Git blame identifies the last person to edit a line, not the person responsible for fixing the underlying vulnerability. That breaks triage when the last change was cosmetic, when ownership has shifted, or when the original author has left. AppSec teams need active maintainer context and code lineage, otherwise findings are routed to people who cannot action them quickly.
Why This Matters for Security Teams
Git blame is useful for debugging history, but it is a poor proxy for operational ownership. Security teams that use it as the primary routing signal often misassign remediation to whoever touched a line last, rather than the maintainer who understands the component, release path, and downstream impact. That matters most when findings must be triaged quickly across product, platform, and shared libraries.
The risk is not just slower remediation. Misrouted issues can create alert fatigue, weaken accountability, and make vulnerability management look noisier than it is. A mature process should align code findings with current maintainers, repository stewardship, and service ownership, then use Git history only as supporting context. The NIST Cybersecurity Framework 2.0 places clear emphasis on governance and ownership, which is the right lens here.
In practice, many security teams encounter ownership failures only after a high-severity finding is routed to someone who no longer works on the code, rather than through intentional code stewardship.
How It Works in Practice
Git blame shows the last commit associated with each line, which can help reconstruct change history, but it does not answer who can actually fix the issue today. Security teams need a broader ownership model that combines repository metadata, service catalogs, on-call or team mappings, and release responsibility. Current guidance suggests treating blame as a starting point for investigation, not an authoritative ownership system.
A more reliable workflow usually looks like this:
- Use code scanning or SAST findings to identify the affected file, function, or dependency.
- Map the repository or service to its current maintainer group through an internal catalog or ownership register.
- Check whether the vulnerable code sits in shared infrastructure, generated code, vendored code, or a third-party library.
- Route the issue to the team that can patch, test, and release it, not simply the last editor.
- Preserve Git blame as evidence for lineage, but verify ownership with live operational data.
This distinction becomes important in monorepos, platform engineering environments, and fast-moving product teams where responsibilities shift frequently. It also matters for agentic workflows where automation may open pull requests, because the last commit author may be a bot or a temporary integrator rather than the real code steward. For broader secure development expectations, the OWASP Top 10 for LLM Applications and MITRE ATT&CK are useful references for thinking about how findings and adversary behaviors should be mapped to control owners and defenders.
These controls tend to break down when ownership data is stale, because the repository history is accurate but the organisational reality has already changed.
Common Variations and Edge Cases
Tighter ownership routing often increases process overhead, requiring organisations to balance speed against accuracy. That tradeoff is real, especially in large codebases where a single service may have dozens of contributors over time.
There is no universal standard for this yet, but best practice is evolving toward layered ownership signals. Some teams use CODEOWNERS files, service catalogs, or dependency graphs to identify maintainers. Others add escalation rules for retired engineers, contractors, or merged teams. In regulated environments, that extra context helps demonstrate traceability without pretending that commit history equals accountability.
Edge cases are common. Generated code may have no meaningful human owner. Forked repositories may preserve authorship information that is no longer operationally relevant. Shared libraries can be maintained by a central platform team while consumed by many application teams, so blame points to the wrong place even when the technical history is correct. For identity-heavy systems and NHI-related repositories, the same issue appears when automation, service accounts, or CI pipelines make changes: the actor in Git is not always the accountable system owner.
The practical rule is simple: use Git blame to understand who changed the code, then use current ownership records to decide who should fix it. When those two disagree, current maintainership should win.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Agentic AI Top 10 and MITRE ATLAS address the attack and risk surface, while NIST CSF 2.0, NIST AI RMF and NIST AI 600-1 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST CSF 2.0 | GV.RM | Ownership routing is a governance and risk management issue, not just a developer lookup problem. |
| NIST AI RMF | GOVERN | Automated code analysis and agentic workflows need clear accountability and traceability. |
| OWASP Agentic AI Top 10 | Agent-written or bot-authored changes make last-editor signals unreliable for ownership. | |
| NIST AI 600-1 | GenAI-assisted development increases the need for provenance and output validation. | |
| MITRE ATLAS | Adversarial manipulation of AI-assisted pipelines can obscure true change responsibility. |
Assign remediation based on current accountability and risk ownership, then keep lineage as supporting evidence.
Related resources from NHI Mgmt Group
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on August 19, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
