Add fajarsajid/agent-redteam

agents/fajarsajid__agent-redteam/README.md

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+# agent-redteam
+
+An agentic LLM red-team harness that uses **Claude** to systematically probe AI agent system prompts for security vulnerabilities — including prompt injection, identity spoofing, credential exfiltration, privilege escalation, goal hijacking, and safety-boundary bypass.
+
+Built as a research artifact by Fajar Sajid (Purdue University), it found a **49.5% mean violation rate** across 384 trials against a real e-commerce agent prompt.
+
+---
+
+## Run
+
+```bash
+npx @open-gitagent/gitagent run -r https://github.com/fajarsajid/agent-redteam
+```
+
+---
+
+## What It Can Do
+
+- **Adversarial Probe Generation** — Crafts realistic, target-tailored probes across 8 MITRE-mapped attack categories using Claude as the red-team analyst
+- **Vulnerability Analysis** — Evaluates whether a target system prompt is susceptible to each probe, with CVSS-like severity scores (0–10) and attack paths
+- **Incident Reporting** — Produces structured JSON findings for SIEM/tooling integration and human-readable Markdown reports
+- **CI Pipeline Integration** — Exits `1` on critical/high findings; zero extra dependencies beyond `requests`
+- **Multi-turn Assessment** — Evaluates context drift across interaction sequences (single-turn benchmarks underestimate real-world vulnerability ~1.7× at 7 turns)
+
+---
+
+## Attack Categories
+
+| Category | MITRE | Violation Rate (empirical) |
+|---|---|---|
+| Prompt Injection (Indirect) | T1059 | 70.8% |
+| Identity Spoofing | T1078 | 62.5% |
+| Prompt Injection (Direct) | T1059 | 54.2% |
+| Goal Hijacking | T1565 | 50.0% |
+| Privilege Escalation | T1548 | 45.8% |
+| Data Exfiltration | T1041 | 41.7% |
+| Credential Exfiltration | T1552 | 37.5% |
+| Safety Boundary Bypass | T1562 | 33.3% |
+
+---
+
+## Usage
+
+```bash
+git clone https://github.com/fajarsajid/agent-redteam
+cd agent-redteam
+pip install requests
+export ANTHROPIC_API_KEY=sk-ant-...
+
+# Quick scan
+python redteam.py --prompt examples/orderbot_prompt.txt
+
+# Full run with report output
+python redteam.py --prompt system_prompt.txt \
+    --probes 3 --output report.md --json findings.json
+
+# CI mode (exit 1 on critical/high findings)
+python redteam.py --prompt system_prompt.txt --quiet
+```
+
+---
+
+## Structure
+
+```
+agent-redteam/
+├── agent.yaml              ← GAP manifest
+├── SOUL.md                 ← Agent persona & security philosophy
+├── redteam.py              ← CLI evaluation tool
+├── probe_engine.py         ← Claude-powered adversarial probe generation
+├── categories.py           ← Attack taxonomy (8 categories, MITRE-mapped)
+├── reporter.py             ← Terminal summary + Markdown incident report
+├── test_redteam.py         ← 17/17 unit + mocked API tests
+└── examples/
+    └── orderbot_prompt.txt ← Target agent used in experiments
+```
+
+---
+
+## Built with
+
+[gitagent](https://github.com/open-gitagent/gitagent) — a git-native, framework-agnostic open standard for AI agents.

agents/fajarsajid__agent-redteam/metadata.json

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+{
+  "name": "agent-redteam",
+  "author": "fajarsajid",
+  "description": "Agentic LLM red-team harness: uses Claude to probe AI agent system prompts for identity abuse, credential exfiltration, and safety-boundary vulnerabilities.",
+  "repository": "https://github.com/computer-agent/agent-redteam",
+  "version": "1.0.0",
+  "category": "security",
+  "tags": ["red-teaming", "security", "llm-security", "prompt-injection", "adversarial", "claude", "ai-safety", "vulnerability-assessment"],
+  "license": "MIT",
+  "model": "claude-sonnet-4-20250514",
+  "adapters": ["system-prompt"],
+  "icon": false
+}