AI Security

AI-Generated Code Security Audit

In 3-5 days, we find the vulnerabilities your AI coding assistant introduced. Starting at $1,500 CAD.

What You Get for $1,500

  • Hallucinated dependency scan across npm, PyPI and RubyGems
  • Hardcoded secrets and credential detection (including git history)
  • OWASP Top 10 vulnerability mapping
  • Injection, broken auth and insecure deserialization testing
  • Prioritized findings report with remediation guidance
  • Delivered in 3-5 business days

An AI code security audit identifies vulnerabilities unique to code generated by Copilot, Claude, ChatGPT and similar assistants. Sherlock Forensics tests for hallucinated packages, hardcoded secrets, injection flaws and broken authentication patterns. Quick audits start at $1,500 CAD and deliver in 3-5 business days.

AI code assistants produce code that compiles, passes tests and ships to production. But that code carries a class of vulnerabilities that human-written code rarely exhibits. We find them before attackers do.

From AI Slop to Production-Ready

AI slop, vibe code, AI-assisted development. We audit it all. Every AI code assistant produces the same classes of vulnerabilities. We have seen them across Copilot, Claude, ChatGPT, Cursor, Bolt and Lovable. The name does not matter. The security gaps are the same.

Order a Quick Audit - $1,500 Discuss Custom Scope

The Problem

What AI Code Gets Wrong

01 - Supply Chain

Hallucinated Package Dependencies

AI assistants frequently reference packages that do not exist. Attackers register these phantom package names on npm, PyPI and RubyGems, then wait for developers to install them. A single npm install of a hallucinated dependency can deliver malware directly into your build pipeline. This is not theoretical. Researchers have documented thousands of hallucinated package names from popular AI assistants and confirmed that attackers actively exploit this vector.

02 - Cryptography

Predictable Tokens and Weak Randomness

AI models default to simple implementations. When generating authentication tokens, session identifiers or API keys, they routinely use Math.random() instead of crypto.getRandomValues() or Python's random module instead of secrets. The output looks random to a developer reading the code. It is trivially predictable to an attacker who understands the underlying PRNG.

03 - Injection

SQL Injection and Command Injection

AI assistants generate string-concatenated SQL queries and shell commands with alarming consistency. They produce code that works in development and demonstrates the correct logic but fails to use parameterized queries or proper input sanitization. The resulting injection vectors are invisible to developers who trust the AI output.

04 - Secrets

Hardcoded Secrets and API Keys

AI models trained on public repositories reproduce patterns they learned from training data. This includes embedding placeholder API keys, database credentials and JWT secrets directly in source files. These placeholders frequently survive code review because reviewers assume someone will replace them before deployment. They do not.

05 - Deserialization

Insecure Deserialization

AI-generated code frequently deserializes untrusted input without validation. Python's pickle.loads(), Java's ObjectInputStream and PHP's unserialize() appear in AI output with no type checking or allowlisting. These patterns enable remote code execution when processing attacker-controlled data.

06 - Auth

Broken Authentication Patterns

AI assistants generate authentication flows that look complete but contain critical gaps. Missing rate limiting on login endpoints, JWT tokens without expiration, password reset flows without proper token invalidation and session management that fails to rotate identifiers after privilege changes.

Scope

What We Audit

AI Assistant Common Patterns Risk Level
GitHub Copilot Hallucinated imports, inline secrets, weak crypto High
Claude / Claude Code Overly permissive configs, missing input validation Medium-High
ChatGPT / GPT-4 SQL concatenation, insecure deserialization, placeholder keys High
Cursor / Windsurf / Others Mixed patterns from underlying models Variable

OWASP Top 10 Coverage

Every AI code audit maps findings to the OWASP Top 10 framework. We test for injection, broken authentication, sensitive data exposure, XML external entities, broken access control, security misconfiguration, cross-site scripting, insecure deserialization, vulnerable components and insufficient logging.

Dependency Chain Analysis

We trace every import, require and include statement in AI-generated code against live package registries. Hallucinated packages are flagged. Existing packages are checked against the NIST National Vulnerability Database for known CVEs. Transitive dependencies are mapped and assessed.

Secrets Scanning

Entropy analysis and pattern matching across the entire codebase to identify hardcoded credentials, API keys, tokens and certificates. We check git history for secrets that were committed and later removed but remain accessible in version control.

Pricing

Engagement Options

Quick AI Code Audit - $1,500
Focused review of AI-generated code in a single application or repository. Covers dependency validation, secrets scanning, injection testing and OWASP Top 10 mapping. Delivered in 3-5 business days with a prioritized findings report.
Full Application Security Assessment - Custom
Comprehensive security assessment covering the full application stack. Manual penetration testing, source code review, architecture analysis and remediation guidance. Includes retest to verify fixes. Scoped based on application size and complexity.
Continuous AI Code Monitoring - Monthly
Ongoing security review integrated into your CI/CD pipeline. Every pull request containing AI-generated code is flagged and reviewed. Monthly reporting with trend analysis and developer training recommendations.

