AI安全扫描器

pip install prism-scanner

# Scan a local skill directory
prism scan ./my-skill/

# Scan a GitHub repo directly
prism scan https://github.com/user/skill-repo

# Check your system for agent residue
prism clean --scan

# Generate a cleanup plan (non-destructive)
prism clean --plan

# Execute cleanup with automatic backups
prism clean --apply

brew tap prismlab/tools
brew install prism-scanner

npx prism-scanner scan https://github.com/user/skill-repo

# .github/workflows/prism-scan.yml
name: Prism Security Scan
on: [push, pull_request]

permissions:
  security-events: write
  contents: read

jobs:
  scan:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: aidongise-cell/prism-scanner@main
        with:
          path: '.'
          fail-on: 'high'

pip install "prism-scanner[mcp]"

{
  "mcpServers": {
    "prism-scanner": {
      "command": "prism-mcp"
    }
  }
}

claude mcp add prism-scanner prism-mcp

# Build the image
docker build -t prism-scanner .

# Scan a local directory
docker run -v $(pwd)/my-skill:/workspace/target:ro prism-scanner scan /workspace/target

# Scan a remote repo
docker run prism-scanner scan https://github.com/user/skill-repo

# Generate HTML report
docker run -v $(pwd):/workspace/output prism-scanner scan https://github.com/user/repo --format html -o /workspace/output/report.html

docker run ghcr.io/prismlab/prism-scanner scan <target>

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
  Prism Scanner v0.1.0
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

  Target: evil_skill
  Platform: clawhub
  Duration: 42ms

[1/3] Behavior Analysis
  ✗ CRITICAL  S8    Data exfiltration: secrets sent to external endpoint  evil_skill.py:10
  ✗ CRITICAL  S10   Download and execute: fetches remote payload          evil_skill.py:24
  ✗ HIGH      S1    Shell execution with untrusted input                  evil_skill.py:14
  ✗ HIGH      S13   Persistence: writes LaunchAgent plist                 evil_skill.py:36
  ⚠ MEDIUM    S6    Dynamic code execution (eval/exec)                    evil_skill.py:21

[2/3] Metadata Analysis
  ✗ CRITICAL  P1    Hardcoded credential: AWS Access Key                  evil_skill.py:47
  ⚠ MEDIUM    P2    Base64-encoded executable content                     evil_skill.py:50
  ⚠ MEDIUM    P6    Prompt injection pattern in string literal            evil_skill.py:53

[3/3] Residue Scan
  (skipped — use `prism clean --scan` for system-level checks)

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
  Grade: F (Critical)

  Key Risks:
    ▸ CRITICAL: Data exfiltration to external endpoint (S8)
    ▸ CRITICAL: Download and execute remote payload (S10)
    ▸ CRITICAL: Hardcoded AWS credential (P1)
    ▸ HIGH: Shell execution with user input (S1)
    ▸ HIGH: Persistence mechanism installed (S13)

  Behavior Profile:
    exfiltrates_data, executes_shell, downloads_and_executes, installs_persistence

  Recommendation: DO NOT INSTALL — Critical security risks detected.

  Findings: 3 critical, 2 high, 3 medium
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

# Rich terminal output (default) — color-coded severity, grade highlighting
prism scan ./skill/

# Machine-readable JSON
prism scan ./skill/ --format json

# Standalone HTML report — dark-themed, self-contained, shareable
prism scan ./skill/ --format html -o report.html

# SARIF for GitHub Code Scanning
prism scan ./skill/ --format sarif -o results.sarif

prism scan https://github.com/user/skill-repo --format html -o report.html

name: Security Scan
on: [push, pull_request]

jobs:
  prism-scan:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          python-version: "3.12"

      - name: Install Prism Scanner
        run: pip install prism-scanner

      - name: Run security scan
        run: prism scan . --format sarif -o results.sarif --fail-on high

      - name: Upload SARIF results
        if: always()
        uses: github/codeql-action/upload-sarif@v3
        with:
          sarif_file: results.sarif

rules/
├── malicious_signatures.yaml   # Known malicious code signatures and hashes
├── permissions.yaml            # Permission baseline definitions
└── suspicious_domains.yaml     # C2 domains, dynamic DNS, disposable TLDs

src/prism/
├── cli.py                  # CLI entry point and output formatting
├── scanner.py              # Orchestrator — runs engines, collects findings
├── models.py               # Finding, ScanResult, Severity, Layer data models
├── scoring.py              # Letter-grade risk assessment (A-F)
├── report.py               # HTML report generator
├── fetcher.py              # Git clone / URL fetching with security guards
├── cleaner.py              # System cleanup: plan, apply, rollback
├── suppression.py          # .prismignore parsing
├── rules_loader.py         # YAML rule loading
└── engines/
    ├── ast_engine.py       # AST-based analysis (S1-S14)
    ├── pattern_engine.py   # Regex pattern matching (P1-P9)
    ├── manifest_engine.py  # Metadata & manifest analysis (M1-M6)
    ├── residue_engine.py   # System residue scanner (R1-R10)
    └── taint.py            # Intra-file taint tracking

[![Prism Grade A](https://img.shields.io/badge/Prism-Grade%20A-brightgreen?style=flat-square&logo=data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAyNCAyNCIgZmlsbD0id2hpdGUiPjxwYXRoIGQ9Ik0xMiAxTDMgNXY2YzAgNS41NSAzLjg0IDEwLjc0IDkgMTIgNS4xNi0xLjI2IDktNi40NSA5LTEyVjVsLTktNHoiLz48L3N2Zz4=)](https://github.com/aidongise-cell/prism-scanner)