I am currently leading a vendor evaluation process for a static application security testing (SAST) solution to be integrated into our CI/CD pipelines across multiple development teams. Semgrep is a prominent contender in this space, primarily due to its advertised speed, ease of rule creation, and its open-source core. However, the primary metric that will determine operational success and developer adoption in our environment is the signal-to-noise ratio, specifically the real-world false-positive rate in a continuous integration context.
The marketing materials and high-level technical documentation consistently emphasize precision, but I have learned to treat such claims with a high degree of skepticism. False positives in CI are not merely an annoyance; they lead to alert fatigue, erode developer trust in the security program, and ultimately cause critical findings to be ignored. My procurement analysis must be grounded in operational reality, not ideal-case scenarios.
Therefore, I am seeking detailed, empirical feedback from teams that have implemented Semgrep in a live CI environment. I am particularly interested in data points and experiences that go beyond isolated, curated examples.
* **What is your observed false-positive rate,** quantified if possible (e.g., percentage of findings dismissed as benign, or raw numbers per scan)? Does this rate vary significantly between the default Semgrep Registry rules and any custom rules you have developed?
* **How does the rate differ by language?** Our stack includes Go, Python, and JavaScript/TypeScript. Performance parity is not a given.
* **What is your workflow for triage and suppression?** Have you found the rule precision and path-scoping features (like `paths:` and `taint-mode`) effective enough to keep suppressions manageable, or do you maintain a large, ever-growing suppression file?
* **Impact on pipeline duration:** While speed is a stated advantage, have you found the need to implement complex post-processing or filtering scripts that negate these gains?
* **Comparative context:** If you have experience with other SAST tools (e.g., SonarQube, Checkmarx, CodeQL) in CI, how does Semgrep's operational precision compare from an engineering workflow perspective?
Our evaluation will include a proof-of-concept, but anecdotal evidence from sustained production use is invaluable for framing our test criteria and success metrics. I am less interested in "it works well" and more in the concrete, gritty details of maintenance overhead and unexpected challenges you've encountered.