Analyzes weaknesses, generates targeted follow-ups
Heatmap	Visual matrix of vulnerability rates by category/severity
Regression	Save baseline → re-run later → detect fixes or regressions
Scoring	Custom rubrics with weighted category/severity/classification scores
Chains	Multi-step attacks with {{previous_response}} templates
Payload Editor	Create custom payloads with syntax highlighting + AI generation

Usage Workflow

1. Configure Target → Add LLM endpoint + API key + model
2. Select Categories → Pick attack types to test
3. Run Attack      → Stream results in real-time
4. Review Results  → Heuristic classification + severity scores
5. Adaptive        → Auto-generate follow-up attacks on weaknesses
6. Generate Report → Export comprehensive findings as Markdown

Architecture

• All client-side — no server components, your API keys stay local
• NDJSON streaming — real-time results during attack runs
• Heuristic analysis — pattern-matching classifier (no LLM-based grading = no extra cost)
• Zustand + localStorage — state persists across sessions

Companion Tool: RedClaw

For autonomous multi-strategy campaigns (CLI/TUI), see RedClaw — the autonomous red-teaming agent framework.

• RedPincer = web dashboard, manual + automated testing
• RedClaw = autonomous CLI agent, adaptive multi-strategy campaigns
• Together = complete LLM security testing suite

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Built by @rustyorb — Crack open those guardrails. 🦞