Reviewing Indemnity Exclusions in AI Coding Assistant Terms

Read the indemnity as a set of conditions

A headline promise to defend customers against intellectual property claims over generated code says little until you read what surrounds it. The scope is usually set by exclusions, conditions precedent and definitions, and these often point to how the tool is configured and used rather than to what the vendor's model produced.

That shifts the review from a purely legal reading to a joint legal and engineering one. A condition such as "the customer must have enabled the required filters" is a statement about a technical setting. If developers can change that setting, or if nobody records its state, the condition may be impossible to prove when a claim arrives.

NIST's generative AI guidance points in the same direction at a general level. It includes actions to review vendor contracts and to establish terms of use for generative AI systems. It is not a clause-level checklist, but it supports treating contract terms as part of risk management rather than as a procurement formality.

Common exclusion categories and the question each raises

Indemnity clauses for AI code generation can contain any of the following. Read for each one, then ask what must be true for it not to apply.

• Required filters or settings: Which settings must be on, and who can change them? Evidence needed: a record of configuration state at the time of generation.
• Modified or combined output: How does the clause define modification and combination? Evidence needed: a way to tie shipped code back to the generated suggestion.
• Non-vendor or unapproved models: Is coverage limited to named models or modes? Evidence needed: a record of which model served each interaction.
• Knowledge or intent carve-outs: What notice or awareness removes coverage? Evidence needed: a record of how warnings and flags were handled.
• Security defects: Are vulnerability-related claims outside the indemnity? Evidence needed: security context for the code, and a clear view of the residual exposure.
• Open-source licence claims: Does the indemnity address licence obligations or only copyright and trade secret claims? Evidence needed: licence context for generated code.

Test each condition against actual developer workflows

Contract language describes an intended deployment. Developers work differently. They may use the assistant in several editors, on personal or managed accounts, with different plugins, and with different model choices where the tool allows it. NIST's AI risk management framework flags third-party AI and off-label use as risks, which is a useful lens: coverage built on a specified configuration may not extend to use outside it.

For each condition, run a short walkthrough with engineering. Ask which teams use the assistant and in which environments. Ask whether the required settings are applied by an administrator or chosen by each user, and whether they can be changed silently. Ask whether developers can select a different model or mode, and whether generated code is routinely edited, merged with internal libraries or combined with third-party components before commit.

The answers usually expose gaps between the clause and the practice. A modification exclusion, for example, may be triggered by ordinary development work, since most generated code is edited before it ships. If so, the indemnity may cover far less than the business assumes, and that should be a documented finding, not a surprise.

Decide which conditions need technical enforcement and evidence

Not every condition needs engineering controls. Some are best handled by negotiation, such as narrowing a knowledge carve-out or clarifying a definition. Others depend on behaviour that will drift unless something enforces it.

A practical test has two parts. First, can the condition be enforced centrally, or does it rely on each developer doing the right thing? Second, if a claim arrives in a year, can you show the state of that condition on the relevant date? Conditions that fail the second part have little value in practice, even if they are technically met.

The evidence should be created at the time of the interaction rather than reconstructed afterwards. Reconstruction from memory, tickets or later configuration exports is slow and easily challenged. Also consider retention. Code and related artefacts need to be kept long enough to match the period in which a claim could be raised, and NIST's secure development draft practices on storing all forms of code are a reasonable reference point for that discipline.

For open-source and security conditions, software composition analysis is a common way to identify known vulnerabilities and components in code. It is a useful input to review, but it does not replace a contractual position on licence claims or security-defect exclusions.

Negotiation positions and questions for the vendor

Bring specific questions to vendor review and ask for answers in writing. The aim is to narrow the gap between what the clause requires and what your environment can realistically demonstrate.

• Ask for the complete list of settings, filters and configurations required for coverage, and whether administrators can enforce them for all users.
• Ask how modification and combination are defined, and seek language that covers ordinary editing and integration of generated code.
• Ask which models and modes are covered, and whether coverage follows the customer's approved configuration rather than a default.
• Ask what knowledge, intent or notice triggers remove coverage, and what the vendor would accept as evidence that a condition was met.
• Ask how open-source licence claims and security defects in generated code are treated, and seek explicit wording rather than silence.
• Ask about notice periods, control of defence, termination rights and whether terms can change during the contract term.

Where runtime enforcement and code provenance evidence fit

Runtime policy enforcement and code provenance evidence help with the operational side of this review. They do not replace contractual protection, and they cannot cure a clause that excludes your use case.

Trussed enforces policy in the execution path of coding assistants, applying allow, redact or block decisions to individual interactions and tool calls. That is relevant to conditions about required settings and permitted usage, because a rule is enforced at runtime, not reviewed after the fact. Trussed also records code provenance, meaning the origin, licence and security context of code, and enforcement produces audit-ready evidence that can be retained under configurable retention settings. Together these give legal teams records to point to when asked whether a condition was met.

The limits matter. This evidence describes interactions and code context. It does not settle how a court or vendor would read a clause, and whether it satisfies a vendor's evidentiary demands should be agreed during negotiation, not assumed.