Introducing Semgrep Agentic Workflows: Automate Deep Vulnerability Hunting at Scale

Semgrep has launched nine pre-built Agentic Workflows, currently in public beta, to enhance application security by quickly detecting complex flaws such as authentication, injection, and business logic errors. These workflows utilize the Semgrep Pro Engine, AI models like Claude Opus, and Semgrep Mandoline, a code slicer, to perform deterministic analysis and reasoning about exploitability, effectively automating the identification of vulnerabilities at a speed and scale beyond traditional methods. Designed to counter the advanced capabilities that attackers now possess, these workflows enable continuous security monitoring of codebases, offering AppSec teams a robust tool to match the increasing pace of AI-generated code reviews. Initial testing with design partners showed high accuracy in detecting true positives, aligning closely with internal review results, and the platform supports both out-of-the-box use and further customization with a Python SDK and CLI. As Semgrep continues to develop this technology, future enhancements will focus on triage, remediation, and proactive security measures to further strengthen AppSec processes.

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