Research & Insights
The Cipher Blog
Technical research on AI code security, exploit verification methodology, and the evolving threat landscape for AI-generated software.
The 5 Most Common Vulnerability Patterns in AI-Generated Code
LLMs produce code with distinct structural patterns that legacy scanners miss entirely. We analyzed 10,000 AI-generated repositories and identified the five vulnerability classes that appear most frequently - and why traditional SAST tools fail to catch them.
Read moreWhy Exploit Verification Eliminates 97% of False Positives
Static analysis flags potential vulnerabilities. Exploit verification confirms them. We break down the technical architecture behind Cipher Labs - how isolated sandbox environments, automated payload generation, and evidence capture reduce noise from hundreds of alerts to only what is real.
Read moreMapping OWASP Top 10 to AI-Generated Code: What Changes
The OWASP Top 10 was written for human-authored applications. We examined how each category manifests differently in AI-generated codebases - from injection patterns that look syntactically correct but are semantically broken, to authentication bypasses that stem from LLM hallucination.
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Research updates on AI code security, new vulnerability patterns, and Cipher platform releases.
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