The model context window is the set of information an AI system can see and use during a run. For identity governance, it matters because secrets placed here can be echoed, stored, or reused by downstream tools, turning a temporary credential into an exposure event.
Expanded Definition
The model context window is the bounded set of prompts, retrieved content, tool outputs, and prior messages an AI system can attend to during a run. In NHI governance, this matters because the window can carry secrets, tokens, API keys, or certificates far beyond the original source system, which changes the exposure model from storage risk to runtime disclosure risk. The NIST Cybersecurity Framework 2.0 helps frame this as an information protection and access control problem, not just a model quality concern.
Definitions vary across vendors, especially where memory, retrieval augmentation, and tool invocation are blended into one product experience. NHI Management Group treats the context window as every place the model can actively reference during inference, including content injected by an agent, because each item can influence output and downstream action. That is why context hygiene must be governed like a privileged data path, with explicit limits on what enters the window and what may be echoed back. The most common misapplication is treating the context window as a safe temporary buffer, which occurs when operators place live secrets into prompts or retrieval sources without controlling exposure, retention, or tool forwarding.
Examples and Use Cases
Implementing context-window controls rigorously often introduces friction between agent usefulness and data minimisation, requiring organisations to weigh richer task completion against tighter disclosure limits.
- An AI agent summarises a ticket that includes an API key, then passes the summary into another tool; the key was never intended to leave the original workflow.
- A retrieval-augmented assistant pulls in operational runbooks, but one runbook embeds a service account token, creating an accidental secret propagation path.
- A developer pastes a certificate chain into a chat session for troubleshooting, and the model later reproduces it in a response visible to broader users.
- A security team uses the context window to supply just enough entitlement data for a workflow, while excluding the raw secret and sending only a reference identifier.
- In the Ultimate Guide to NHIs, NHI Management Group shows how broad visibility gaps and excessive privileges magnify the blast radius when credentials are handled carelessly; pairing that guidance with the NIST Cybersecurity Framework 2.0 reinforces the need for controlled information flow.
Why It Matters in NHI Security
Context-window misuse turns ephemeral access into durable risk. When a secret is placed into the window, it can be echoed to logs, reused by a downstream agent, captured by a connected tool, or exposed in a follow-on response. This is especially dangerous in NHI environments because service accounts and API keys often already carry excessive privilege. NHI Management Group reports that 79% of organisations have experienced secrets leaks, and 77% of those incidents resulted in tangible damage, which makes runtime secret handling a governance issue rather than a theoretical model concern.
Security teams should treat the context window as part of the access boundary for every agent workflow. That means minimising injected credentials, using references instead of raw secrets, constraining retrieval sources, and reviewing what tool outputs are allowed back into the window. The same operational discipline aligns with the Ultimate Guide to NHIs, which highlights how visibility gaps and poor secret handling compound exposure across machine identities. Organisations typically encounter the consequence only after a secret has already been echoed, logged, or forwarded by an agent, at which point model context window controls become 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 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 covers prompt injection and unsafe context handling around tool-using agents. | |
| OWASP Non-Human Identity Top 10 | NHI-02 | Secret handling controls apply when credentials are introduced into model context. |
| NIST CSF 2.0 | PR.DS | Data security outcomes depend on controlling sensitive information within AI runtime paths. |
Keep raw secrets out of context windows and replace them with references or vaulted tokens.
