Just wrapped up our first full year with Checkmarx (CxSAST) and the internal report is… mixed. We were sold on shifting security left, but the reality of developer adoption has been the biggest blocker. The headline numbers: **5 critical vulnerabilities** that would have been near-impossible to catch in manual review were flagged and fixed. That's a solid win. But only **~20% of our devs** actively use the IDE plugins or regularly check scan results. The rest see it as a noisy gate in the CI/CD pipeline.
The cost angle is interesting. Our initial procurement was based on a rough "per developer" estimate, but with only 20% real usage, the effective cost per *active* user is 5x what we budgeted. That's a brutal metric to bring to finance. We're paying for shelfware for 80% of the team.
Here's where the friction happens:
* **Scan times.** For our larger microservices, a full scan can take 25+ minutes. Devs won't run it locally.
* **Noise-to-signal.** The initial setup flagged thousands of issues. Tuning the query set and creating a manageable "Security Gate" policy (critical/high only for the build break) took months.
* **Remediation guidance.** When it *does* find something, the advice is often generic. The senior devs have to translate it into a framework-specific fix, which adds overhead.
The 5 critical finds were legit—things like hardcoded secrets in legacy code and a nasty SQLi in an obscure endpoint. For those alone, the security team calls it a success. But from a FinOps and engineering efficiency perspective, the ROI is questionable at our current adoption rate.
Has anyone else hit this wall? Specifically:
* What did you do to boost IDE plugin usage beyond mandatory training?
* Did you renegotiate pricing based on actual active users, or find a way to tie costs more directly to usage (like scans run)?
* Are there specific query bundles or customizations that made results more immediately actionable for your devs?
I'm putting together a "renewal mitigation" spreadsheet, and the data on effective cost per user is going to be the main lever. Looking for any real-world numbers or contract adjustments others have achieved.