surface-audit MCP server
Commit Nov 1, 2026Performs deterministic security smoke tests on web URLs to detect regressions in headers, TLS, cookies, and CORS before deployment.
Also known as fillbyte/surface-audit
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What is surface-audit MCP?
surface-audit performs deterministic security smoke tests on web URLs to detect regressions in headers, TLS, cookies, and CORS before deployment.
Summary generated from the project's README
About surface-audit MCP server
Detecting security regressions in web headers, TLS, and CORS before deployment is what surface-audit enables for engineering teams. This tool performs deterministic security smoke tests on staging, preview, and pre-production URLs to identify surface-level mistakes. It is designed to act as a security gate in continuous integration pipelines rather than a full crawling or exploit platform.
Developers can use this server locally or within CI environments via the CLI, Docker containers, or GitHub Actions. When used as an MCP server, it exposes tools like scan, list_checks, list_formats, and render_report to an AI client. To ensure safety, the MCP integration requires an explicit host allow-list to restrict which domains the AI can probe. The system generates findings in various formats including SARIF, Markdown, HTML, and JSON to integrate with code scanning tools and pull request comments.
What you can do with it
- 1Identify security regressionsCompare a new deployment against a baseline to see if any high-severity security issues were introduced.
- 2Automate CI security gatesFail a build automatically if the scan detects high-severity vulnerabilities in a preview environment.
- 3Audit web surface areaCheck a specific URL for missing security headers, weak TLS versions, or permissive CORS configurations.
- 4Generate machine-readable reportsProduce SARIF files to integrate security findings directly into GitHub Advanced Security dashboards.
Written from the project's README. Every use case is checked against a quote from it.
README
View on GitHubsurface-audit
Deterministic security smoke tests for staging, preview, and pre-deploy web apps.
surface-audit sends a small, bounded set of safe probes at a known
URL and turns the result into CI-friendly findings, SARIF, Markdown,
HTML, and JSON reports. It is designed for teams that want to catch
security regressions in headers, TLS, redirects, cookies, CORS, exposed
files, and other surface-level mistakes before they promote a build.
⚠️ Authorized use only. This tool sends real HTTP requests to the target. Only run it against systems you own or have explicit written permission to test. See
SECURITY.md.
Why Teams Use It
- Safe by default — bounded checks against a known URL, not a crawler and not an exploit framework.
- Regression-oriented — baseline suppression and report diff help answer "what got worse?" instead of just "what exists?"
- CI-native —
--fail-on, SARIF, Markdown, HTML, and JSON all fit cleanly into pull requests, code scanning, and release gates. - LLM-safe MCP support — the optional MCP server exposes only a host allow-listed interface.
- Extensible — checks and renderers are pluggable via entry points.
- Supply-chain aware — PyPI Trusted Publishing, Sigstore signatures, GitHub Releases, and CycloneDX SBOMs are built into the release flow.
Use It When
- you have a staging, preview, or pre-production URL
- you want a deterministic security gate in CI
- you care about security regressions between two deployments
- you want machine-readable output for SARIF, dashboards, or PR comments
Reach for Other Tools When
- you need full crawling or spidering
- you need authenticated scanning workflows
- you want exploit confirmation or a broad template corpus
That positioning is deliberate: surface-audit is strongest as a
pre-deploy security smoke test, not as a full DAST platform.
Quick Start
pipx install surface-audit
surface-audit scan https://preview.example.com \
--scope-host preview.example.com \
--fail-on HIGH
Detailed installation: docs/INSTALL.md.
Distribution Options
- PyPI — best when you want the CLI in
pipx, a virtualenv, or your own Python-based tooling. - GHCR — best when your CI prefers a prebuilt container image over installing Python dependencies at runtime.
- GitHub Action — best when a preview-environment workflow already lives in GitHub Actions and you want the shortest integration path.
Container-first teams can use the published GHCR image on tagged releases:
docker run --rm ghcr.io/fillbyte/surface-audit:latest \
scan https://preview.example.com --fail-on HIGH
Use the GitHub Action @v1 tag for the stable major line, or pin an
exact action release such as @v1.0.7 when you want fully reproducible
workflow inputs. Tagged releases also publish GitHub Release artifacts,
CycloneDX SBOMs, and Sigstore signatures.
More end-to-end patterns: docs/RECIPES.md. Release
and tag-management details: docs/RELEASE.md.
Security Regression Diff
# Capture a baseline once
surface-audit scan https://preview.example.com \
--output reports/baseline.json \
--format json
# Gate only on newly introduced HIGH+ findings
surface-audit scan https://preview.example.com \
--baseline reports/baseline.json \
--fail-on HIGH
# Or diff two reports explicitly
surface-audit diff reports/before.json reports/after.json \
--output reports/diff.json \
--fail-on-new
GitHub Action
The repository ships an action at the repo root so you can run the scan in a preview-environment workflow without hand-rolling install steps:
- name: Run surface-audit
uses: fillbyte/surface-audit@v1
with:
target: ${{ steps.preview.outputs.url }}
scope-hosts: preview.example.com
output: reports/surface-audit.sarif
format: sarif
fail-on: HIGH
- name: Upload SARIF
uses: github/codeql-action/upload-sarif@v4
with:
sarif_file: reports/surface-audit.sarif
More end-to-end patterns: docs/RECIPES.md.
