Accountability should sit with the teams that own the connected systems, the IAM or security operations function that governs non-human identities, and the risk owners approving external integrations. Each connection needs a clear owner, a review cycle, and a revocation path. Shared ownership without explicit control boundaries usually results in weak enforcement and delayed remediation.
Why This Matters for Security Teams
Insecure app-to-app connections turn a single integration into a shared attack surface. When service accounts, API keys, OAuth grants, or other secrets are reused across teams, accountability becomes blurred and revocation slows down. That is exactly why the OWASP Non-Human Identity Top 10 treats non-human identity exposure as a first-class control problem, not just an engineering hygiene issue.
The practical risk is supply chain spread. A compromised connector can expose downstream systems, impersonate trusted automation, or persist long after the original owner assumes the integration is dormant. NHIMG’s 52 NHI Breaches Analysis shows how often non-human credentials become the hidden path from one system to many. When app-to-app trust is not explicitly owned, the breach response is usually fragmented and slow.
Security teams should treat each connection like a production asset with an accountable owner, a defined purpose, and a removal path. The important question is not whether the connection exists, but who can approve, rotate, and kill it when the risk changes. In practice, many security teams encounter failed accountability only after an exposed secret or abused integration has already moved laterally into sensitive systems.
How It Works in Practice
Accountability for insecure app-to-app connections should be assigned across three layers: the system owner, the IAM or security function that governs non-human identities, and the business or risk owner who accepted the integration. That shared model only works if each party has a distinct decision right. The system owner is responsible for the technical implementation, the IAM team enforces credential policy and lifecycle controls, and the risk owner approves the trust relationship and business exception.
In practice, that means every machine-to-machine relationship should be inventoried as a discrete non-human identity, not buried in source code, ticket comments, or tribal knowledge. Controls should include named ownership, purpose limitation, renewal dates, and a revocation workflow that is tested before an incident. Current guidance from NIST SP 800-53 Rev. 5 Security and Privacy Controls reinforces the need for access governance, but it does not remove the need for local accountability design.
For app-to-app flows, the cleanest operating model is to tie identity to workload, not to a person or a vague team alias. That aligns with the NHI guidance in The State of Secrets in AppSec, especially where secret sprawl and delayed remediation make ownership gaps visible only after exposure. Controls should also require secrets rotation, scoped permissions, and logging that shows which service called which API, under which identity, and with what approval context. These controls tend to break down in fast-moving CI/CD environments because ephemeral builds and ad hoc integrations outpace manual review.
Common Variations and Edge Cases
Tighter ownership often increases administrative overhead, requiring organisations to balance clearer accountability against the speed of platform teams and developers. That tradeoff becomes harder in shared service platforms, partner integrations, and vendor-managed APIs where multiple groups legitimately touch the same connection.
There is no universal standard for this yet, but current guidance suggests treating the risk owner as the final approver while the technical owner remains responsible for implementation and revocation. For external SaaS or B2B integrations, that may mean the procurement, vendor risk, and application teams all have partial responsibility, but only one group should own the live credential and its expiration. In the agentic and automation space, this matters even more because autonomous tools can chain permissions in ways humans do not anticipate, a theme also reflected in the Anthropic report on AI-orchestrated cyber espionage.
Edge cases usually appear when the integration is embedded in code owned by one team but the secrets are managed elsewhere, or when a partner insists on shared credentials for convenience. NHIMG’s Klue OAuth Supply Chain Breach illustrates why shared trust without explicit revocation control creates exposure at scale. The rule should be simple: if no one can confidently answer who can disable the connection today, accountability is already failing.
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, NIST SP 800-63, NIST AI RMF and NIST Zero Trust (SP 800-207) set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-01 | Addresses non-human identity ownership and lifecycle gaps in app-to-app connections. |
| NIST CSF 2.0 | PR.AC-1 | Access control governance depends on clear accountability for connected systems. |
| NIST SP 800-63 | Digital identity assurance informs how machine identities are established and validated. | |
| NIST AI RMF | GOVERN | Autonomous or automated connections need governance and accountability for risk decisions. |
| NIST Zero Trust (SP 800-207) | RA | Zero trust requires continuous verification of each connection rather than implicit trust. |
Assign each integration a named NHI owner and enforce documented lifecycle controls from issue to revocation.
Related resources from NHI Mgmt Group
- Who is accountable when AI supply chain exposure leaks customer data or source code?
- Who is accountable when a supply chain worm uses stolen tokens to create infrastructure?
- Who is accountable when a third party breach leads to internal data exposure and potential supply chain risk?
- Who is accountable for cleaning up and validating exposure after a software supply chain package compromise?
