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
| code | meaning |
|---|---|
| 0 | low risk |
| 1 | scan failed |
| 2 | medium risk — review before proceeding |
| 3 | high risk — do not clone |
| 4 | scan incomplete — too little was read to call the repository safe |
--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.
Incomplete scans (exit 4)
A repository scan is one tree request plus up to ~200 file reads, and GitHub allows 60 requests an hour without a token. When the budget runs out part way through, the rest of the repository is never looked at — so a "low risk, no findings" result over 30 of 180 files is the absence of looking, not a clean bill of health.
The result says so (scanSummary.complete: false, with
scanSummary.incompleteReason of "rate-limit" or "fetch-errors"), the
human output withholds the verdict and the score, and the exit code is 4
instead of 0. In CI the exit code is the decision and nobody reads stdout, so
a gate on flagrix scan stops here as it does on any non-zero code. Findings
are the other way round: evidence found is evidence however little else was
read, so a medium or high verdict keeps its own code and the coverage note
reads "there may be more".
Set a token to make this rare: GITHUB_TOKEN raises the budget to 5,000/h.
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 ~200). Set GITHUB_TOKEN (or FLAGRIX_GITHUB_TOKEN, or
--token) to raise it to 5,000/h and to scan private repositories. A scan that
runs out of budget reports partial coverage and exits 4 — see
Incomplete scans.
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).
Dependencies are also checked against the OSV malicious-package feed
(osv-malicious.json from the same repository: every npm/PyPI package the
OpenSSF malicious-packages project has confirmed malicious). The feed is
downloaded and matched locally, so dependency names never leave your machine.
It is cached 6 h and revalidated with its ETag. Set FLAGRIX_OSV_FEED=0 to
skip it (the curated list in the signatures still applies).
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.