Unexpected input changes the outcome
Test the application against competing instructions and boundary cases that a normal functional test may never encounter.
Review the policies and application boundaries behind safer AI responses.
Request an assessmentModels respond to more than an application’s intended instructions. User input, retrieved information and integration behavior all influence the result. We examine where controls apply, how they fail and what engineering changes can make them more dependable.
Test the application against competing instructions and boundary cases that a normal functional test may never encounter.
Understand what enters a model, what leaves it and where application checks should protect sensitive context.
Review how external instructions and data influence application behavior across the workflow.
Examine the context, data and trust assumptions that shape decisions and responses.
Test important security boundaries with practical scenarios and document what happens.
Connect the review to the frameworks, services and engineering practices your team uses.
A focused review of the controls, connections and behaviors that matter to your application.
Request an assessmentEstablish the context behind the system and the decisions it makes.
Understand the boundaries and assumptions behind important actions.
Review practical risks in the context of your application.
Give your team evidence they can reproduce and understand.
Translate findings into focused engineering improvements.
“A security assessment should make the next decision clearer. We connect technical findings to your application, your priorities and the work your team can take forward.”
Practical perspectives for teams building and operating AI systems.
Tell us what you are building and the security questions your team needs to answer.
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