The tendency for adversaries or users to bypass formal restrictions by switching to alternative tools, services, or channels. In security governance, it means a policy can appear effective while real-world use migrates to unmanaged paths that are harder to see and control.
Expanded Definition
Route-around behaviour describes the practical gap between a written control and how people or adversaries actually work around it. In security programs, it often appears when a restriction is technically valid but operationally inconvenient, prompting activity to shift into shadow IT, unapproved messaging apps, personal storage, or other unmanaged channels. The term is especially relevant in identity governance, cloud security, and agentic AI environments, where access can move faster than policy review cycles.
Usage in the industry is still evolving, and no single standard governs this term yet. NHI Management Group treats it as a governance signal rather than a purely user-compliance issue: if a team can bypass an approved path, the policy design may be creating incentives to evade it. That makes route-around behaviour a useful lens for evaluating whether controls are observable, usable, and enforceable in practice. The NIST Cybersecurity Framework 2.0 is helpful here because it emphasizes outcomes, risk management, and continuous adaptation rather than assuming policy intent automatically translates into real control.
The most common misapplication is treating route-around behaviour as simple noncompliance, which occurs when organisations ignore the design friction that pushes legitimate activity into unmanaged channels.
Examples and Use Cases
Implementing route-around detection rigorously often introduces monitoring overhead and user friction, requiring organisations to weigh tighter control against speed and usability.
- A developer cannot access an approved internal file-sharing platform quickly enough, so project artefacts move to a consumer cloud drive that bypasses logging and retention rules.
- An analyst blocked from using a sanctioned AI assistant starts pasting sensitive content into a public LLM interface, creating exposure of secrets, customer data, or internal logic.
- A contractor denied timely access through formal IAM workflows borrows a colleague’s session or uses a shared account, undermining attribution and accountability.
- An attacker finds a hardened primary channel but shifts to email, chat, or collaboration tools with weaker detection, making the attack harder to see in central monitoring.
- Security teams studying cloud and identity patterns often compare these shifts to guidance from sources such as the NIST Cybersecurity Framework 2.0 to understand where governance failed to align with actual behavior.
In agentic AI settings, route-around behaviour can also happen when a sanctioned tool is too constrained, causing users or automated workflows to adopt alternate agents, ad hoc plugins, or unofficial orchestration paths that were never reviewed for access scope or data handling.
Why It Matters for Security Teams
Route-around behaviour matters because it is often the earliest sign that a control has lost operational legitimacy. If security teams only measure whether a policy exists, they can miss the fact that users, administrators, or agents are already operating outside the intended boundary. That creates blind spots in identity attribution, secrets handling, audit logging, incident response, and data loss prevention. In NHI and agentic AI environments, the risk is sharper because machine identities and autonomous tools can move through approved and unapproved channels at machine speed, amplifying small governance gaps into systemic exposure.
This is why route-around behaviour should be evaluated alongside access governance, approvals, and observability, not as a separate user-behavior problem. A control that is too slow, too rigid, or too opaque invites workaround patterns that undermine assurance. Practitioners often benefit from checking whether the approved path is the path of least resistance, because if it is not, the organisation is effectively designing for evasion. The lesson aligns with the broader outcome-focused approach in the NIST Cybersecurity Framework 2.0 and becomes especially important when governance extends across identity, cloud, and AI workflows.
Organisations typically encounter route-around behaviour only after a breach, audit finding, or shadow workflow discovery, at which point the bypass path becomes operationally unavoidable to address.
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, NIST AI RMF and NIST SP 800-63 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST CSF 2.0 | GV.OC-03 | Defines governance and outcome alignment that helps spot when users bypass intended controls. |
| NIST AI RMF | Frames AI risk as a lifecycle governance issue, relevant when users shift to unofficial AI paths. | |
| OWASP Non-Human Identity Top 10 | NHI guidance highlights shadow credentials and unmanaged paths that enable control bypass. | |
| OWASP Agentic AI Top 10 | Agentic AI guidance addresses tool misuse and unauthorized alternate execution paths. | |
| NIST SP 800-63 | IAL/AAL/FAL | Digital identity assurance weakens when users route around formal identity and authentication flows. |
Compare policy outcomes to real workflows and redesign controls that people routinely route around.
Related resources from NHI Mgmt Group
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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
