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Convex Security Check

Community
waynesutton
convex-security-check

Quick security audit checklist covering authentication, function exposure, argument validation, row-level access control, and environment variable handling

Overview

Publisherwaynesutton
Repositoryconvexskills
Skill nameconvex-security-check
Stars
404
Forks
32
Bundled files
3
LicenseApache-2.0
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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Convex Security Check 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/waynesutton/convexskills.git /tmp/convexskills
mkdir -p .claude/skills
cp -r /tmp/convexskills/skills/convex-security-check .claude/skills/convex-security-check
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Convex Security Check 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 Convex Security Check 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 Convex Security Check 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.

Convex Security Check

A quick security audit checklist for Convex applications covering authentication, function exposure, argument validation, row-level access control, and environment variable handling.

Documentation Sources

Before implementing, do not assume; fetch the latest documentation:

Instructions

Security Checklist

Use this checklist to quickly audit your Convex application's security:

1. Authentication
  • Authentication provider configured (Clerk, Auth0, etc.)
  • All sensitive queries check ctx.auth.getUserIdentity()
  • Unauthenticated access explicitly allowed where intended
  • Session tokens properly validated
2. Function Exposure
  • Public functions (query, mutation, action) reviewed
  • Internal functions use internalQuery, internalMutation, internalAction
  • No sensitive operations exposed as public functions
  • HTTP actions validate origin/authentication
3. Argument Validation
  • All functions have explicit args validators
  • All functions have explicit returns validators
  • No v.any() used for sensitive data
  • ID validators use correct table names
4. Row-Level Access Control
  • Users can only access their own data
  • Admin functions check user roles
  • Shared resources have proper access checks
  • Deletion functions verify ownership
5. Environment Variables
  • API keys stored in environment variables
  • No secrets in code or schema
  • Different keys for dev/prod environments
  • Environment variables accessed only in actions

Authentication Check

typescript
// convex/auth.ts
import { query, mutation } from "./_generated/server";
import { v } from "convex/values";
import { ConvexError } from "convex/values";

// Helper to require authentication
async function requireAuth(ctx: QueryCtx | MutationCtx) {
  const identity = await ctx.auth.getUserIdentity();
  if (!identity) {
    throw new ConvexError("Authentication required");
  }
  return identity;
}

// Secure query pattern
export const getMyProfile = query({
  args: {},
  returns: v.union(v.object({
    _id: v.id("users"),
    name: v.string(),
    email: v.string(),
  }), v.null()),
  handler: async (ctx) => {
    const identity = await requireAuth(ctx);
    
    return await ctx.db
      .query("users")
      .withIndex("by_tokenIdentifier", (q) => 
        q.eq("tokenIdentifier", identity.tokenIdentifier)
      )
      .unique();
  },
});

Function Exposure Check

typescript
// PUBLIC - Exposed to clients (review carefully!)
export const listPublicPosts = query({
  args: {},
  returns: v.array(v.object({ /* ... */ })),
  handler: async (ctx) => {
    // Anyone can call this - intentionally public
    return await ctx.db
      .query("posts")
      .withIndex("by_public", (q) => q.eq("isPublic", true))
      .collect();
  },
});

// INTERNAL - Only callable from other Convex functions
export const _updateUserCredits = internalMutation({
  args: { userId: v.id("users"), amount: v.number() },
  returns: v.null(),
  handler: async (ctx, args) => {
    // This cannot be called directly from clients
    await ctx.db.patch(args.userId, {
      credits: args.amount,
    });
    return null;
  },
});

Argument Validation Check

typescript
// GOOD: Strict validation
export const createPost = mutation({
  args: {
    title: v.string(),
    content: v.string(),
    category: v.union(
      v.literal("tech"),
      v.literal("news"),
      v.literal("other")
    ),
  },
  returns: v.id("posts"),
  handler: async (ctx, args) => {
    const identity = await requireAuth(ctx);
    return await ctx.db.insert("posts", {
      ...args,
      authorId: identity.tokenIdentifier,
    });
  },
});

// BAD: Weak validation
export const createPostUnsafe = mutation({
  args: {
    data: v.any(), // DANGEROUS: Allows any data
  },
  returns: v.id("posts"),
  handler: async (ctx, args) => {
    return await ctx.db.insert("posts", args.data);
  },
});

Row-Level Access Control Check

typescript
// Verify ownership before update
export const updateTask = mutation({
  args: {
    taskId: v.id("tasks"),
    title: v.string(),
  },
  returns: v.null(),
  handler: async (ctx, args) => {
    const identity = await requireAuth(ctx);
    
    const task = await ctx.db.get(args.taskId);
    
    // Check ownership
    if (!task || task.userId !== identity.tokenIdentifier) {
      throw new ConvexError("Not authorized to update this task");
    }
    
    await ctx.db.patch(args.taskId, { title: args.title });
    return null;
  },
});

