Sql Security logo

Sql Security

Community
mizchi
sql-security

SQL injection screening for host code (MoonBit / TS / Rust) plus secretlint setup notes. Flags single-line template-literal or string-concat SQL builders, regardless of value source — the scanner is line-based and does NOT trace data flow, so a clean scan is not proof of safety (multi-line template literals are missed) and every hit needs a manual review or an explicit `// sql-security: ok` opt-out.

Overview

Publishermizchi
Repositoryskills
Skill namesql-security
Stars
333
Forks
4
Bundled files
1
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by mizchi on GitHub. Read the source before you install it.

Installation

Install the Sql Security AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mizchi/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/sql-security .claude/skills/sql-security
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sql Security in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Sql Security on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Sql Security is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

SQL Security

Use this when a project ships SQL through host code (MoonBit / TS / Rust / Go) and wants a cheap line of defence against the two recurring sources of SQL-domain incidents:

  1. SQL injection: a string template that interpolates a value into a SQL fragment instead of binding it through a placeholder.
  2. Secrets in queries: a hardcoded token or connection string that leaks into git history. Handled by secretlint, not this skill — see "Companion: secretlint" below.

sql-injection-scan.mjs

bash
node scripts/sql-injection-scan.mjs your-project/src

The scanner walks the directory, ignores generated files (db/gen/, sqlc_*.mbt, *.test.mbt, _build/, dist/, target/), and flags:

  • template-interp: a backtick string literal that starts with a SQL keyword (SELECT, INSERT INTO, WHERE, AND (, ...) AND contains a ${...} placeholder. Example: `WHERE c.vector_id IN (${placeholders})`.
  • string-concat: a quoted SQL string adjacent to a + and an identifier. Example: "SELECT * FROM " + table.

The keyword match is case-sensitive on purposefrom / where / join appear constantly in English prose and would generate hundreds of false positives if matched case-insensitively.

The scanner exits 1 on findings — every hit deserves a manual review even if it turns out to be safe.

Limitations — a clean scan is NOT proof of safety

The scanner reads one line at a time. Its template-literal rule requires the opening backtick, the ${...} placeholder, and the closing backtick to all sit on a single physical line. Consequences:

  • Multi-line template literals are silently missed. A query whose backtick opens on one line and whose ${value} lands on a continuation line (a common formatting style) produces zero findings and exit 0, even though it is a genuine injection. Example the scanner does NOT catch:

    ts
    const sql = `
      SELECT id FROM users
      WHERE name = ${name}   // <-- real injection, not flagged
    `;
  • Exit 0 means "no single-line hits found," never "safe." When reviewing for SQL injection, also read any multi-line or programmatically-assembled SQL by hand; do not treat a clean scan as a pass. Fold a multi-line query onto one line if you want the scanner to see it.

This is a deliberate cost/coverage trade-off (zero-dep, no parser), not a bug — but it is a blind spot you must compensate for in review.

Reading the findings

A finding does not automatically mean injection. Many legitimate cases exist:

  • Internal placeholder expansion: building ?,?,?,...,? for an IN clause from a server-derived count. The interpolated value is ?, never user input. Annotate with the opt-out comment so future scans can ignore it.
  • FTS5 / vector queries that sqlc cannot parse: dynamic clause builders that interpolate column lists or ? counts. User input still passes through .bind(...).
  • Inline migration scripts building DDL at deploy time.

The scanner is intentionally noisy because the cost of missing one real SQLi is much higher than the cost of triaging a list of 5 false positives.

Opt-out marker

To silence a known-safe line, add a comment with the marker sql-security: ok either on the same line or on the line above:

ts
// sql-security: ok (placeholders is server-derived `?` count, values bind separately)
const sql = `WHERE c.vector_id IN (${placeholders})`;

The scanner accepts // (TS / MoonBit / Rust / Go) and # (Python / shell) comment markers.

Companion: secretlint

For credential leakage (the other half of "SQL security"), use secretlint. Recommended setup for a pkfire-managed repo's pre-push hook:

bash
pnpm add -D secretlint @secretlint/secretlint-rule-preset-recommend

Then run on pre-push:

bash
pnpm exec secretlint --secretlintignore .gitignore "**/*"

This is per-repo and complements any user-global secretlint configuration. The mizchi/skills/pkfire skill has a ready-made recipe at assets/recipes/14-secretlint-pre-push.pkl for projects using pkfire hooks.

When to invoke

  • pre-push: cheap, runs once before sending code to the remote.
  • pre-commit: optional. secretlint here can be slow on large diffs; sql-injection-scan is cheap enough.
  • PR review: paste the scanner output into the review checklist.

Not in scope

  • Stored XSS / template injection: these go through frontend / templating layers, not SQL.
  • Authz bypasses: row-level access checks are app logic, not a SQL concern.
  • DoS via expensive query: covered by sql-plan-audit (look for new SCAN entries) and rate limiting at the edge.

Engine extensibility

The scanner regex is engine-agnostic. The SQL-keyword set works for SQLite / Postgres / MySQL out of the box. Add RETURNING / OVERLAPS / LIMIT OFFSET if a Postgres-heavy project needs broader coverage.

Requirements

  • Node 20 or newer.

Files

  • scripts/sql-injection-scan.mjs — zero-dep text scanner.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Sql Security AI skill do?

SQL injection screening for host code (MoonBit / TS / Rust) plus secretlint setup notes. Flags single-line template-literal or string-concat SQL builders, regardless of value source — the scanner is line-based and does NOT trace data flow, so a clean scan is not proof of safety (multi-line template literals are missed) and every hit needs a manual review or an explicit `// sql-security: ok` opt-out.

Why use Sql Security on TypingMind?

Because you install it once and use it with any model. Sql Security is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Sql Security in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mizchi/skills/tree/main/sql-security. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Sql Security?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Sql Security?

As many as you like. As long as a model supports skills, you can use Sql Security with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Sql Security AI skill free?

It is published on GitHub by mizchi. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