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Implementation Plan: Adversarial Red Team Code Auditor

1) Goal and Scope

Build a multi-agent security auditing system where a red-team attacker and blue-team defender iterate on vulnerabilities, and an arbiter validates fixes with tool-driven checks. Output is a professional security report with evidence, patches, and verification results.

Scope (MVP for hackathon):

  • Target Python codebases first (FastAPI/Flask-style apps and simple libraries).
  • Support a curated set of high-signal vulnerabilities: injection, authz/authn checks, insecure deserialization, path traversal, SSRF, unsafe subprocess, secret leakage, weak crypto usage.
  • Provide CLI-driven workflow: scan -> fix -> verify -> report.

2) Architecture Overview

  • CLI (Typer + Rich) orchestrates the pipeline.
  • Agents (OpenAI Agents SDK) implement roles with strict JSON contracts.
  • Shared state is a JSON run bundle stored on disk for reproducibility.
  • Verification uses local tools (ruff, bandit, pytest) to ground the arbiter.

Directory layout (initial):

  • src/audit/ core package
    • agents/ role definitions + system prompts
    • flows/ orchestrators (scan/fix/verify/report)
    • tools/ local tooling wrappers (ruff/bandit/pytest, patch apply)
    • contracts/ JSON schemas + data models
  • examples/vuln_app/ intentionally vulnerable demo
  • tests/ unit + integration tests
  • docs/ supporting docs

3) Agents and Responsibilities

Red Team (Attacker)

  • Finds vulnerabilities with evidence: file path, line range, code snippet, CWE tag, severity, exploit rationale.
  • Outputs a structured finding list + proposed test/verification steps.

Blue Team (Defender)

  • Proposes minimal patches with rationale.
  • Outputs unified diff + updated finding status.

Arbiter (Security Auditor)

  • Verifies fixes using tools and the red team’s test plan.
  • Accepts/rejects with explicit reasons and remaining risk.

Reporter

  • Generates REPORT.md with summary, findings, patches, and verification logs.

4) Workflow and Control Loop

  1. Scan: Red Team analyzes repo and emits findings.
  2. Fix: Blue Team proposes minimal patches for accepted findings.
  3. Reattack (optional): Red Team re-scans post-fix code to see what still breaks.
  4. Verify: Arbiter runs local checks, evaluates reattack output, and accepts/rejects.
  5. Loop: If rejected, send back to Defender with arbiter feedback (max 2 iterations).
  6. Report: Reporter generates final report and scorecard.

Key rule: the arbiter’s decision must be tool-grounded (tests/scanners), not just model opinion.

5) Data Contracts (JSON)

Core object: Finding

{
  "id": "F-001",
  "cwe": "CWE-89",
  "severity": "high",
  "file": "src/app/db.py",
  "line": 42,
  "evidence": "...code snippet...",
  "impact": "SQL injection via user input",
  "fix_plan": "parameterized query",
  "status": "open|fixed|rejected"
}

Run bundle (runs/<run_id>.json) includes:

  • findings[]
  • patches[] (unified diffs)
  • verification[] (tool outputs + pass/fail)
  • decision_log[] (arbiter decisions)

6) Tooling and Verification

  • ruff: lint + quick static checks
  • bandit: security-specific static analysis
  • pytest: regression checks on example app

Arbiter must report:

  • Which tools ran, exit codes, and failing rules
  • Which findings were verified as fixed

7) CLI Commands (Target)

# scan
python -m audit scan <path>

# fix (writes patch file)
python -m audit fix <path> --autofix

# verify
python -m audit verify <path>

# full pipeline
python -m audit run <path>

8) Example App (Demo)

examples/vuln_app/ will include:

  • A minimal API with seeded vulnerabilities
  • Basic tests that fail pre-fix and pass post-fix
  • A known “answer key” of expected findings

9) Evaluation and Metrics

  • Baseline: single-agent audit pass (no loop).
  • Scorecard:
    • confirmed findings
    • false positives
    • fixes applied
    • verification pass rate
    • time to fix
    • baseline delta and overlap

We will show a simple comparison table in the report.

10) Risks and Mitigations

  • Hallucinated findings: require evidence snippet + file/line + tool corroboration when possible.
  • Over-patching: blue team must minimize diffs; arbiter rejects invasive changes.
  • Time: keep scope to Python + curated vulnerabilities; add languages later only if time remains.

11) Milestones (Hackathon)

  1. Scaffold repo + CLI skeleton
  2. Implement scan/fix/verify flows
  3. Build demo app + tests
  4. Add report generator + metrics
  5. Record 2-min demo