Frequently Asked Questions

AI Code Audit FAQs

What is an AI-generated code security audit?
A systematic review of code produced by AI assistants like GitHub Copilot, Claude and ChatGPT. It identifies vulnerabilities unique to AI-written code including hallucinated package dependencies, predictable cryptographic tokens, injection flaws and hardcoded secrets.
Why does AI-generated code need a separate security audit?
AI code assistants produce code that compiles and appears functional but frequently contains security flaws invisible to developers who did not write it. Traditional static analysis tools miss many AI-specific vulnerability patterns like hallucinated dependencies and training-data-derived secrets.
How much does an AI code security audit cost?
Quick audits start at $1,500. Full application assessments are scoped based on codebase size and complexity. View pricing options or contact us for a custom quote.
What is AI slop?
AI slop is the industry term for unreviewed code generated by AI assistants that compiles and runs but contains security vulnerabilities, poor architecture and compounding technical debt. We audit AI slop and transform it into production-ready code. Learn more about AI slop auditing.
Do you audit vibe-coded applications?
Yes. Vibe-coded applications built with tools like Cursor, Bolt and Lovable carry the same vulnerability patterns as any AI-generated code. We audit these applications against OWASP Top 10 standards with particular focus on authentication, authorization and data exposure. See our vibe coding security audit service.
What AI tools do you audit code from?
We audit code generated by GitHub Copilot, Claude, ChatGPT, Cursor, Windsurf, Bolt, Lovable and any other AI code assistant. The underlying vulnerability patterns are consistent across all AI tools. Our methodology is tool-agnostic.
How long does an AI code audit take?
Quick audits deliver in 5 business days. Larger codebases may require 10-15 business days.
Can you audit code I wrote with Claude, Cursor or Copilot?
Yes. We audit code generated by all major AI assistants including Claude, Cursor, Copilot, ChatGPT, Bolt, Lovable and Replit. Not sure if you need a code audit or a full penetration test? Compare your options.

FAQ

Frequently Asked Questions

What is an AI-generated code security audit?
A systematic review of code produced by AI assistants like GitHub Copilot, Claude and ChatGPT. It identifies vulnerabilities unique to AI-written code including hallucinated package dependencies, predictable cryptographic tokens, injection flaws and hardcoded secrets that automated scanners frequently miss.
Why does AI-generated code need a separate security audit?
AI code assistants produce code that compiles and appears functional but frequently contains security flaws invisible to developers who did not write it. These include importing packages that do not exist, using weak randomness for security tokens, embedding API keys in source files and generating SQL queries vulnerable to injection.
How much does an AI code security audit cost?
Quick audits start at $1,500 CAD for small to medium codebases and deliver in 3 to 5 business days. Full application security assessments with manual testing and remediation guidance are scoped based on codebase size and complexity.
Do you audit vibe-coded applications built with Cursor, Bolt or Lovable?
Yes. Vibe-coded applications carry the same vulnerability patterns as any AI-generated code. We audit these applications against OWASP Top 10 standards with particular focus on authentication, authorization and data exposure.
What AI coding tools do you audit code from?
We audit code generated by GitHub Copilot, Claude, ChatGPT, Cursor, Windsurf, Bolt, Lovable, Replit and any other AI code assistant. The underlying vulnerability patterns are consistent across all AI tools and our methodology is tool-agnostic.

By Framework

Framework-Specific Security Audits

AI-generated code inherits framework-specific vulnerabilities. We audit applications built on the most common web frameworks with methodology tailored to each technology stack.

Django Security Audit

ORM injection, template injection, CSRF bypass and misconfigured settings.py in AI-generated Django applications.

Laravel Security Audit

Mass assignment, Eloquent injection, exposed .env files and broken authentication in AI-generated Laravel projects.

Node.js Express Security Audit

Prototype pollution, insecure middleware chains, missing rate limiting and unvalidated input in Express applications.

Next.js Security Audit

Server-side rendering leaks, API route exposure, misconfigured middleware and authentication bypass in Next.js apps.

React Security Audit

XSS through dangerouslySetInnerHTML, exposed API keys, insecure state management and client-side authorization flaws.

WordPress Security Audit

Plugin vulnerabilities, exposed wp-config, XML-RPC abuse, privilege escalation and unpatched core installations.

Authority Resources

Standards and References

Methodology Sources

Related Services

Certifications

Our code review team holds recognized certifications in application security.

CISSP

Related

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Pre-funding security assessments for AI startups covering model APIs, data pipelines and infrastructure hardening.

Free AI Security Guide

A downloadable guide to securing AI systems, covering prompt injection, model security and data pipeline integrity.

Compare

Choose Your Assessment

Feature Quick Audit Standard Comprehensive
Price$1,500$5,000$12,000
External testingYesYesYes
Internal testing--Yes (ShadowTap)
OWASP Top 10BasicFullFull
Social engineering--Yes
Debrief call-30 min60 min
Retest included--Yes (90 days)
Timeline5 days10-15 days15-20 days
Best forMVPs, side projectsProduction appsEnterprise
★★★★★ 4.8 out of 5 based on 17 reviews Leave a Review

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From Our Blog

Related Reading

Audit Your AI Slop Before It Costs You Everything

AI slop ships fast and breaks faster. Unreviewed AI-generated code carries injection flaws, hallucinated dependencies and hardcoded secrets.

What We Found Auditing 50 AI-Built Applications

Aggregate findings from 50 AI code audits. 92% had critical vulnerabilities, 78% stored secrets in plaintext and 54% had SQL injection.

The 2026 AI Code Audit Checklist

The definitive checklist for auditing AI-generated code. What every CTO needs to review before shipping AI output to production.

Scope Your AI Code Audit

We audit single AI-built applications and full engineering teams shipping Copilot-assisted code daily. Every engagement is scoped to match your risk profile.

Call 604.229.1994
Phone
604.229.1994
Burnaby Office
Burnaby, BC, Canada
Coquitlam Office
Coquitlam, BC, Canada
Quick Audit Timeline
3-5 business days from engagement start