Sample Output
Target: https://preview.example.com/
Summary: HIGH 1 MEDIUM 2 LOW 1
HIGH security-headers Missing Content-Security-Policy header
MEDIUM auth-cookies Cookie 'sessionid' missing SameSite
MEDIUM security-txt Missing /.well-known/security.txt
LOW directory-listing Auto-generated index page exposed
Built-in checks
| Check ID | OWASP | Summary |
|---|---|---|
security-headers |
A05 | Missing and weakly-configured HSTS / CSP / XFO / Referrer / Permissions |
ssl-tls |
A02 | Weak ciphers or obsolete TLS versions |
https-redirect |
A02 | Plain HTTP does not redirect to HTTPS |
cross-origin-isolation |
A05 | Missing COOP / COEP / CORP isolation headers |
xss-reflection |
A03 | Query-string input reflected without output encoding |
sql-injection |
A03 | Database error messages leaked on meta-character input |
csrf |
A01 | Mutating HTML forms without a recognizable anti-CSRF token |
auth-cookies |
A07 | Cookies missing Secure / HttpOnly / SameSite |
open-redirect |
A01 | Query parameters that allow off-origin 30x redirects |
misconfiguration |
A05 | Well-known exposed paths (.env, .git, admin consoles) |
directory-listing |
A05 | Auto-generated directory index pages |
cors |
A05 | Permissive CORS reflections and wildcard-with-credentials |
security-txt |
A09 | Missing /.well-known/security.txt (RFC 9116) |
Run surface-audit list-checks to see what is registered in your
environment (including any third-party plugins).
Usage
# Save a JSON report and fail CI on HIGH+ findings
surface-audit scan https://example.com \
--output reports/example.json --format json --fail-on HIGH
# Emit SARIF for GitHub Advanced Security
surface-audit scan https://example.com \
--output reports/example.sarif --format sarif
# Run only a subset of checks
surface-audit scan https://example.com \
--enable security-headers --enable ssl-tls
Full CLI and library reference: docs/USAGE.md.
MCP integration
pip install "surface-audit[mcp]"
surface-audit mcp-serve --allow-host staging.example.com
This exposes scan, list_checks, list_formats, and render_report
tools to local MCP clients while keeping scans gated behind an explicit
host allow-list.
Project Site
The project site highlights the smoke-test workflow, GitHub Action, sample artifacts, and core adoption patterns:
Download trends remain available via PyPI Stats.
Library example
import asyncio
from surface_audit import Scanner, ScannerConfig
async def main() -> None:
report = await Scanner(
"https://example.com",
config=ScannerConfig(max_concurrency=4, timeout=5.0),
).run()
for finding in report.findings:
print(finding.severity.value, finding.check_id, finding.title)
asyncio.run(main())
Extend it
Any package shipping an entry point under surface_audit.checks adds a
check. A starter template for third-party checks lives under
examples/plugin-template:
# your-plugin/pyproject.toml
[project.entry-points."surface_audit.checks"]
cors_wildcard = "my_checks.cors:PermissiveCORSCheck"
See docs/ARCHITECTURE.md for layering, SOLID
scorecard, and design patterns.
Documentation
docs/INSTALL.md— per-platform installationdocs/USAGE.md— CLI, library, and CI recipesdocs/RECIPES.md— preview, SARIF, baseline, MCP, and action recipesdocs/RELEASE.md— PyPI, GHCR, GitHub Release, andv1tag processdocs/ARCHITECTURE.md— layering and extension pointsdocs/SCHEMA.md— JSON report contractexamples/plugin-template— starter template for third-party checksSUPPORT.md— where to ask questions and report the right thingCONTRIBUTING.md— development workflowSECURITY.md— vulnerability disclosureCODE_OF_CONDUCT.md— community expectations
Development
make install # set up .venv with dev extras
make all # ruff + mypy + bandit + pytest
CI runs on every push across Python 3.10 – 3.14 — see
.github/workflows/ci.yml.
License
Apache License 2.0 — Copyright © 2026 Uğur Kontel. See also
NOTICE for attribution requirements that apply to
redistributions.
surface-audit is an open-source project from
Fillbyte.
surface-audit MCP questions
What kind of security checks does surface-audit perform?
It checks for security headers, SSL/TLS configurations, HTTPS redirects, CORS settings, cookie attributes, and exposed files.
Can I use this tool in my CI/CD pipeline?
Yes, it is designed to be CI-native and supports SARIF, Markdown, HTML, and JSON reports for integration with pull requests and release gates.
How does the tool handle security regressions?
It allows you to capture a baseline and then run scans that only fail if new high-severity findings are introduced.
Is it safe to run against any website?
No, you should only run it against systems you own or have explicit written permission to test.