@ktbatterham/external-posture-core
v0.8.0
Published
Low-noise external posture analysis core for web targets.
Maintainers
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@ktbatterham/external-posture-core
Low-noise external posture analysis for public web targets.
This package is the reusable scanner engine extracted from the External Posture Insight app. It is designed for passive or near-passive posture assessment rather than active exploitation or noisy recon.
Safety model
External Posture Insight is passive-first and production-conscious, but it is not magic invisibility dust. A standard scan may make DNS queries, perform TLS handshakes, fetch the target page, follow redirects, query third-party public datasets such as Certificate Transparency / OSV, and run a small set of low-noise HTTP checks. It does not attempt exploitation, brute forcing, authentication bypass, form submission, fuzzing, password testing, or vulnerability exploitation.
Use it only against systems you own or are authorized to assess. Results are heuristic and should be treated as decision support, not a formal penetration test or compliance attestation.
What it covers
- HTTP security headers and redirect posture
- TLS and certificate inspection
- Cookie hygiene
- Passive HTML inspection
- AI surface and third-party trust signals
- Low-noise exposure, CORS, API-surface, and DNS/mail posture checks
- OWASP/MITRE-aligned finding labels
Current status
This package is published and consumable from npm:
It is also used by the External Posture Insight app from the local workspace during development.
Release workflow
- local package check:
npm run pack:core - CI verification:
.github/workflows/core-package-checks.yml - publish workflow:
.github/workflows/publish-core-package.yml - publish requires an
NPM_TOKENrepository secret
Recommended release flow:
- update the version in
packages/core/package.json - run
npm run test:core - run
npm run pack:core - create and push a tag like
core-v0.1.1 - let the publish workflow release the package
See also:
packages/core/CHANGELOG.mdpackages/core/RELEASING.md
Public API
CLI
The package now includes a pipe-friendly CLI:
npx @ktbatterham/external-posture-core scan example.comInstall globally if you want the short command:
npm install -g @ktbatterham/external-posture-core
epi scan example.comScan multiple targets in one run:
npx @ktbatterham/external-posture-core scan example.com github.com bbc.co.uk
epi scan example.com github.com bbc.co.ukAvailable output formats:
npx @ktbatterham/external-posture-core scan example.com --format summary
npx @ktbatterham/external-posture-core scan example.com --format json
npx @ktbatterham/external-posture-core scan example.com --format markdown
npx @ktbatterham/external-posture-core scan example.com --format sarif
npx @ktbatterham/external-posture-core scan example.com --format ci-jsonThe CLI writes machine-readable report output to stdout, and lightweight multi-target progress to stderr only when running interactively. This keeps JSON/SARIF output pipe-friendly.
CI policy modes:
npx @ktbatterham/external-posture-core scan example.com github.com --fail-on warning
npx @ktbatterham/external-posture-core scan example.com --baseline previous-report.json --fail-on-regression
npx @ktbatterham/external-posture-core scan example.com github.com --fail-if-score-below 75
npx @ktbatterham/external-posture-core compare current-report.json baseline-report.json --fail-on critical --fail-on-regression--fail-onsets exit code1when findings at or above the selected severity are present.--fail-on-regressionsets exit code1when the baseline comparison detects a regression (score drop, new issues, or worse HTTP status class).--fail-if-score-belowsets exit code1when any scanned target score is below the given threshold.
Write results to a file:
npx @ktbatterham/external-posture-core scan example.com --format json --output report.jsonCompare against a previously saved JSON report:
npx @ktbatterham/external-posture-core scan example.com --baseline previous-report.jsonCompare two saved reports directly:
npx @ktbatterham/external-posture-core compare current-report.json baseline-report.json
npx @ktbatterham/external-posture-core compare current-report.json baseline-report.json --format sarifBatch scans return:
- summary: one line per target
- markdown: a compact comparison table
- sarif: one SARIF log containing findings across all scanned targets
- ci-json: compact machine-readable output with policy pass/fail status
- json:
{
"analyses": [{ "...": "scan result" }]
}Direct report comparison returns:
- summary: score, status, and change summary
- markdown: a compact comparison report
- sarif: only findings that are newly introduced in the current report versus the baseline
- ci-json: compact machine-readable output with policy pass/fail status and diff details
- json:
{
"current": { "...": "latest saved report" },
"baseline": { "...": "older saved report" },
"diff": { "...": "structured change summary" }
}Show usage:
npx @ktbatterham/external-posture-core --helpanalyzeUrl(url)
Run a full posture analysis for a public target.
import { analyzeUrl } from "@ktbatterham/external-posture-core";
const result = await analyzeUrl("https://example.com");
console.log(result.score, result.grade);analyzeTarget remains available as a compatibility alias, but analyzeUrl is the primary public entrypoint.
When a baseline report is supplied to the CLI, summary and Markdown output append a Changes Since Baseline section. JSON output returns:
{
"analysis": { "...": "latest scan result" },
"diff": { "...": "structured change summary" }
}analyzeHtmlDocument(url, html)
Run passive HTML/content analysis against a fetched HTML document.
import { analyzeHtmlDocument } from "@ktbatterham/external-posture-core";
const htmlSecurity = analyzeHtmlDocument("https://example.com", "<html>...</html>");
console.log(htmlSecurity.clientExposureSignals);Notes
- Only use this against targets you are authorized to assess.
- The package is intentionally conservative about active probing.
- Scoring is heuristic and should be treated as a prioritization aid, not an absolute security truth.
- The author is not responsible for misuse, unauthorized scanning, operational impact, or decisions made from the output without appropriate validation.
