About flagrix
flagrix is a local scanner for developers and AI agents that checks GitHub repositories and profiles for malware before cloning. Its verdict is pinned to the scanned commit, and it can also check dependencies against a locally matched OSV malicious-package feed.
Key features
- 01Scan repositories before cloning
- 02Score GitHub profiles for scam signals
- 03Pin verdicts to commit SHA
- 04Check dependencies against OSV feed
- 05JSON output and risk exit codes
Use cases
- 01Review a coding assignment repository before cloning
- 02Check a GitHub profile for scam indicators
- 03Gate git clone operations in a Claude Code hook
MCP support
Its stdio MCP server exposes `scan_github_repo` and `scan_github_user` tools for AI agents.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y flagrixGITHUB_TOKENSecretOptional GitHub token — raises API rate limits and enables private-repo scansLocal servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
2Saved tool list · updated 2w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| ref | string | No | Branch, tag, or commit to scan (default: default branch) |
| target | string | Yes | GitHub repository URL or owner/repo slug, e.g. https://github.com/acme/repo |
Details
From the project READMEflagrix
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 |
--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).
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.
Comments
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