Baseline Threat Model

A first-pass threat model generated from available system context, usually intended to accelerate review rather than replace it. It gives engineers a starting point for validating threats, severity, and mitigations, especially when teams are too large or too busy for fully manual drafting.

Expanded Definition

A baseline threat model is a preliminary security analysis that captures the most likely threats, assets, trust boundaries, and abuse paths using the system information available at the time. It is not the final word on risk. Instead, it creates a structured starting point that teams can refine as architecture details, data flows, and control assumptions become clearer. In practice, it is often used to speed up design review, prioritise follow-up questions, and avoid waiting for a fully manual workshop before any threat thinking begins.

For glossary purposes, the concept sits between informal brainstorming and a formalised threat model. The distinction matters because a baseline model can be generated from partial inputs, but it still needs human validation before it is used for approvals or security sign-off. That aligns with the way threat intelligence and campaign reporting are used in fast-moving environments, such as the CISA cyber threat advisories process and the analysis in Anthropic — first AI-orchestrated cyber espionage campaign report, where initial patterns inform response but do not replace deeper investigation.

The most common misapplication is treating the baseline as a complete threat model, which occurs when teams use auto-generated output as approval evidence without reviewing assumptions, omitted assets, or missing attack paths.

Examples and Use Cases

Implementing a baseline threat model rigorously often introduces a speed-versus-completeness tradeoff, requiring organisations to weigh rapid design feedback against the risk of false confidence.

• Early product design reviews use a baseline model to identify obvious authentication, authorisation, and data exposure risks before engineers invest in detailed implementation.
• Platform teams generate a first-pass model from cloud diagrams, then refine it during architecture review once trust boundaries and dependencies are confirmed.
• Security teams use baseline models to triage large portfolios, focusing manual effort on systems with exposed APIs, sensitive data, or privileged automation.
• AI and agentic systems often require a baseline view of tool access, prompt injection exposure, and action boundaries, then deeper analysis with resources such as the CSA MAESTRO agentic AI threat modeling framework and MITRE ATLAS adversarial AI threat matrix.
• Operations teams use a baseline model after a new incident pattern emerges, then update it with concrete adversary behaviour and mitigations from the current threat landscape.

In all of these cases, the baseline model is useful because it lowers the cost of starting, not because it eliminates the need for validation.

Why It Matters for Security Teams

Security teams need baseline threat models because review capacity is always limited, while system change is continuous. A good baseline gives structure to early decisions, helps surface missing assumptions, and prevents teams from shipping without any threat analysis at all. The value is highest when the system is still changing, because that is when later review work is cheapest to correct.

The risk is that speed can hide uncertainty. If the baseline is created from stale diagrams, generic templates, or incomplete inventory data, the organisation may miss the real attack surface entirely. That is especially important for AI-enabled and autonomous systems, where agent authority, tool access, and exception handling can expand the blast radius of a flaw. Frameworks such as MITRE ATLAS adversarial AI threat matrix help teams think about adversarial pressure, while CISA cyber threat advisories help keep that baseline anchored to current threat activity.

Organisations typically encounter the operational cost of a weak baseline only after an incident, at which point threat modeling becomes unavoidable to explain what was missed and what must be rebuilt.

Related resources from NHI Mgmt Group

• Shared Responsibility Model
• What does AI model abuse reveal about the current NHI threat surface?
• What does a fully malicious server threat model reveal in a password manager audit?
• Dynamic Security and Utility Threat Model