Static analysis findings should be measured against the code and scan context in which they appear, because they can open and close repeatedly as code changes. SCA findings need dependency-lifecycle logic, because the first-found date can reset when a vulnerable library is removed and later re-added. One rule does not fit both.
Why MTTR Has to Reflect the Finding Type
Teams should not treat MTTR as a single clock that starts at first detection and ends at closure for every issue class. static analysis findings and SCA findings behave differently over time, so the measurement rule has to match the lifecycle of the weakness. Otherwise the same report will mix together code-state defects and dependency-state defects in a way that hides real response performance.
static analysis findings are tied to a specific code snapshot, so the meaningful question is how quickly the team corrected the code path that produced the issue. SCA findings are tied to a dependency version and its presence in the software bill of materials, so the meaningful question is how quickly the team removed or replaced the vulnerable component after it was introduced or reintroduced.
The practical result is that MTTR should be anchored to the object being remediated, not just to the scanner result. That lets teams compare like with like and avoids rewarding a process that simply suppresses alerts without actually fixing the underlying condition.
What Changes for Static Analysis Versus SCA
Static analysis findings can open, close, and reopen as the codebase changes. A developer may fix the flaw in one branch, reintroduce a similar pattern later, or move the vulnerable logic into a different file or function. The clock therefore needs to track the finding instance in its code context, because the same logical defect may recur across commits.
SCA findings behave more like dependency exposure events. If a vulnerable library is removed, the original exposure can be considered remediated. But if that same library is later re-added, the finding is not a continuation of the old state, it is a new exposure event against the current dependency graph. That is why first-found date logic must reflect the dependency lifecycle rather than the first time the library ever appeared in the repository.
For Financial Services Identity Security Guide, lifecycle-aware measurement is especially important in regulated environments where remediation evidence has to match the control state that existed at the time of review. The same principle applies here: measure the state that is actually exposed now, not a historical state that no longer describes the software.
How to Build a Fair MTTR Rule for Both
Teams usually need two slightly different measurement definitions rather than one blended KPI. For static analysis, measure from detection to the commit or release that removes the code pattern from the affected code path. For SCA, measure from detection to the release or dependency update that eliminates the vulnerable package, with a reset when the package is removed and later reintroduced.
This distinction becomes more reliable when the team records the finding identity, the affected artifact, and the remediation event type. Static analysis should be linked to file, rule, branch, and commit context. SCA should be linked to package name, version, transitive path, and the dependency graph at the time of detection. Without that metadata, teams end up comparing an open code defect to a removed-and-readded library as if they were the same kind of work.
Authoritative control guidance also supports separating detection and remediation logic from the measurement itself. NIST SP 800-53 Rev 5 Security and Privacy Controls reinforces the need for integrity, configuration management, and auditability around changes, while OWASP API Security Top 10 is a useful reminder that different security defects demand different measurement lenses depending on the object being protected.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
NIST SP 800-53 Rev 5, OWASP ASVS and SLSA set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST SP 800-53 Rev 5 | CM-2 — Baseline Configuration | Finding MTTR depends on tracking code and dependency state changes over time. |
| CM-3 — Configuration Change Control | Static analysis findings reopen when code changes reintroduce the flaw. | |
| SI-2 — Flaw Remediation | MTTR is a remediation measure for software flaws and vulnerable dependencies. | |
| Recommendation — Track remediation against the current configuration baseline before closing findings. Tie closure to approved code changes that remove the vulnerable condition. Measure and manage the time to remediate discovered software flaws. | ||
| OWASP ASVS | V15 — Secure Coding and Architecture | Static analysis findings are code-level defects that map to secure coding discipline. |
| Recommendation — Measure how quickly code defects are removed from the affected code path. | ||
| SLSA | Supply chain integrity | SCA findings are dependency provenance and artifact integrity problems. |
| Recommendation — Use dependency provenance and rebuild controls to reduce reintroduced vulnerable packages. | ||
Practitioner Guidance
What to prioritise: Define separate MTTR rules for code findings and dependency findings before you trend the metric. If you use one timer for both, your averages will be operationally neat but analytically misleading.
What to verify: Confirm that your SCA workflow resets the “age” of a vulnerability when a package is reintroduced after removal, and that your static analysis workflow does not carry an old fix date forward after the vulnerable code pattern reappears in a later change.
Common mistake: Do not use scanner first-seen timestamps as the sole measure of remediation speed. That approach overstates delay for recurring code issues and understates delay when dependency exposure is reintroduced after a clean period.
Practitioner takeaway: The best MTTR metric is the one that matches the lifecycle of the asset being fixed, because code defects and dependency exposures fail, recur, and resolve on different clocks.
Related resources from NHI Mgmt Group
- What do teams get wrong about automated code remediation from static analysis findings?
- How should security teams adopt static analysis without overwhelming developers with noisy findings?
- How should security teams measure whether static analysis rules are actually worth enforcing in developer workflows?
- How should security teams prioritise NHI remediation in cloud environments?