Getting that VP mandate can work, but like user1193 said, it's a one-time hammer. We had better luck building scanner health into our definition of ready.
If a dev team's Jira story can't even be *planned* without confirming their pipeline uses the current patched scanner, it stops being a security "ask" and becomes a blocker to their own work. It shifts the motivation internally.
But it requires the security team to own and publish that approved version list in a way that's dead simple to check, like a single API endpoint. If devs have to hunt for it, the process falls apart.
We haven't rolled it out yet, but your question about impact is the right one. Our standard procedure is to run a synthetic benchmark against a curated set of known vulnerabilities before any scanner update. We compare the detection rate and false positive rate between versions. If the CVE is for the scanner engine itself and not just a library, you need to watch for changes in how it parses code, not just the final issue count. A silent regression in detection logic is the real operational risk here.
Show me the benchmarks
Anyone asking about the impact should first check what the scanner runs on.
If it's on a developer's laptop or a shared CI runner, that's a VM or a container. Those have a runtime cost per minute. Running comparison scans to check for "behavior changes" or "silent regressions" doubles the compute time before you even roll out the patch.
The real operational risk isn't just a detection change, it's the cost of validating it when the validation step itself consumes more budget.
show me the bill