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IS CURSOR SAFE?

Cursor is an IDE that integrates AI directly into the coding workflow for code generation, editing, and debugging. While it dramatically boosts productivity, the AI can generate code with subtle security flaws - SQL injection through unsanitized queries, missing CSRF protection, exposed debug endpoints, and dependencies with known CVEs. These issues are easy to miss during rapid AI-assisted development.

72%
No CSP header
74%
No rate limiting
47%
No DMARC
447+
Sites analyzed
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TOP SECURITY RISKS

critical

SQL Injection in AI-Generated Queries

AI code assistants frequently generate raw SQL queries with string concatenation or template literals instead of parameterized queries. This introduces SQL injection vulnerabilities that let attackers read, modify, or delete database contents through crafted input.

high

Missing CSRF Protection

AI-generated form handlers and API routes typically lack CSRF token validation. Attackers can craft malicious pages that trick authenticated users into performing unintended actions like changing account settings or making transactions.

high

Exposed Debug and Development Endpoints

Cursor-generated code often includes debug routes, verbose error pages, and development-only endpoints that leak stack traces, environment variables, or internal application state. These endpoints are frequently left in production deployments.

medium

Outdated Dependencies with Known CVEs

AI models suggest package versions from their training data, which may include libraries with known security vulnerabilities. Without explicit version auditing, projects accumulate dependencies with published CVEs that attackers can exploit.

medium

Insecure Authentication Patterns

AI-generated authentication code may use weak session management, store tokens in localStorage instead of httpOnly cookies, or implement password hashing with outdated algorithms. These subtle flaws compromise user account security.

SECURITY CHECKLIST

Review all AI-generated database queries for SQL injection and switch to parameterized queries
Use prepared statements or an ORM for all database operations instead of raw SQL
Add CSRF token validation to all state-changing form submissions and API endpoints
Remove all debug routes, verbose error handlers, and development endpoints from production
Audit dependencies with npm audit or a similar tool and update packages with known CVEs
Add security headers including CSP, X-Frame-Options, and Strict-Transport-Security
Verify authentication tokens are stored in httpOnly secure cookies, not localStorage
Review AI-generated code for hardcoded secrets or credentials before committing
Add input validation and output encoding to prevent cross-site scripting
Test error handling to ensure stack traces and internal details are not exposed to users
UNPWNED checks all of the above automatically with 700+ security tests.

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FREQUENTLY ASKED QUESTIONS

Does Cursor-generated code have security vulnerabilities?

AI-generated code can contain subtle security flaws like SQL injection, missing CSRF protection, and insecure authentication patterns. These issues are not unique to Cursor - any AI code assistant can produce vulnerable code. UNPWNED scans your deployed application to catch these vulnerabilities regardless of how the code was written.

What are the most common security issues in AI-generated code?

The top issues are SQL injection through string concatenation in queries, missing CSRF tokens, exposed debug endpoints, and outdated dependencies with known CVEs. AI models also tend to use insecure defaults for authentication and session management. UNPWNED checks for all of these patterns and provides specific remediation steps.

How should I review Cursor-generated code for security?

Focus on database queries (ensure parameterized), authentication flows (check token storage and session handling), and API routes (verify authorization checks). Remove any debug endpoints and audit dependencies. Run an UNPWNED scan on your deployed app for automated detection of issues you might miss manually.

Can AI code assistants introduce vulnerabilities that static analysis misses?

Yes, AI-generated code can contain logic-level vulnerabilities like broken access control and business logic flaws that static analyzers struggle to detect. Runtime testing and dynamic scanning catch what static tools miss. UNPWNED performs dynamic analysis on your live application to find vulnerabilities that only appear at runtime.

Can UNPWNED help secure code written with AI assistants?

Absolutely. UNPWNED scans your deployed application for exposed credentials, injection vulnerabilities, missing security headers, authentication flaws, and over 100 other security signals. It works regardless of whether the code was written by hand or generated by AI, giving you a clear prioritized list of what to fix.

Data based on 447+ website scans. Last updated: 2026-04-06. Statistics reflect aggregate findings across all scanned websites, not Cursor exclusively.