Flagrix

Scan GitHub repositories and profiles for malware before you clone — from the terminal, CI, or an AI agent. The same commit-pinned verdict as the Flagrix browser extension, made callable.

npx flagrix scan https://github.com/some-org/coding-assignment

  some-org/coding-assignment @ 3f9c2a1
  HIGH RISK — Do not clone  security score 12/100
  3 files scanned · 10 dependencies · 2 issues

  CRITICAL Data exfiltration patterns detected: Keylogger Pattern
    assignment.js:14
      14  document.addEventListener("keydown", (e) => send(e.key))

Built after real fake-recruiter campaigns ("coding assignment" repos that steal wallets, SSH keys, and browser sessions) started targeting developers.

Commands

flagrix scan <url | owner/repo>   # scan a repository (--ref <branch|sha>)
flagrix scan-user <username>      # score a GitHub profile for scam signals
flagrix mcp                       # MCP server (stdio) for AI agents

Exit codes

--json (automatic when stdout is piped) emits the full result. The verdict is pinned to the scanned commit (commitSha in the JSON): every file is read at that SHA, so a push mid-scan or after the verdict can't silently invalidate it.

AI agents

claude mcp add flagrix -- npx -y flagrix mcp

Tools: scan_github_repo, scan_github_user. A Claude Code hook that gates every git clone on a scan ships in hooks/ — see docs/agent-gating.md.

Tokens & rate limits

Unauthenticated scans use GitHub's 60 req/h budget (a scan issues one request per scanned file, up to ~50). Set GITHUB_TOKEN (or FLAGRIX_GITHUB_TOKEN, or --token) to raise it to 5,000/h and to scan private repositories.

Privacy

Fully local. No telemetry, no accounts, no Flagrix backend — the only network calls go to the GitHub/npm APIs and the public detection-rules repository (signature refresh, cached 6 h, with a bundled offline snapshot).

How it works

Scanning logic lives in @flagrix/scanner-core (MIT), signatures in flagrix-detection-rules (MIT) — the same engine and rules the browser extension uses. Verdicts are risk assessments, not definitive fraud determinations; always verify through official channels.

AI Disclosure

This project leverages Claude AI for boilerplate generation, test-suite expansion, and optimization. All AI-generated code is strictly reviewed, refactored, and verified by human maintainers before merging.

License

MIT — see LICENSE.