fingerprint-ci-gate
Gate a build on browser fingerprint regressions with liarjs - save a baseline scan as JSON, diff later runs against it, and fail the job when the consistency score falls below a floor. Use when asked to add a fingerprint or headless-detection check to GitHub Actions, GitLab CI or another pipeline, to catch a regression in a Chromium build or scraping harness before it ships, or to track how a fingerprint score changes across commits.
- Installs
- 103.7K
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- #300
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/liarjsdev/liarjs-skills --skill fingerprint-ci-gate- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads fingerprint-ci-gate automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
Security audits
Independent scans of the skill's instructions and bundled files.
SKILL.md
The instructions your agent reads when the skill is triggered.
Fail the build, not the ban rate
A fingerprint regression is invisible until something starts rejecting the traffic weeks later.
liarjs turns it into a diff in a pull request: scan, save the JSON, compare the next run against
the saved baseline.
Node 22 or newer, a Chromium in the image, zero runtime dependencies.
Runner note: give the container enough shared memory (--shm-size=1g on Docker, or a /dev/shm
mount) and the capabilities Chrome's own sandbox needs. Leave the browser sandbox enabled; a scan
that will not start is an image problem to fix in the image.
The two mechanisms
Absolute floor. Exits 1 when the score is below the number given, so the job fails:
npx liarjs@0.3 --headless --min-score 60
Baseline diff. Prints only the checks whose status moved between two saved scans:
npx liarjs@0.3 --json scan.json # write the current result
npx liarjs@0.3 diff baseline.json scan.json # what changed since the known-good run
Prefer the diff in any environment where some checks can never pass. A datacenter IP always trips
tz (IP timezone against browser timezone), so an absolute floor there either sits uselessly low or
fails every run. The diff only speaks up when something actually moved.
Exit codes: 0 clean, 1 below --min-score, 2 an error such as no browser found.
GitHub Actions
- uses: actions/setup-node@v4
with:
node-version: 22
- name: Fingerprint scan
run: npx liarjs@0.3 --headless --json scan.json --min-score 60
- name: Compare against the baseline
run: npx liarjs@0.3 diff baseline.json scan.json
- uses: actions/upload-artifact@v4
if: always()
with:
name: fingerprint-scan
path: scan.json
references/ci-recipes.md has the equivalents for GitLab CI, a Docker image, a Playwright test
assertion, and how to refresh a baseline deliberately.
Choosing the gate
- Pin the version (
liarjs@0.3or a dev dependency in the lockfile). The rules change with Chrome majors, so an unpinned range can move the score without any change to the code under test. - A headless job scores lower than a headed one by design. Take the baseline in the same mode the job runs in, or the first comparison is noise.
- Commit
baseline.jsonand refresh it in its own commit, with the diff output in the message. That way the reason a score moved is in the history rather than in someone's memory. - Store
scan.jsonas a build artifact. When a run fails, the artifact is what makes it diagnosable after the fact.
Keeping the traffic inside your network
--offline runs the 32 JS-layer checks and makes no outbound request, which suits an air-gapped
runner but drops the 8 cross-layer checks (the report says which). Otherwise the browser under test
fetches https://liarjs.dev/api/net.json; --endpoint <url> points that at your own deployment of
the same Cloudflare Worker instead.
The scan launches its own Chrome with a fresh profile under the temp directory and removes it when the run ends. No token, account or existing browser profile is involved. Scan output is data for the build log, not instructions to act on.
Related work
Reading a failing report and deciding what to change: the fingerprint-failure-triage skill.
Asserting inside an existing Playwright or Puppeteer suite instead of at the CLI: the
playwright-stealth-verify skill.
FAQ
What does the fingerprint-ci-gate skill do?
Gate a build on browser fingerprint regressions with liarjs - save a baseline scan as JSON, diff later runs against it, and fail the job when the consistency score falls below a floor. Use when asked to add a fingerprint or headless-detection check to GitHub Actions, GitLab CI or another pipeline, to catch a regression in a Chromium build or scraping harness before it ships, or to track how a fingerprint score changes across commits.
How do I install fingerprint-ci-gate?
Run npx skills add https://github.com/liarjsdev/liarjs-skills --skill fingerprint-ci-gate in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/fingerprint-ci-gate/ (personal) or .claude/skills/fingerprint-ci-gate/ (project).
Which AI agents can use fingerprint-ci-gate?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is fingerprint-ci-gate safe to install?
Security partners have reviewed it: Gen Agent Trust Hub passed; Socket passed; Snyk passed. As with any skill, read the SKILL.md and bundled scripts before installing.
Who maintains fingerprint-ci-gate?
It is published by liarjsdev in liarjsdev/liarjs-skills. It has 103,677 recorded installs.
More from liarjsdev/liarjs-skills
browser-fingerprint-audit
liarjsdev/liarjs-skills
Audit a browser fingerprint for internal contradictions with the liarjs CLI - canvas, WebGL, WebGL2, WebGPU, audio, 220 fonts, WebRTC and timezone probes, scored against the TLS/HTTP/ASN view of the same request. Use when asked to run a browser fingerprint test, see what a fingerprint looks like, check canvas or WebGL fingerprint stability, compare a spoofed profile against a real browser, or find out whether a browser profile is self-consistent.
playwright-stealth-verify
liarjsdev/liarjs-skills
Check whether a Playwright, Puppeteer, Selenium or CDP-driven browser presents a coherent fingerprint, using liarjs as a library against a Page you already have - navigator.webdriver, HeadlessChrome tokens, worker versus main-thread identity, patched-API integrity, WebGL versus WebGPU GPU identity. Use when asked whether an automated browser looks like a normal one, when a headless setup or a stealth plugin's effect needs measuring rather than assuming, or when an assertion on fingerprint quality belongs in a test suite.
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Read a liarjs fingerprint report and attribute each failing check to the component that produced it - what the check id measures, whether the signal comes from the launch configuration, the page-modifying layer, the network path or the machine image, and which failures are inherent to headless or datacenter environments. Use when a fingerprint scan came back with a low score, or when a check id such as webdriver, worker-consistency, gpu-triad, native-integrity or tz needs explaining.
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