Both. Secrets scanning is an AppSec control because it finds leaks in code and pipelines, but it is also an identity control because the artifact being exposed is a credential. Organisations get better outcomes when they tie scanning to ownership, rotation, and revocation workflows instead of treating it as a standalone developer tool.
Why This Matters for Security Teams
secrets scanning should not be treated as a narrow code hygiene task. When a token, API key, certificate, or private credential is exposed, the issue is not only that source code may be leaked. The larger risk is that an identity has escaped into places where it can be copied, reused, or abused without oversight. That makes secrets scanning relevant to both AppSec and IAM governance, especially where non-human identities are created and consumed at speed.
Security teams often miss this boundary because the first alert arrives in a repository, while the real exposure sits in access control, rotation, and revocation processes. A scan that finds a secret but does not trigger ownership and invalidation still leaves an active path to compromise. This is why the control needs to connect to the governance model described in the NIST Cybersecurity Framework 2.0, not just the developer workflow.
In practice, many security teams encounter credential abuse only after the exposed secret has already been used, rather than through intentional detection and containment.
How It Works in Practice
Operationally, secrets scanning works best as a feedback loop across source control, build systems, artifact stores, and runtime telemetry. AppSec teams usually own the detection mechanics: pattern matching, entropy checks, allowlisting for known test values, and integration into pull requests and CI pipelines. IAM or identity governance teams should own what happens next: confirming the secret’s owner, determining whether it is human or non-human, and enforcing rotation or revocation before the exposure becomes an incident.
That split matters because the exposed object is often a credential for an application, service account, bot, or cloud workload. The OWASP Non-Human Identity Top 10 is useful here because it frames leaked or overprivileged machine identities as a governance issue, not just a coding defect. NIST control language also supports this mapping: NIST SP 800-53 Rev 5 Security and Privacy Controls helps teams anchor detection, access enforcement, and response into repeatable control ownership.
- Detect secrets in code, build logs, tickets, and packaged artifacts.
- Classify each finding by credential type, system owner, and privilege scope.
- Revoke or rotate the exposed secret before remediation is marked complete.
- Record the event in IAM, SOC, or GRC workflows so recurring exposure is measurable.
- Apply exception handling for deliberate test values, but keep approvals explicit and time bound.
In mature programmes, the scan result becomes an identity event: who owns the credential, what it can access, where it was used, and whether the service can continue operating after rotation. These controls tend to break down when secrets are embedded in legacy scripts, shared by multiple services, or hard-coded into deployed binaries because ownership and rotation cannot be executed cleanly.
Common Variations and Edge Cases
Tighter secrets governance often increases operational overhead, requiring organisations to balance faster developer delivery against stronger credential control. That tradeoff is real in environments with frequent build changes, ephemeral workloads, or large numbers of service-to-service connections.
Best practice is evolving for ephemeral and short-lived credentials. Some teams assume short TTLs remove the need for scanning, but that is only partly true. Even temporary credentials can be abused during their valid window, and their presence in repositories or logs still creates a chain of exposure. In AI and automation-heavy environments, the problem becomes more complex because agents and pipelines may request, store, or forward secrets without clear human ownership. That is where identity governance and AppSec must operate together.
There is no universal standard for this yet, but a practical rule is simple: if a finding can be used to authenticate, it needs identity treatment; if the finding exists because of code or pipeline exposure, it also needs AppSec treatment. Security teams should be cautious with shared service accounts, third-party integrations, and secrets embedded in container images, because the cleanest scanning result does not guarantee the cleanest runtime exposure. The most reliable approach is to connect scanning to detection, ownership, rotation, and retirement workflows, then review the pattern through the lens of OWASP Non-Human Identity Top 10 and the control structure of NIST Cybersecurity Framework 2.0.
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 address the attack and risk surface, while NIST CSF 2.0 and NIST SP 800-53 Rev 5 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST CSF 2.0 | PR.AC-1 | Secrets exposure is an access-control issue because credentials grant entry. |
| OWASP Non-Human Identity Top 10 | Leaked machine credentials are a core non-human identity governance problem. | |
| NIST SP 800-53 Rev 5 | IA-5 | Authenticator management directly covers secret issuance, storage, and rotation. |
Treat exposed secrets as NHI lifecycle events requiring ownership, rotation, and retirement.
