Install
openclaw skills install @athola/nm-pensive-hardenApplies NIST/CWE security hardening to Python and Rust code
openclaw skills install @athola/nm-pensive-hardenNight Market Skill — ported from claude-night-market/pensive. For the full experience with agents, hooks, and commands, install the Claude Code plugin.
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.
/security-review.attune:war-room
with a security-focused panel.pensive:bug-review.harden:discovery — inventory languages, build files, hooks,
CI workflowsharden:scan-python — run python-checks.md detectors when
Python is presentharden:scan-rust — run rust-checks.md detectors when Rust
is presentharden:scan-cross-cutting — run cross-cutting.md detectors
(deps, secrets, SBOM, CI)harden:scan-frontier — run frontier-checks.md (PQC, LLM
supply chain, sandboxing)harden:nist-mapping — map findings to NIST SSDF practicesharden:proposals — for each finding above the threshold,
draft a concrete remediation per modules/proposal-shape.mdharden:approval-gate — present proposals to the user for
apply / file / defer / rejectharden:apply-and-validate — apply approved proposals as
discrete commits, re-run gates, capture evidenceharden:report — write reviews/harden-<date>.md and
optionally post to DiscussionsLoad 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.
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.
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.
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.
For each finding above the configured severity threshold, draft a
concrete remediation per modules/proposal-shape.md:
pensive:blast-radiusPresent 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.
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."
Write reviews/harden-<date>.md with:
If running inside a PR context, post the executive summary as a
comment via abstract:post_review_insights.
| 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 |
# 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`
- Pattern: <module>.loads(user_supplied_input)
- Reachability: untrusted, comes from request body
**Proposal:** ...
**Blast radius:** ...
**Reversal plan:** ...
--auto-apply,
CRITICAL findings always prompt.--report-only until the user has reviewed at least one
report and explicitly opts into proposals.The skill composes (rather than re-implements):
pensive:rust-review — full Rust audit when Rust is presentpensive:bug-review — bug-hunting backbonepensive:safety-critical-patterns — NASA Power-of-10 adaptedpensive:tiered-audit — three-tier discipline (--tier 1/2/3)pensive:blast-radius — change-impact assessment for proposalsleyline:supply-chain-advisory — dependency postureleyline:authentication-patterns — auth/credential reviewleyline:content-sanitization — input handlingabstract:hook-authoring — hook-event securityimbue:proof-of-work — evidence discipline for findings--auto-apply flag covering its severity).reviews/harden-<date>.md exists and lists every finding
with a disposition (applied / filed / deferred / rejected /
advisory).