Harden Codebase Skill

Active security hardening: scan the existing repository for vulnerabilities and forward-facing threats, then propose concrete remediations the user can approve, defer, or file.

This skill is the engine behind /harden. It complements the Claude Code built-in /security-review (which scans the pending diff) by sweeping the whole repository against citation-backed checks rather than line-level review of in-flight code.

When To Use

• Quarterly security-posture audits.
• Before tagging a release that touches sensitive code paths.
• After a published advisory affects the language ecosystem.
• When onboarding a new repository and want a baseline.
• After integrating a new dependency or upstream service.

When NOT To Use

• Pending-diff review on a single PR. Use /security-review.
• Architecture-level threat modeling. Use attune:war-room with a security-focused panel.
• Cryptographic protocol review. The skill flags suspect crypto but does not propose protocol fixes (specialist work).
• One-off bug hunting. Use pensive:bug-review.

Required TodoWrite Items

1. harden:discovery: inventory languages, build files, hooks, CI workflows
2. harden:scan-python: run python-checks.md detectors when Python is present
3. harden:scan-rust: run rust-checks.md detectors when Rust is present
4. harden:scan-cross-cutting: run cross-cutting.md detectors (deps, secrets, SBOM, CI)
5. harden:scan-frontier: run frontier-checks.md (PQC, LLM supply chain, sandboxing)
6. harden:nist-mapping: map findings to NIST SSDF practices
7. harden:proposals: for each finding above the threshold, draft a concrete remediation per modules/proposal-shape.md
8. harden:approval-gate: present proposals to the user for apply / file / defer / reject
9. harden:apply-and-validate: apply approved proposals as discrete commits, re-run gates, capture evidence
10. harden:findings-verified: citations confirmed by citation_verifier.py
11. harden:report: write reviews/harden-<date>.md and optionally post to Discussions

Progressive Loading

Load modules based on what the discovery step finds.

Detected	Load
Python files (*.py, pyproject.toml)	modules/python-checks.md
Rust files (*.rs, Cargo.toml)	modules/rust-checks.md
Any	modules/nist-controls.md (citation backbone)
Any	modules/cross-cutting.md (deps, secrets, CI)
LLM SDK use (anthropic, openai), MCP server, post-quantum surface	modules/frontier-checks.md
Any with proposals enabled	modules/proposal-shape.md

The module hub keeps the SKILL.md itself under the estimated_tokens: 1100 budget. Detail lives in the modules.

Core Workflow

Phase 1: Discovery

Inventory the repo without modifying anything:

# Languages and build files
find . -type f \( -name '*.py' -o -name '*.rs' -o -name '*.sh' \) \
  | head -200 > /tmp/harden-langs.txt

# Build manifests
ls pyproject.toml Cargo.toml package.json go.mod 2>/dev/null

# CI workflows and pre-commit
ls .github/workflows/ .pre-commit-config.yaml 2>/dev/null

# Hooks and Dockerfiles
find . -path ./node_modules -prune -o -type f \
  \( -name 'hooks.json' -o -name 'Dockerfile*' \) -print

Dispatch /discovery-prefilter if the repo has > 5000 source files to bound the scan.

Phase 2: Citation-backed scan

For each detected language, load the matching module and run its detector list. Each detector outputs findings with the schema defined in modules/proposal-shape.md. The citation column is mandatory: a finding without a NIST/CWE reference is downgraded to "advisory" and not eligible for active proposal.

Phase 3: NIST mapping

Group findings by SSDF practice (PW.4, PW.8, RV.1, etc.) and CWE ID. The mapping table lives in modules/nist-controls.md. The report's executive summary references SSDF practice coverage so the audit is comparable across runs.

Phase 4: Proposal generation

For each finding above the configured severity threshold, draft a concrete remediation per modules/proposal-shape.md:

• Specific files and lines touched
• Diff or config snippet (not "consider doing X")
• Blast-radius assessment via pensive:blast-radius
• Reversal plan: how to revert if the change breaks behavior
• Test that should pass after the change

Phase 5: Approval gate

Present proposals one at a time via AskUserQuestion. Default options: apply, file as issue, defer to backlog, reject. Auto-apply is opt-in via the --auto-apply flag and respects a per-finding severity threshold.

