security-recipes.ai

Search CVEs. Remediate vulnerabilities with AI agents. Sourced facts stay sourced, remediation stays bounded, and every plan carries verification, rollback, and stop conditions — the live site's contract, and this repo's.

security-recipes.ai is an Eleventy site for sourced CVE intelligence and evidence-gated vulnerability remediation that AI agents can consume without inheriting deployment or production authority.

The project is intentionally narrow:

• a complete rolling Medium/High/Critical CVE database,
• evidence-qualified canonical CVE remediation records,
• practical security remediation recipes,
• prompt and rules-file examples,
• agent setup guides,
• MCP integration patterns,
• an optional read-only MCP server for recipe search and approved upstream MCP context,
• a reusable GitHub Action that turns this guidance into toggleable CI health checks.

It is not a scanner, ticketing system, SOAR platform, deployment tool, or custom security toolkit. Existing security tools should produce the findings; this site helps agents use the right remediation context and stop at the right time.

Start with the live CVE Database for an exact vulnerability or the AI Vulnerability Remediation Playbooks for the evidence-to-patch workflow. Agent-specific guides cover Codex, Claude Code, Cursor, GitHub Copilot, Devin, Shiba Studio, Hermes Desktop, and OpenClaw. The Visual Guide shows the complete path from source qualification and search discovery to a bounded plan, proof, rollback, and human review. For the distinct problem of securing an agent system's identities, tools, connectors, context, memory, runtime, and recovery controls, use AI Agent Security.

Current product and workflow

Qualified search discovery

The complete catalog remains searchable, while public canonical CVE pages stay limited to reviewed or evidence-qualified records. Those pages ship unique search metadata, server-rendered core facts and affected-version evidence, one remediation authority (stable reviewed guidance first, otherwise complete source-linked AI enrichment), a short approval-gated AI implementation prompt, canonical URLs, breadcrumbs, and Article/TechArticle structured data. The CVE database describes the catalog as a Dataset; the remediation pillar exposes its visible seven-step workflow as a HowTo. Year-partitioned CVE sitemaps contain only indexable canonical routes, and the build fails when sitemap parity, canonical ownership, crawl reachability, metadata limits, or same-origin links drift.

Indexability is also withheld from mass-templated recipe children. The 72 development code-hygiene recipes and 39 generated compliance-framework recipes remain browsable from their canonical hubs with noindex,follow while they share a common method. A bounded rendered-body similarity gate prevents a child from re-entering sitemaps until its evidence, examples, and tests are materially distinct. The hubs remain indexable and carry the shared discovery context.

After an SEO-bearing release, the public revision must match the merge commit before sitemap submission or URL inspection. The Caddy deployment guide documents the DNS-verified Search Console handoff, priority live-URL checks, sitemap submission, indexing requests, and query monitoring. Submission is a discovery hint; it does not guarantee indexing or a particular ranking.

The remediation pillar also records a public repository example for CVE-2026-13149 in brace-expansion. It ties the dependency-only change to the reviewed pull request, tests, advisory evidence, and recovery path while explicitly separating the same PR's unrelated Fail2Ban work.

CVE search to canonical record	CVE evidence to bounded agent plan
Proof and human review	Read-only MCP context

What this project is for

AI coding agents can help close security findings when their work is bounded: one finding, one recipe, one reviewed output.

security-recipes.ai helps teams answer:

• Which recipe matches this finding?
• Which prompt should the agent use?
• Where do I put the instructions for Copilot, Claude, Cursor, Codex, or Devin?
• Which MCP servers should the agent read for advisory, scanner, repository, or runbook context?
• What should the PR or triage note include before a reviewer trusts it?

What ships

• Eleventy documentation site (fast static builds, no Go toolchain).
• CVE-first observatory home page and data-first CVE database.
• Recipe hubs for dependency, SAST, sensitive-data, base-image, CVE, and default-hardening remediation.
• CVE intelligence intake policy, prompt, fixtures, and evaluator for routing advisory signals before an agent patches.
• A complete rolling ten-year Medium/High/Critical CVE catalog composed from integrity-verified NVD JSON 2.0 feeds, CISA KEV metadata, and every applicable vetted remediation archetype. Only reviewed stable Markdown pages override that conservative baseline.
• An integrity-hashed search allowlist that publishes canonical CVE pages only for reviewed stable Markdown or AI enrichment that passes the deterministic recipe-ready evidence contract. The full database remains searchable even when a record is not eligible for search indexing.
• A versioned seven-phase agentic change contract for every catalog CVE: discover, assess, mitigate, remediate, verify, rollback, and triage. Each action declares likely file targets, mutation and approval boundaries, required evidence, outputs, and failure behavior without guessing a patch or fixed version.
• A structured compliance library spanning 39 security, privacy, assurance, resilience, and software-supply-chain frameworks without reproducing licensed control text. Its framework hub is the search surface; templated child assessments remain noindex,follow until differentiated.
• A 72-recipe code-hygiene library covering cross-language and ecosystem- specific audit, remediation, verification, and stop-condition workflows. Its development children remain noindex,follow while their bodies share a generated template.
• Recipes with existing prompt collections preserved.
• Agent setup guides for GitHub Copilot, Claude, Cursor, Codex, and Devin.
• MCP integration guidance for public and organization-approved security data sources.
• Optional read-only FastMCP server in mcp_server.py for recipe search, retrieval, and opt-in upstream MCP context.
• Docker and Docker Compose configuration for local or droplet hosting.
• Helper scripts for site maintenance, validation, imports, and deployment.

Repository map