harden
Skill19 starsChanged 32 days agoMITView on GitHub
Harden code where untrusted input enters the system. Use when implementing auth, handling user input, storing sensitive data, integrating external APIs, adding file uploads or LLM features, or crossing any trust boundary. Don't use for secret scanning (/safe-repo) or dependency CVEs (/deps-audit).
46 other projects use a version of this.
Adopted by
Most recently taken up by
- alchemy-run/alchemy-effecttheir own version, first seen Nov 9, 2026
- alchemy-run/alchemytheir own version, first seen Nov 8, 2026
- parker-brown-family/agent-skillstheir own version, first seen Nov 8, 2026
- nexmoe/DayBeetheir own version, first seen Nov 1, 2026
- davidanthonyn/claude-skillstheir own version, first seen Oct 20, 2026
- excatt/superclaude-plusplustheir own version, first seen Oct 13, 2026
Used with
Projects with it also use layout, shape and 3 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
owshq-mecSkilllayout
Improve layout, spacing, and visual rhythm. Fixes monotonous grids, inconsistent spacing, and weak visual hierarchy. Use when the user mentions layout feeling off, spacing issues, visual hierarchy, crowded UI, alignment problems, or wanting better composition.
Also in 5 projects that use this
HAR5HA-7663Skillshape
Plan the UX and UI for a feature before writing code. Runs a structured discovery interview, then produces a design brief that guides implementation. Use during the planning phase to establish design direction, constraints, and strategy before any code is written.
Also in 8 projects that use this
AnthropicSkillstart
Set up your bio-research environment and explore available tools. Use when first getting oriented with the plugin, checking which literature, drug-discovery, or visualization MCP servers are connected, or surveying available analysis skills before starting a new project.
Also in 3 projects that use this
CloudflareSkillsecurity-audit
Security guidance and vulnerability review for codebases, APIs, services, CLI tools, libraries, and daemons. Use for security questions, focused reviews, vulnerability research, security audits, or pen tests. Run the complete workflow only for explicit codebase audit or pen-test requests, full/comprehensive/end-to-end reviews, or requested report artifacts.
Also in 3 projects that use this
Microsoft AzureSkillverify
End-to-end app testing pipeline for browser-based web apps on cloud browsers via Azure Playwright Workspaces: verify the live app, author tests for working flows, heal failing tests, then re-run with video and produce one consolidated report. Three phases (app verification, test authoring, test healing) plus a scoped final sanity run; each phase emits a sub-report. Use when asked to "verify my app", "make sure my app works and has good test coverage", "do a full QA pass", "add tests where I'm missing coverage", "fix failing tests and add new ones", "smoke test before deploy", "QA my deployment", or any combined verify-and-test ask. Requires Azure CLI (`az login`) and a Playwright Workspace resource ID — bootstraps configs on first invocation. Browser-based web apps with Playwright only — not for unit/API tests, native mobile/desktop, load/perf, or full accessibility audits.
Also in 3 projects that use this
Other versions46 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 46
- alchemy-run/alchemy★ 1.9ksame name
- alchemy-run/alchemy-effect★ 1.9ksame name
- SterlingChin/marvin-template★ 1ksame name
- talesofai/cohub★ 585same name
- educlopez/ui-craft★ 441same name
- nexmoe/DayBee★ 424same name
- nexmoe/eve★ 424same name
- Southclaws/storyden★ 348same name
- AkaraChen/aghub★ 271same name
- zacharyfmarion/openscad-studio★ 238same name
36 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository42 other files it gives its agents.
- AGENTS.mdAGENTS.md
- a11y-auditSkill
- architecture-auditSkill
- buildSkill
- checkSkill
- codebase-designSkill
- code-reviewSkill
- commitSkill
- create-skillSkill
- debateSkill
- debugSkill
- deps-auditSkill
- domain-modelingSkill
- feedbackSkill
- frontend-ui-engineeringSkill
- grillSkill
- guideSkill
- handoffSkill
- i18nSkill
- perf-auditSkill
- prototypeSkill
- refactorSkill
- researchSkill
- retroSkill
- reviewSkill
- reviseSkill
- safe-repoSkill
- setupSkill
- source-drivenSkill
- tddSkill
- teachSkill
- to-adrSkill
- to-docSkill
- to-prSkill
- to-releaseSkill
- to-specSkill
- to-stackSkill
- to-ticketsSkill
- triageSkill
- visual-reviewSkill
- wait-whatSkill
- zoom-outSkill
The file
We split this skill into the rules it gives an agent
2 rules. 0 are common, 1 is distinctive, and 1 is very specific to this project.
0
Common
Most of the 44 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 49
No secrets or other tenants' data in prompts or retrieved context
- Very specific: line 55
After security-relevant code: deps-audit shows no critical/high CVEs (or each documented with review date).
“Common” is measured: kept by at least 6 in 10 of the 44 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Harden
Security as a constraint on every line that touches user data, auth, or external systems. Proactive: applied during implementation, not after. Reactive scans belong to safe-repo (sensitive data) and deps-audit (CVEs).
Ask first — human approval required
- New authentication flow or auth logic changes
- Storing new categories of sensitive data (PII, payment)
- New external service integrations
- CORS configuration changes
- File upload handlers
- Rate-limit / throttling changes
- Granting elevated permissions or roles
Validate at the boundary
Validate at the system boundary (route handler, message consumer), not in business logic: a schema validator (Zod, Joi, pydantic, …) defines the contract; reject with 422 + structured error before business logic touches the data. Trust internal code; validate only at the edges.
Defaults that are easy to forget
- Authorization per resource (ownership), not just authentication
- Queries parameterized; shell commands take argument arrays, never strings built from input; output encoded for its context (HTML, URL, JS)
- Passwords hashed with argon2, scrypt, or bcrypt; reset tokens single-use and short-lived
- OAuth with PKCE and
state; redirect targets from an allowlist, never a raw user-supplied URL - Third-party scripts pinned with Subresource Integrity hashes
- Session cookies
httpOnly+secure+sameSite; auth tokens never inlocalStorage - Strip sensitive fields from API responses by default
- Security headers (CSP, HSTS, X-Frame-Options, X-Content-Type-Options)
- Rate limit on auth endpoints
- Logs and error responses free of secrets, tokens, PII, stack traces
- File uploads: allowlist MIME types, enforce max size before processing, check magic bytes when the type matters, store outside the webroot
- Outbound requests: allowlist destinations; never fetch a user-provided URL unvalidated (SSRF)
- CORS: explicit origin allowlist from config; no wildcard on authenticated endpoints
- External integrations: verify webhook signatures, time out every external call, validate third-party response shapes before use; never deserialize untrusted input with unsafe loaders
- Log security events (auth failures, access denials, input rejections) — without the payloads
- Raw HTML from users only through a sanitizer (DOMPurify or equivalent)
AI / LLM features
- Model output is untrusted input: validate it before it reaches
eval, SQL, a shell,innerHTML, or a file path - The prompt is not a security boundary; enforce permissions in code (prompt injection)
- No secrets or other tenants' data in prompts or retrieved context
- Agent tools scoped to the task; a human confirms destructive actions
- Token, rate, and recursion limits on every model call
Verification
After security-relevant code: deps-audit shows no critical/high CVEs (or each documented with review date); safe-repo --diff clean; headers present (curl -I); authz checked on every protected endpoint.
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