Security Audit Prover MCP for AI. Force your AI agent to validate code security policies.
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Security Audit Prover forces your AI client to check code against OWASP Top 10 standards before deployment. It systematically validates five critical vectors—Input Validation, Secrets Management, Access Control, Injection Prevention, and Dependency Auditing.
Use it when you can't trust the code base and need a non-negotiable security gate.
What your AI can do
Validate security audit
Forces a structured audit of code against OWASP Top 10 standards, checking input validation, secrets storage, auth architecture, injection prevention, and dependency policy.
Checks every user-facing input (headers, query params, body) for proper sanitization, type checking, and format validation.
Scans code and Git history to find hardcoded API keys, tokens, or database passwords that must be moved to environment variables.
Confirms that every user-specific endpoint enforces both authentication (login status) and authorization (ownership/role checks).
Forces the use of parameterized queries for all SQL, NoSQL, and command executions.
Checks that package versions are pinned in lockfiles and that transitive dependencies have been audited against known CVEs.
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Security Audit Prover MCP Server: 1 Tool for Code Validation
This single tool forces systematic security audits across five critical vectors: input validation, secret management, authentication, injection prevention, and dependency auditing.
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Forces a structured audit of code against OWASP Top 10 standards, checking input validation, secrets storage, auth architecture, injection...
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 1 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Dealing with insecure defaults and manual checks shouldn't be part of deployment.
Today, security reviews mean copy-pasting checklists: 'Did they sanitize the input? Yes/No.' You manually check if every API endpoint has an ownership check. Then you run a separate linter just to look for secrets in config files—it’s tedious, slow, and easily skipped when deadlines loom.
With the Security Audit Prover MCP Server, that manual process disappears. Your agent runs all five critical checks simultaneously. It doesn't just tell you 'fail'; it tells you *why* it failed (e.g., CWE-79: Improper Neutralization of Input) and gives you the specific fix needed—like using `DOMPurify.sanitize()`.
Security Audit Prover MCP Server: Enforce secure coding standards.
You stop relying on developers' memory or adherence to best practices. Instead of asking, 'Did you remember to check for IDOR?', the tool runs an automated test against every user-specific resource endpoint, making it impossible to ship code that overlooks ownership checks.
The result is a non-negotiable security gate. When your agent approves the build using `validate_security_audit`, you know the five most exploited vulnerability classes were addressed—period.
What your AI can actually do with this
validate_security_audit: This tool forces your AI client to run a structured audit of your code base against OWASP Top 10 standards before you ever deploy it. You use this when you need a non-negotiable security gate that systematically validates five critical vectors: input handling, credential storage, access boundaries, injection prevention, and dependency integrity.
When the agent runs validate_security_audit, it first tackles data coming into your system. It checks every single user-facing input—that means headers, query parameters, and request bodies—to confirm proper sanitization, type checking, and format validation across all sources. If any external input could be hostile or unsanitized, the process fails immediately.
Next, it hunts down exposed credentials. The tool scans your code files and even checks Git history to locate hardcoded API keys, tokens, or database passwords. You'll find that these secrets must be moved out of constants and into secure environment variables for proper handling.
It then verifies access boundaries by confirming that every single user-specific endpoint enforces two things: first, authentication—proving who the user is; second, authorization—making sure that person has the ownership or role required to view that data. The system flags common IDOR (Insecure Direct Object Reference) issues right out of the gate.
For database safety, it prevents injection attacks by forcing parameterized queries for all SQL, NoSQL, and command executions. You can't use raw concatenated strings; every query must utilize binding placeholders to guarantee separation between commands and data. This applies whether you’re dealing with a relational database or executing system commands.
Lastly, the process audits dependency integrity. It checks that your package versions are properly pinned in lockfiles and that any transitive dependencies—the packages your packages rely on—have been audited against known CVEs. This keeps your supply chain solid and catches risks like Log4Shell before they ever hit production.
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Here's how it actually works
The bottom line is: it gives you an objective, technical report on security flaws that human reviewers often miss.
You activate the Security Audit Prover tool, feeding it your current code component or module.
The agent runs five distinct checks: input sanitization, secret scanning, access control mapping, injection parameterization, and dependency vetting. It analyzes the implementation against known secure coding patterns.
It returns a structured verdict (e.g., SECURITY_PROVEN or SECRETS_EXPOSED), detailing exactly which of the five vectors failed and providing concrete remediation steps.
Who is this actually for?
This is for the developer who gets tired of deploying code and finding a critical vulnerability in production. It's for the architect needing proof of secure design patterns, or the compliance officer who can’t wait for manual penetration testing. If you ship code frequently, use this.
