GitHub Secret Scanning vs Semgrep Code

GitHub Secret Scanning detects exposed credentials so they can be secured before exploitation. It scans every branch in Git history, plus issue and pull request content, discussions, wikis, and secret gists. Detected leaks produce repository alerts with details about the credential, while push protection can block secrets before they enter code. Organizations can define regular expressions for their own secret formats. Generic patterns cover items such as private keys, connection strings, and API keys, and AI detection can identify unstructured secrets such as passwords. Validity checks may contact issuing services to see whether credentials remain active. GitHub can work with providers to validate findings and notify them for actions such as revocation. Scanning is automatic and free for public repositories. Private and internal organization repositories require Secret Protection on GitHub Team or Enterprise Cloud; Enterprise Server supports user-owned repositories with that protection. It is available through API, web, and self-hosted deployment, with hybrid deployment.

Semgrep Code is a cloud-based static application security testing product for finding vulnerabilities in source code and helping developers address them. It combines deterministic analysis for issues such as XSS and SQL injection with AI analysis aimed at complex flaws, including IDOR and business logic vulnerabilities. Pull requests can carry tailored, step-by-step remediation instructions, and the product supports 35 programming languages. Semgrep lists integrations with GitHub, GitLab, Bitbucket, Jenkins, CircleCI, Azure and Buildkite, plus VS Code and IntelliJ extensions and Slack, email and webhook notifications. The Free Edition includes Code and Supply Chain, with scanning for up to 10 repositories and a limit of 10 contributors. Teams supports up to 500 private repositories; Enterprise has no repository or contributor limit. For local or fully CI-based scans, code stays on the user's computer or CI environment; opting into AI processing sends part of a file containing a finding to a model. The Free Edition costs nothing. Teams — Code is listed at $30 a month.