Introducing Semgrep Custom Workflows

AI is proving capable of identifying code security vulnerabilities, such as business logic flaws and broken access control, that traditional tools often miss, though integrating AI into production introduces challenges like variable costs, inconsistent outputs, and lack of auditability. While AI can manage complex tasks that deterministic tools struggle with, such as reasoning about code context and evaluating business logic, it remains expensive and difficult to audit. Semgrep addresses these challenges by providing a programmable platform called Custom Workflows, which combines the strengths of deterministic analysis and AI in pipelines that are testable, auditable, and scalable. This approach allows for the creation of tailored workflows that can handle detection, triage, validation, and remediation across entire repository fleets without requiring teams to build and maintain extensive infrastructure. Custom Workflows, currently in private beta, utilize Semgrep's infrastructure to enable teams to define security processes in Python, ensuring reproducibility, observability, and cost management while maintaining human oversight in security policy and exception handling.

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