// Verify ownership before delete
export const deleteTask = mutation({
  args: { taskId: v.id("tasks") },
  returns: v.null(),
  handler: async (ctx, args) => {
    const identity = await requireAuth(ctx);
    
    const task = await ctx.db.get(args.taskId);
    
    if (!task || task.userId !== identity.tokenIdentifier) {
      throw new ConvexError("Not authorized to delete this task");
    }
    
    await ctx.db.delete(args.taskId);
    return null;
  },
});

Environment Variables Check

typescript
// convex/actions.ts
"use node";

import { action } from "./_generated/server";
import { v } from "convex/values";

export const sendEmail = action({
  args: {
    to: v.string(),
    subject: v.string(),
    body: v.string(),
  },
  returns: v.object({ success: v.boolean() }),
  handler: async (ctx, args) => {
    // Access API key from environment
    const apiKey = process.env.RESEND_API_KEY;
    
    if (!apiKey) {
      throw new Error("RESEND_API_KEY not configured");
    }
    
    const response = await fetch("https://api.resend.com/emails", {
      method: "POST",
      headers: {
        "Authorization": `Bearer ${apiKey}`,
        "Content-Type": "application/json",
      },
      body: JSON.stringify({
        from: "noreply@example.com",
        to: args.to,
        subject: args.subject,
        html: args.body,
      }),
    });
    
    return { success: response.ok };
  },
});

Examples

Complete Security Pattern

typescript
// convex/secure.ts
import { query, mutation, internalMutation } from "./_generated/server";
import { v } from "convex/values";
import { ConvexError } from "convex/values";

// Authentication helper
async function getAuthenticatedUser(ctx: QueryCtx | MutationCtx) {
  const identity = await ctx.auth.getUserIdentity();
  if (!identity) {
    throw new ConvexError({
      code: "UNAUTHENTICATED",
      message: "You must be logged in",
    });
  }
  
  const user = await ctx.db
    .query("users")
    .withIndex("by_tokenIdentifier", (q) => 
      q.eq("tokenIdentifier", identity.tokenIdentifier)
    )
    .unique();
    
  if (!user) {
    throw new ConvexError({
      code: "USER_NOT_FOUND",
      message: "User profile not found",
    });
  }
  
  return user;
}

// Check admin role
async function requireAdmin(ctx: QueryCtx | MutationCtx) {
  const user = await getAuthenticatedUser(ctx);
  
  if (user.role !== "admin") {
    throw new ConvexError({
      code: "FORBIDDEN",
      message: "Admin access required",
    });
  }
  
  return user;
}

// Public: List own tasks
export const listMyTasks = query({
  args: {},
  returns: v.array(v.object({
    _id: v.id("tasks"),
    title: v.string(),
    completed: v.boolean(),
  })),
  handler: async (ctx) => {
    const user = await getAuthenticatedUser(ctx);
    
    return await ctx.db
      .query("tasks")
      .withIndex("by_user", (q) => q.eq("userId", user._id))
      .collect();
  },
});

// Admin only: List all users
export const listAllUsers = query({
  args: {},
  returns: v.array(v.object({
    _id: v.id("users"),
    name: v.string(),
    role: v.string(),
  })),
  handler: async (ctx) => {
    await requireAdmin(ctx);
    
    return await ctx.db.query("users").collect();
  },
});

// Internal: Update user role (never exposed)
export const _setUserRole = internalMutation({
  args: {
    userId: v.id("users"),
    role: v.union(v.literal("user"), v.literal("admin")),
  },
  returns: v.null(),
  handler: async (ctx, args) => {
    await ctx.db.patch(args.userId, { role: args.role });
    return null;
  },
});

Best Practices

  • Never run npx convex deploy unless explicitly instructed
  • Never run any git commands unless explicitly instructed
  • Always verify user identity before returning sensitive data
  • Use internal functions for sensitive operations
  • Validate all arguments with strict validators
  • Check ownership before update/delete operations
  • Store API keys in environment variables
  • Review all public functions for security implications

Common Pitfalls

  1. Missing authentication checks - Always verify identity
  2. Exposing internal operations - Use internalMutation/Query
  3. Trusting client-provided IDs - Verify ownership
  4. Using v.any() for arguments - Use specific validators
  5. Hardcoding secrets - Use environment variables

References

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 Convex Security Check AI skill do?

Quick security audit checklist covering authentication, function exposure, argument validation, row-level access control, and environment variable handling

Why use Convex Security Check on TypingMind?

Because you install it once and use it with any model. Convex Security Check 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 Convex Security Check in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/waynesutton/convexskills/tree/main/skills/convex-security-check. 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 Convex Security Check?

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 Convex Security Check?

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

Is the Convex Security Check AI skill free?

Yes. It is published on GitHub by waynesutton under the Apache-2.0 license. 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.

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