Phase 6: Apply and validate

Apply each approved proposal as a discrete commit:

git add <touched files>
git commit -m "harden: <finding-id> <one-line summary>"

After each apply, re-run the project gates:

make test --quiet && make lint && make type-check

If a gate fails, revert the commit (git revert HEAD --no-edit) and downgrade the finding to "needs human design."

Phase 7: Report

Write reviews/harden-<date>.md with:

• Executive summary (SSDF practice coverage, CWE distribution)
• Findings table grouped by severity
• Per-finding detail: detection signal, citation, proposal, status
• Disposition table (applied / filed / deferred / rejected)
• Re-run instructions

If running inside a PR context, post the executive summary as a comment via abstract:post_review_insights.

Severity Classification

Severity	Definition	Default disposition
CRITICAL	Active exploit path, RCE, credential leak	apply or file immediately
HIGH	Plausible exploit, missing defense-in-depth on attack surface	propose for apply
MEDIUM	Best-practice gap, hardening opportunity	propose for apply with --auto-apply medium
LOW	Style/documentation gap with security flavor	file as issue
ADVISORY	Pattern detected without exploit narrative	report only

Output Format

# Hardening Report — <date>

## Executive Summary

- Codebase: <repo> @ <sha>
- Languages scanned: Python (X files), Rust (Y files)
- NIST SSDF practices covered: PW.4, PW.7, PW.8, RV.1, RV.2
- CWE Top 25 hits: <count> across <distinct CWEs>
- Disposition: <N> applied, <N> filed, <N> deferred, <N> rejected

## Findings

| ID | Severity | Citation | File:Line | Disposition |
|----|----------|----------|-----------|-------------|
| H1 | CRITICAL | CWE-502, NIST SSDF PW.7 | `src/x.py:45` | applied (commit abc123) |
| H2 | HIGH | CWE-89, NIST SSDF PW.4 | `src/y.py:120` | filed (#456) |

## Per-finding detail

### H1 — Unsafe deserialization

**Citation:** CWE-502 (Deserialization of Untrusted Data),
NIST SSDF PW.7 (Review and analyze human-readable code).

**Detection signal:**
- File: `src/x.py:45`
- Anchor: `data = pickle.loads(user_supplied_input)`
- Pattern: <module>.loads(user_supplied_input)
- Reachability: untrusted, comes from request body

**Proposal:** ...

**Blast radius:** ...

**Reversal plan:** ...

Safety Rails

• Never apply without approval. Even with --auto-apply, CRITICAL findings always prompt.
• One finding per commit. Reversals are per-finding, not per-batch.
• Re-run gates after each apply. A gate failure reverts the commit and downgrades the finding.
• Citation is mandatory. Findings without a NIST/CWE/RustSec reference are advisory only and skip the apply phase.
• Read-only on first run. First invocation defaults to --report-only until the user has reviewed at least one report and explicitly opts into proposals.

Integration

The skill composes (rather than re-implements):

• pensive:rust-review: full Rust audit when Rust is present
• pensive:bug-review: bug-hunting backbone
• pensive:safety-critical-patterns: NASA Power-of-10 adapted
• pensive:tiered-audit: three-tier discipline (--tier 1/2/3)
• pensive:blast-radius: change-impact assessment for proposals
• leyline:supply-chain-advisory: dependency posture
• leyline:authentication-patterns: auth/credential review
• leyline:content-sanitization: input handling
• abstract:hook-authoring: hook-event security
• imbue:proof-of-work: evidence discipline for findings

Verify Findings Are Grounded (harden:findings-verified)

Write findings to .review/findings.json, run the citation verifier (Skill(imbue:review-core) Step 5), and drop or label UNVERIFIED any the verifier rejects.

Exit Criteria

• Discovery output lists every language and build manifest detected in the repo.
• Each finding carries a CWE or NIST SSDF citation; the report executive summary lists the SSDF practice coverage.
• Each finding above the severity threshold has a concrete proposal (file, diff or config snippet, blast radius, reversal plan, expected-passing test).
• No proposal was applied without explicit user approval (or without an --auto-apply flag covering its severity).
• Each applied proposal is its own commit, reversal-friendly.
• After every apply, the project gates were re-run; any gate failure reverted the commit and downgraded the finding.
• reviews/harden-<date>.md exists and lists every finding with a disposition (applied / filed / deferred / rejected / advisory).
• Every reported finding carries a Location + verbatim Anchor confirmed by citation_verifier.py (exit 0), or unverified findings were dropped or labeled UNVERIFIED.