Uses it to validate that every API endpoint uses parameterized queries and enforces ownership checks (IDOR prevention).
Runs the audit as a mandatory pre-commit or CI/CD gate, ensuring no secrets are committed and all dependencies are pinned.
Verifies that new services adhere to least-privilege principles across authentication and authorization boundaries.
What Changes When You Connect
Stops hardcoded secrets from reaching Git. The tool immediately flags credentials found in source code, forcing developers to move them to AWS Secrets Manager or Vault.
Eliminates injection risks by checking for parameterized queries. It forces the use of $1 bindings instead of raw string concatenation when building SQL or OS commands.
Stops broken access control (IDOR). The audit mandates that every resource-accessing endpoint checks not just if a user is logged in, but if they own the specific resource ID.
Prevents supply chain attacks. By requiring pinned versions and lockfile commits, it forces developers to account for transitive dependency risks.
Ensures all input is treated as hostile. It mandates validation on every external source—from request body text to file MIME types—before processing.
See it in action
The 'Oops, I committed a key' scenario
A developer accidentally commits an API key in a comment. Instead of waiting for GitHub’s slow scanner, the agent runs validate_security_audit. The tool immediately detects the secret pattern and forces the dev to rotate the key before merging.
The 'IDOR' bug hunt
A new microservice endpoint is built for viewing user profiles. It passes authentication but fails authorization checks (User A can view User B's data). The agent runs validate_security_audit, which flags the lack of ownership check, requiring an explicit if (req.user.id !== req.params.userId) block.
Building a complex data pipeline
The team needs to run queries across SQL and NoSQL databases using user-provided search terms. Running the audit forces them away from string concatenation, demanding the use of safe, parameterized query builders for both database types.
Updating a third-party package
A developer upgrades an NPM dependency without checking its transitive dependencies. The agent runs validate_security_audit, which forces them to audit the entire dependency tree and verify that all new packages are properly pinned in the lockfile.
The honest tradeoffs
Assuming the framework handles it
Writing a comment like, 'The ORM layer takes care of sanitization' or using vague phrases that skip validation steps.
Don't rely on assumption. The validate_security_audit tool forces specific actions: use parameterized queries explicitly (e.g., db.query("$1", [input])) and show the sanitizer function call (e.g., DOMPurify.sanitize(input)).
Fixing the key, forgetting history
A developer finds a secret in code, deletes it, commits 'Fixed!', and assumes the problem is gone.
The tool reminds you: deleting it from the latest commit isn't enough. You must rotate the credential and check git log to ensure no history contains the plaintext key.
Using generic validation
Implementing input checks with simple regex that only validate length but ignore type or format constraints.
The tool demands specific strategies: for file uploads, you must specify a MIME whitelist and a virus scan. For paths, restrict them to an expected subdirectory pattern.
When It Fits, When It Doesn't
Use this if your primary goal is risk mitigation and compliance validation—you need proof that the code resists common attacks (XSS, SQLi, IDOR). This tool works best when integrated into a mandatory CI/CD gate. Don't use it if you just need to check for general performance bottlenecks or basic business logic correctness; those require functional testing tools. If your only concern is whether the user flow meets spec, skip this one. But if the code talks to a database or accepts external input, run validate_security_audit first.
Questions you might have
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.
How does using `Security Audit Prover` enforce authorization beyond basic authentication? +
It mandates explicit ownership checks for every resource endpoint. The tool specifically detects IDOR (Insecure Direct Object Reference) vulnerabilities by verifying that the authenticated user owns or has permission to access the requested resource ID. It forces you to implement role-based and attribute-based access control logic.
If I accidentally commit a secret, can `Security Audit Prover` help me clean up my Git history? +
The tool alerts developers that removing secrets from the latest commit is insufficient. It emphasizes that committed credentials remain in Git history forever, forcing you to rotate the key immediately and implement pre-commit hooks (like gitleaks) for prevention.
What types of input validation does `validate_security_audit` enforce besides basic regex checks? +
It requires comprehensive sanitization beyond simple pattern matching. You must prove type and length checking, MIME whitelisting for file uploads, and validate that user input is sanitized using libraries like DOMPurify before storage or rendering.
Does `Security Audit Prover` cover transitive dependencies or just pinned versions in package.json? +
It mandates auditing the entire dependency graph, not just direct pins. You must commit lockfiles and run automated scans (like npm audit) to check for vulnerabilities introduced by transitive packages, ensuring provenance verification across all layers.
How does `Security Audit Prover` handle injection prevention when using multiple query types? +
It requires that you use parameterized queries exclusively for every type: SQL, NoSQL, LDAP, and even template engines. It flags any instance where user input is concatenated directly into a query string or command array.
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