audit-code

Detecting hardcoded API keys and dangerous code patterns involves recursively scanning source repositories to identify risky calls, unsafe deserialization, and credential strings across Python, JavaScript, and shell files.

Finding SQL injection risks during a pull request security review involves applying pattern-based detection to source files to surface SQL string interpolation and unsafe execution patterns. This generates severity-ranked reports with file locations and remediation guidance.

Yes, you can check repository hygiene for committed environment files and supply-chain risks. The process scans for suspicious exfiltration patterns, package-supply risks, and overly permissive sensitive files to ensure no obvious security regressions exist.

Yes, source code security auditing works with Python, JavaScript, shell, infrastructure, and configuration files. It applies pattern-based detection to identify hardcoded secrets, injection risks, and file permission issues across these formats during periodic audits.

Reviewing AI-generated code for security regressions before a commit requires running a source scan to detect unsafe execution patterns, exfiltration risks, and hardcoded passwords. This yields structured severity-ranked reporting with specific file locations and remediation steps.