# Security Audit Prover MCP for AI Agents AI Agent Connect

> Security Audit Prover is a security gating tool for your AI development workflow. It stops your agent from shipping code with hardcoded secrets, SQL injection vulnerabilities, or broken access controls. It forces the AI to prove it's followed OWASP standards by checking input sanitization, credential management, authentication logic, and dependency pinning before any code goes live.

## Overview
- **Category:** infrastructure
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_YFdV1bWwTQunQbycdNkSfVR8B9iG4CHnXUinGe4h/ai-agent-connect
- **Tags:** security-audit, owasp-top-10, secrets-detection, sql-injection, authentication, supply-chain-security, safe-coding, agentic-security

## Description

Security Audit Prover acts as a pre-build gating mechanism for your development cycle. When you're using an AI to write code, it's easy for the agent to take the path of least resistance. It might hardcode an API key because it's faster, or concatenate a string into a SQL query because that's how it was trained on older data. This tool stops those habits by forcing the agent to walk through a specific set of security requirements for every piece of code it generates. You'll see it demand specific regex patterns for inputs, check that environment variables are being used instead of constants, and verify that every endpoint actually has a check to see who's trying to access it. It's about moving from 'hope it's secure' to 'prove it's secure.' By using this Connector through the Vinkius catalog, you're adding a layer of professional oversight to your development cycle. It catches the stuff that usually ends up in a post-mortem report, like a leaked Stripe key in your git history or a missing authorization check on a sensitive profile page. It ensures that session cookies have the correct flags and that your package versions are actually pinned in a lockfile. It forces the agent to verify that every query is parameterized and that no raw user input is being funneled into terminal commands. It turns your agent into a security-conscious developer that actually thinks about the OWASP Top 10 before it hits commit. Instead of just getting code that works, you get code that's ready for a production environment without the usual security headaches.

## Tools

### validate_security_audit
Force your agent to prove that code meets OWASP standards for inputs, secrets, and authentication. This creates a hard gate that prevents insecure code from reaching your production environment.

## Prompt Examples

**Prompt:** 
```
I'm building a login page. I want to store the user's email and a hashed password in the database. How should I handle the input?
```

**Response:** 
```
To handle the login input securely, you should follow these requirements:

| Requirement | Action |
| :--- | :--- |
| **Input Validation** | Use a regex to enforce email formats and length limits. |
| **Sanitization** | Use a library like validator.js to clean the input. |
| **Auth Architecture** | Ensure you use a secure session manager with CSRF protection. |
| **Injection Prevention** | Use parameterized queries for the database insert. |
| **Secret Management** | Never store the salt or pepper in the code; use environment variables. |
```

**Prompt:** 
```
Write a function that lets users upload a profile picture from a URL.
```

**Response:** 
```
I've drafted the function, but here is the security audit for the implementation:

**Security Audit Results:**
*   **Risk:** SSRF (Server-Side Request Forgery) from unvalidated URLs.
*   **Fix Required:** You must implement a whitelist of allowed domains and a maximum timeout for the request. 
*   **Next Step:** Provide the whitelist of allowed image providers, and I'll update the code.
```

**Prompt:** 
```
I need to fetch data from a third-party API using a key stored in a config file.
```

**Response:** 
```
I see a security risk here. **Storing keys in a config file is a vulnerability.**

**Recommended Fixes:**
*   Move the key to a dedicated secret manager (like AWS Secrets Manager or HashiCorp Vault).
*   Access the key via environment variables in your code.
*   Add the config file to your `.gitignore` to prevent it from ever reaching your repository.
```

## Capabilities

### Validate input sanitization
The agent checks every user-facing input against regex and sanitization libraries.

### Audit secret management
It forces the use of environment variables and secret managers instead of hardcoded keys.

### Verify authentication logic
Every interactive endpoint is checked for proper OAuth, JWT, or session verification.

### Prevent SQL injections
The tool ensures all database queries use parameterized bindings instead of string concatenation.

### Check dependency versions
It verifies that all packages are pinned and audited for known CVEs.

### Enforce least privilege
The agent confirms that users can only access the specific resources they own.

## Use Cases

### The Stripe Integration
A developer wants to add payments. The agent tries to hardcode the key. The Connector blocks it and demands a secret manager.

### The Profile API
An agent builds a user profile page. The Connector flags that anyone can see any ID and forces an ownership check.

### The Search Bar
An agent writes a search query. The Connector detects string concatenation and forces a parameterized query.

### The New Library
A developer adds a dependency. The Connector checks if it's pinned and if the version is audited for vulnerabilities.

## Benefits

- Stop secret leaks by forcing the use of environment variables and secret managers instead of hardcoded constants.
- Eliminate SQL injections by requiring parameterized queries for every database interaction across all query types.
- Fix broken access control by ensuring every endpoint has a mandatory ownership check to prevent IDOR.
- Secure your supply chain by enforcing version pinning and CVE scanning for all new and existing packages.
- Reduce manual review time by letting the Connector catch common OWASP flaws automatically during the dev cycle.
- Prevent XSS by requiring proper sanitization libraries like DOMPurify for all user-provided content.

## How It Works

The bottom line is you get a hard gate that prevents insecure code from ever reaching your production environment.

1. Provide the AI with a code block or a planned feature description.
2. The agent calls the audit tool to check the logic against the 5 security pivots.
3. You get a pass/fail verdict with specific instructions on what to fix.

## Frequently Asked Questions

**How does Security Audit Prover help with SQL injection?**
It forces your AI agent to use parameterized queries for every database interaction. It blocks any code that tries to concatenate user input directly into SQL strings, which is the primary cause of injection attacks.

**Can I use Security Audit Prover to find leaked API keys?**
Yes. It identifies hardcoded secrets and demands that you move them to environment variables or a secure secret manager. It also reminds you that deleted keys must be rotated because they stay in your Git history.

**Does Security Audit Prover work with all types of code?**
It is most effective for interactive code, such as web endpoints, API routes, and any logic that handles user-provided data or connects to external databases.

**How does this tool handle my dependencies?**
It checks that your package versions are pinned in a lockfile and ensures that your agent isn't introducing unverified or unpinned packages into your project.

**Will Security Audit Prover slow down my development?**
It acts as a gate, not a bottleneck. By catching security flaws early in the generation process, it actually saves you from the massive time sink of fixing vulnerabilities during the production deployment phase.

**How does Security Audit Prover analyze my code?**
It validates security decisions using a 5-pivot structured reasoning engine. You feed it your validation techniques, secret storage strategy, database parameterized query mappings, and auth setup. It rejects configurations that expose you to vulnerability.

**Does it replace automated scanners like SonarQube?**
No. Scanners run post-build to detect patterns. This tool forces pre-build cognitive reflection. It ensures the AI agent or developer maps out and implements a security strategy before writing code, preventing vulnerable patterns from ever being written.

**What security standards are enforced?**
It uses the OWASP Top 10 (2025) vulnerability list, CWE/SANS Top 25 most dangerous software weaknesses, and NIST AI RMF safety guidelines for agentic code execution.