AI Source Code
Security Review

Traditional SAST tools rely on pattern matching and produce many false positives. Our AI engine understands code semantics, traces data flows across files, recognizes sanitization patterns, and validates findings against real execution paths. This results in near-zero false positives and findings that developers can trust.

We support 30+ languages including Python, Java, JavaScript/TypeScript, Go, C#, PHP, Ruby, Solidity, Rust, and more. Our AI is also framework-aware, with specific rules for popular frameworks like React, Django, Spring Boot, Express, and others.

Our AI validates every finding by tracing data flows, understanding authentication context, and checking for proper sanitization. We don't just flag potential issues-we verify that they represent real security risks in your specific code context.

Yes! We provide native integrations for GitHub Actions, GitLab CI, Jenkins, CircleCI, and generic webhook support. You can run automated security reviews on every commit, pull request, or scheduled intervals.

Yes. Our AI goes beyond syntax-level vulnerabilities to identify business logic flaws like broken authentication flows, authorization bypasses, improper state transitions, and race conditions that traditional tools miss.

Most repositories complete in under 5 minutes, even for large codebases with millions of lines of code. Our AI processes code in parallel and focuses on high-risk areas first.