Ownership should be shared across application security, platform engineering, and identity governance, with clear accountability for the credentials, scripts, and build paths each team controls. If no one owns the runtime trust boundary, detection becomes fragmented and response slows. The accountable team is the one that can approve, revoke, or isolate the compromised asset.
Why This Matters for Security Teams
When a trusted dependency or script is compromised, the risk is not limited to the code itself. The real impact often comes from the permissions, build paths, deployment automation, and identity bindings that allow the compromised artifact to run. That makes ownership a governance problem as much as a technical one. Security teams need to know who can revoke access, stop execution, rotate secrets, and validate integrity across the delivery path.
This is especially important in environments that rely on CI/CD pipelines, package registries, signed artifacts, and automation accounts. If those controls are split across teams without a defined decision owner, compromise can spread before anyone can isolate it. Current guidance from the NIST Cybersecurity Framework 2.0 supports clear governance, but it does not assign responsibility by itself. Organisations still need explicit ownership for the trust boundary where code, identity, and runtime access meet.
In practice, many security teams discover the ownership gap only after a pipeline token, package dependency, or automation script has already been abused to move laterally or persist in production.
How It Works in Practice
Practical ownership starts by separating the asset from the authority that controls it. A dependency may be maintained by application teams, but if it is introduced through a build system, the platform team often controls the execution environment. If a script uses elevated credentials or service accounts, identity governance must own the approval, rotation, and revocation rules for those credentials. The right owner is the team with the ability to make the fastest effective containment decision.
That usually means defining a response path before compromise occurs. A strong operating model assigns named owners for source repositories, artifact registries, CI/CD runners, secrets stores, and production execution accounts. It also defines what happens when integrity is questioned:
- quarantine the dependency, script, or package version
- revoke or rotate the associated secrets and tokens
- disable the automation account or pipeline runner if needed
- validate build provenance and compare hashes or signatures
- review downstream systems that may have already consumed the compromised asset
Where agentic automation is involved, the same logic applies to non-human identities and tool access. If an AI agent or automated script has standing credentials, the organisation needs a clear owner for both the execution authority and the guardrails that constrain it. The ownership model should also align with incident response, because compromise often crosses team boundaries faster than formal handoffs can keep up. Anthropic’s first AI-orchestrated cyber espionage campaign report is a useful reminder that automation and trusted toolchains can be abused as force multipliers when access is not tightly governed.
These controls tend to break down when ownership is split between development and operations but no single team can actually pause execution, revoke credentials, and confirm downstream blast radius.
Common Variations and Edge Cases
Tighter ownership often increases coordination overhead, requiring organisations to balance faster containment against the reality of shared delivery pipelines. That tradeoff becomes sharper in monorepos, shared runner fleets, and microservices environments where one compromised script may affect many products at once.
There is no universal standard for exactly which team should own every dependency event. Best practice is evolving, but the principle is consistent: the accountable team is the one that can take the decisive control action. In some cases that is application security for code provenance and review policy. In others it is platform engineering for runtime isolation. For secrets and credentials, identity governance or IAM operations may need to own the revoke and rotate process. The important point is that responsibility should match control authority, not organisational convenience.
Edge cases often appear in outsourced development, shared service accounts, or third-party scripts embedded in internal tooling. Those arrangements require especially clear escalation paths, because “everyone is informed” often means “no one is empowered.” For that reason, ownership should be documented in the control map, incident playbook, and access review process, not left in the project charter alone.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 and OWASP Agentic AI Top 10 address the attack and risk surface, while NIST CSF 2.0 and NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST CSF 2.0 | GV.OC-1 | Defines how ownership and responsibilities should be established across security outcomes. |
| NIST AI RMF | AI governance is relevant when automation or agentic tools use trusted scripts and tool access. | |
| OWASP Non-Human Identity Top 10 | Non-human identities often underpin scripts, runners, and build automation that get compromised. | |
| OWASP Agentic AI Top 10 | Agentic systems can misuse trusted tools or scripts if execution authority is not constrained. |
Assign named control owners for each trust boundary, then document who can contain and recover compromised assets.
Related resources from NHI Mgmt Group
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Reviewed and updated by the NHIMG editorial team on August 20, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
