Quickstart

Quickstart — your first gap analysis in 5 minutes

This guide gets you from a fresh install to a real OSCAL Assessment Results document.

Prerequisites

• Python 3.12+ (python --version to check)
• No prior setup — this quickstart uses evidentia init to scaffold a starter control inventory, so you can run end-to-end from a fresh install

Step 1 — Install (30 seconds)

pip install evidentia

Verify:

evidentia version
# → Evidentia v0.10.9 / Python 3.12.x

Step 2 — Pick a framework (10 seconds)

evidentia catalog list --tier=A

You'll see ~48 Tier-A (production-grade, verbatim-licensed) frameworks. For this quickstart, we'll use NIST 800-53 Rev 5 Low baseline (~149 controls — small enough to inspect by hand).

Step 3 — Scaffold an inventory and run gap analysis (60 seconds)

evidentia gap analyze is inventory-driven: you give it a file describing the controls your organization has (--inventory) and the frameworks to measure against (--frameworks). Scaffold a starter inventory — this writes evidentia.yaml, my-controls.yaml, and system-context.yaml into the current directory:

evidentia init --preset nist-moderate-starter

Then run the analysis against the Low baseline (--inventory, --frameworks, and --output are the three flags you need):

evidentia gap analyze \
  --inventory=my-controls.yaml \
  --frameworks=nist-800-53-rev5-low \
  --output=gap-report.json

Evidentia prints a summary table to the console and writes the full report to gap-report.json:

                 Gap Analysis Summary
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┓
┃ Metric                     ┃     Value ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━┩
│ Total controls required    │       149 │
│ Total gaps                 │       112 │
│ Critical                   │         6 │
│ High                       │        24 │
│ Medium                     │        58 │
│ Low                        │        24 │
│ Coverage                   │     24.8% │
│ Efficiency opportunities   │         3 │
└────────────────────────────┴───────────┘

(Counts are illustrative — the starter inventory is intentionally small, so most Low-baseline controls show up as gaps. Edit my-controls.yaml with your real controls to see your true posture.)

Step 4 — Emit OSCAL Assessment Results (10 seconds)

evidentia gap analyze \
  --inventory=my-controls.yaml \
  --frameworks=nist-800-53-rev5-low \
  --format=oscal-ar \
  --output=assessment-results.json

This produces a NIST OSCAL Assessment Results 1.2.1 document. Validate with:

pip install compliance-trestle
trestle validate --type oscal-ar --file assessment-results.json
# → PASS

Step 5 — Verify the artifact chain (60 seconds)

The wheel you installed has a PEP 740 attestation:

pip install pypi-attestations
pypi-attestations verify pypi \
  --repository https://github.com/Polycentric-Labs/evidentia \
  "pypi:evidentia-0.10.9-py3-none-any.whl"
# → OK: evidentia-0.10.9-py3-none-any.whl

The container image is cosign-signed (if you used the Docker install path):

cosign verify ghcr.io/polycentric-labs/evidentia:v0.10.9 \
  --certificate-identity-regexp 'https://github\.com/Polycentric-Labs/evidentia/\.github/workflows/release\.yml@refs/tags/v.*' \
  --certificate-oidc-issuer https://token.actions.githubusercontent.com
# → "The cosign claims were validated"

Full verification recipes: see docs/verification.md.

What's next

• Run against your own controls: point --inventory at your real control inventory (YAML/CSV/JSON). To fold in collected evidence, run a collector (see first-collection.md) and pass --findings with --format oscal-ar.
• Wire to a CI gate: emit SARIF for GitHub Code Scanning (guide).
• Drive from an AI agent: enable the MCP server (guide).
• Add a custom framework: write your own catalog YAML (guide).

Got stuck?

• Common issues + fixes: 6-project/faq.md
• Open a discussion: github.com/Polycentric-Labs/evidentia/discussions
• Report a bug: github.com/Polycentric-Labs/evidentia/issues/new