AI coding assistants like GitHub Copilot, Cursor, and Claude Dev have accelerated software development speeds dramatically. However, LLMs generate code based on statistical patterns found in open-source repositories—which frequently contain legacy security anti-patterns, outdated libraries, and vulnerable code structures.
Common Security Flaws Found in AI-Generated Code
- Raw SQL String Concatenation: AI suggestions frequently output unparameterized SQL queries, re-introducing SQL Injection into modern stacks.
- Hardcoded API Keys & Secrets: AI assistants often insert placeholder API keys or hardcoded JWT secret strings into committed code files.
- Weak Cryptographic Defaults: Code suggestions commonly recommend outdated algorithms like MD5, SHA1, or ECB mode AES cipher suites.
At SA Infotech, our custom code review and VAPT services ensure that fast-paced AI-assisted development ("Vibe Coding") doesn't compromise your application's security posture. Contact us to audit your codebase today.