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Enterprise / Prompt-injection testing

Examine where instructions cross trust boundaries.

Explore whether untrusted content can influence an AI application's intended instructions, data access, or connected actions within agreed test conditions.

Prompt-injection risks

What happens when content behaves like an instruction?

AI applications may process user input, retrieved documents, external content, and tool responses. Those inputs do not all deserve the same level of trust.

Prompt-injection testing examines agreed attempts to cross those boundaries. The useful finding is the application's observed behavior and its consequences—not simply whether a model can produce an unusual answer.

Testing scope

Scenarios depend on the application.

Instruction handling

Conflicting or misleading input

Examine how agreed untrusted inputs interact with intended task instructions.

Data boundaries

Information access and disclosure

Consider whether information is exposed beyond the permitted access of the test user.

Connected actions

Tool and workflow behavior

Where authorized, examine whether misleading instructions can affect permitted tool calls or actions.

Authorization and deliverables

Defined conditions. Documented limitations.

Before testing

  • Document the owner and testing authorization.
  • Agree models, applications, tools, and accounts.
  • Use approved test data and bounded environments.
  • Define prohibited actions and stop conditions.

What to agree as outputs

  • Test scenarios and observed application behavior.
  • Reproduction context and evidence restrictions.
  • Business relevance and practical recommendations.
  • Explicit limitations and any retesting scope.

Discuss your needs

A useful next step starts with your environment.

Discuss the decision, systems, and boundaries that matter. We can establish what work is appropriate before making commitments.

Discuss your needs ↗