The end-to-end route from untrusted input to a sensitive action. In agent governance, it is the most practical way to understand whether a message, API response, or external signal can reach a high-impact operation without a trustworthy control boundary intervening.
Expanded Definition
Source-to-sink path describes the full chain from a source of untrusted or semi-trusted data to the sink where that data can influence a sensitive action. In NHI and agent governance, the term is useful because the risk is rarely the input alone, but whether that input can traverse parsing, memory, tool selection, policy checks, and execution without a trustworthy boundary.
Definitions vary across vendors and security disciplines, but the operational meaning is consistent: trace the route that turns external content into impact. That makes the concept especially relevant for AI agents, workflow automations, and service-to-service integrations where a message may enter as benign text and exit as a credentialed action. A source-to-sink path is not limited to code injection. It also includes prompt injection, poisoned API responses, malformed event payloads, and any chain where an agent has execution authority. The NIST Cybersecurity Framework 2.0 reinforces the need to identify and reduce pathways that allow unauthorized influence over critical operations.
The most common misapplication is treating the source as the only risk, which occurs when teams inspect untrusted input but do not map where that input can actually reach.
Examples and Use Cases
Implementing source-to-sink analysis rigorously often introduces review overhead, requiring organisations to weigh faster agent execution against stronger containment and traceability.
- An LLM-based support agent receives a user message and later calls a ticketing API; the path from text input to status change must be constrained by policy and approval checks.
- A webhook from a third-party system feeds an automation that can rotate keys or trigger deployments; if the payload is not validated, the sink becomes a privileged action surface.
- An agent reads an external document, extracts instructions, and invokes a cloud API. The question is not whether the document is trusted, but whether it can steer the agent into tool misuse.
- For real-world exploit patterns, the ASP.NET machine keys RCE attack shows how a seemingly indirect input path can culminate in code execution when the control boundary is weak.
- In a CI/CD pipeline, a build artifact or config file may act as a source that reaches a deployment sink, turning data contamination into operational compromise.
In practice, teams use this concept to decide where to add validation, sandboxing, human approval, or tool restrictions. A source-to-sink map is most valuable when it reveals hidden trust between components that appear separate on paper.
Why It Matters in NHI Security
Source-to-sink paths are central to NHI security because NHIs are frequently the mechanism that makes a harmful path actionable. If an agent, service account, or workload identity can take external input and use it with broad permissions, an attacker does not need direct authentication to the target system. They only need to influence the path.
NHIMG data shows that 97% of NHIs carry excessive privileges, which means many sinks are already overpowered before any input arrives. That is why source-to-sink thinking pairs naturally with least privilege, NIST Cybersecurity Framework 2.0 governance, and NHI lifecycle controls. The practical lesson is simple: if the sink can change secrets, deploy code, approve transactions, or modify identities, then every upstream source deserves explicit scrutiny. The relevant failure mode is often invisible until a routine automation becomes an attack path. Organisations typically encounter the consequences only after a prompt injection, poisoned response, or compromised integration has already triggered an unauthorized action, at which point source-to-sink path analysis becomes operationally unavoidable to address.
For this reason, NHI management teams should treat path analysis as a core control, not an academic exercise. It helps expose where a trusted execution context has been quietly extended to untrusted inputs.
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 OWASP Non-Human Identity Top 10 address the attack and risk surface, while NIST CSF 2.0 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Agentic AI Top 10 | Agentic AI guidance centers on unsafe tool use and untrusted input reaching actions. | |
| OWASP Non-Human Identity Top 10 | NHI-07 | Source-to-sink paths expose over-privileged NHI actions and weak control boundaries. |
| NIST CSF 2.0 | PR.AC-4 | Least-privilege access limits how far untrusted inputs can influence critical operations. |
Reduce reachable sinks by constraining NHI entitlements and reviewing privileged automations regularly.
Related resources from NHI Mgmt Group
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on June 11, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
