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Hacker News - Newest: "AI"

AI can't read an investor deck AI as an attorney? Student uses ChatGPT, Gemini to sue UW over alleged racial discrimination Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval GitHub - MeepCastana/KubeezCut: Free Web based video editor Can AI judge journalism? A Thiel-backed startup says yes, even if it risks chilling whistleblowers Coming soon: 10 Things That Matter in AI Right Now DARPA built an AI to fact-check enemy weapons claims What explains heterogeneity in AI adoption? When AI Meets Muscle: Context-Aware Electrical Stimulation Promises a New Way to Guide Human Movements - Department of Computer Science AI Changed How We Build. It Did Not Change What Matters. Linux rules on using AI-generated code - Copilot is OK, but humans must take 'full responsibility for the… Meta spins up AI version of Mark Zuckerberg to engage with employees Code Mode: Let Your AI Write Programs, Not Just Call Tools | TanStack Blog GitHub - Delavalom/graft: Go framework for building AI agents. Type-safe tools, multi-provider (OpenAI, Anthropic, Gemini, Bedrock), zero vendor SDKs. India's TCS tops estimates, says new AI models did not dent services demand Gen Z's fading AI hype Strong feeling: we are in a folded AI reality GitHub - machinarii/total-recall-catalog: A reference catalog of latest knowledge retrieval, memory & RAG systems GitHub - mensfeld/code-on-incus: Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.. Quantization, LoRA, and the 8% Problem: Benchmarking Local LLMs for Production AI Iran war: We spoke to the man making Lego-style AI videos that experts say are powerful propaganda Powell, Bessent discussed Anthropic's Mythos AI cyber threat with major U.S. banks GitHub - immartian/bellamem: Persistent belief-graph memory for AI agents. Retrieves decisive context by importance — not recency, not RAG, not /compact. recursive-mode: The Repo-Native Operating System for AI Engineering After the attack on Sam Altman's home, will AI CEO's go on the offensive? The biggest advance in AI since the LLM Opus 4.6 vs GPT 5.4 One Prompt Unity World Generation Test “AI polls” are fake polls Client Challenge Can AI be a 'child of God'? Inside Anthropic's meeting with Christian leaders
GitHub - MuddySheep/vibeguard-local
MuddySheep · 2026-05-07 · via Hacker News - Newest: "AI"

Static SQL safety analysis for AI agents. Catch the dangerous queries before they reach your database.

npm version License CI


What it does

Your AI agent generates a SQL query. Before you run it, @vibeguard-dev/local checks the query's structure for known footguns: missing WHERE clauses, cartesian explosions, type-coercion bugs, recursive CTEs that don't terminate. 12 senior-DBA-level checks, all static, sub-millisecond, zero network calls.

Quickstart

npm install @vibeguard-dev/local libpg-query

libpg-query is a peer dependency — install it alongside the SDK. Server-side Node only for the initial release; browser support is out of scope for now.

ESM

import { analyze, init } from "@vibeguard-dev/local";

await init(); // one-time WASM-parser bootstrap

const result = analyze(`UPDATE users SET email = 'x@y.com'`);

if (result.catches.length > 0) {
  console.error(result.catches[0]);
  // {
  //   code: 'SQL-003',
  //   title: 'Unbounded UPDATE statement',
  //   severity: 'block',
  //   confidence: 99,
  //   detail: 'UPDATE on `users` has no WHERE clause. Every row in the table will be modified...',
  //   fix:    'Add a WHERE clause that scopes the update to specific rows...',
  //   threatCategories: ['destruction'],
  // }
}

CommonJS

const { analyze, init } = require("@vibeguard-dev/local");

(async () => {
  await init();
  const result = analyze("DELETE FROM users");
  console.log(result.catches[0]?.code); // 'SQL-003'
})();

That's the whole API. After init(), every analyze() call is synchronous and sub-millisecond on typical queries.

What we deliberately do NOT do

This SDK does static analysis only. It checks the shape of your SQL. It does not:

  • Compare your agent's stated intent against what the SQL would actually do
  • Estimate real blast radius from the upstream Postgres planner
  • Provide tamper-evident audit logging
  • Offer human-in-the-loop escalation for grey-zone queries
  • Track per-agent behavioral baselines over time

For those, you want VibeGuard Cloud — the wire-protocol proxy and MCP server this SDK is the static-analysis layer of. Use the SDK locally; use the cloud in production. The two are designed to work together.

The 12 catches

Each catch has a stable code (e.g. SQL-001), a severity, a confidence range, and links to a docs page with examples and references. Catch IDs are forever-stable — once published, an ID always means the same thing (see STABILITY.md).

Code Title Severity Confidence Status
SQL-001 Cartesian explosion block 90–95 ✅ shipped
SQL-002 Self-join footgun warn 70–85 ✅ shipped
SQL-003 Unbounded UPDATE / DELETE block 95–99 ✅ shipped
SQL-004 Implicit type coercion in WHERE warn 75–85 ✅ shipped
SQL-005 NULL comparison footgun warn 90–95 ✅ shipped
SQL-006 OFFSET without ORDER BY warn 85–95 ✅ shipped
SQL-007 NOT IN with nullable subquery warn 75–85 ✅ shipped
SQL-008 String-concat injection patterns block 80–95 ✅ shipped
SQL-009 DISTINCT without obvious reduction info 60–75 ✅ shipped
SQL-010 Correlated subquery in SELECT warn 70–85 ✅ shipped
SQL-011 Aggregate without GROUP BY warn 85–95 ✅ shipped
SQL-012 Recursive CTE without termination block 80–95 ✅ shipped

See ROADMAP.md for what's in / out of scope.

Use with...

Each example is a short, runnable integration showing how to wire the SDK into a common AI tool's pre-execution flow:

Architecture, in one paragraph

The SDK parses your SQL with libpg-query, walks the resulting AST with a small, pure-function traversal helper, and runs each query through a registry of catch-functions. Each catch returns either null (didn't fire) or a structured Catch with code, severity, confidence, detail, and fix. No network calls. No state between calls. Sub-millisecond on typical queries. See ARCHITECTURE.md for the full design rationale.

Contributing

We welcome new catches that meet the SDK's scope: static-AST-detectable SQL anti-patterns with documented real-world incidents. The proposal process starts with an issue (template here); PRs come after maintainer feedback on whether the pattern fits.

See CONTRIBUTING.md for the full process, CODE_OF_CONDUCT.md for community expectations, and ARCHITECTURE.md for how the codebase is laid out.

Security

This SDK does static analysis. It does not execute SQL. It does not open network connections. It does not log to disk.

If you find a vulnerability — a false-negative that lets a real-world dangerous pattern through, a panic / crash on adversarial input, or a supply-chain concern — see SECURITY.md for the disclosure process. Do not file security issues as public GitHub issues.

License

Apache License 2.0 — see also NOTICE for attribution requirements that travel with derivative works.

About

VibeGuard is a wire-protocol security layer for AI agents that write SQL. This SDK is the open-source static-analysis component of the broader product.