AI Application Security Assessment System
Assessment of LLM-powered applications for prompt injection, data access violations, and tool permission overreach. Analysis of scenarios where the model may disclose confidential information or perform disallowed actions.
The task
Test how applications built on language models withstand malicious instructions, data disclosure and abuse of the tools available to them.
Test scenarios
We built a testbed for attacks through user input, documents and external services. The checks cover prompt injection, access to data and the permissions of an agent’s tools.
Scenarios reflect how the specific application is built and what actions the model can perform through its connected tools.
Change control
Data access and tool permissions are constrained at the application level. The prepared scenarios are reused when the model is changed or the system evolves.
The solution combines expert analysis of possible attacks with reproducible technical checks.