Planned focus
AI security.Question the whole system.
An AI feature is part of a wider application. Our planned AI security research looks at how models, data, tools and people interact, and where a system needs a clear boundary.
Start beyond the model.
A useful review begins with the job the AI feature is meant to do. A drafting assistant, an internal knowledge search tool and an agent able to change business records have different responsibilities. Their permitted data access and actions should reflect those differences.
For an AI-enabled application, a model response is one part of a larger flow. The surrounding software decides which information can be retrieved, what a tool can do, which outputs reach users and when a person must approve an action. Those decisions belong in the security design.
Four boundaries worth making explicit.
Data access
Document the data sources, retention expectations and permissions for each user role. A retrieval feature should respect the same access boundaries as the underlying application.
Instructions and untrusted content
Distinguish application instructions from material the system reads. A review should consider how externally supplied content is handled and whether it can influence decisions beyond its intended role.
Tools and consequential actions
Define what each integration is allowed to read or change. Sensitive actions need authorization at the application boundary, with an understandable approval step where appropriate.
Observation and recovery
Decide what evidence is needed to understand an unexpected result without unnecessarily retaining sensitive content. Plan how a team can pause an integration, review an action and recover from a mistake.
Evaluate outcomes, not impressive demos.
A useful AI security evaluation has a defined system version, explicit permission boundaries and representative workflows. It should record both observed failures and the limits of the evaluation. A successful demonstration on a narrow example does not establish that every workflow is safe.
Our intended focus connects these observations with application security and engineering review. Findings should help the team decide which control belongs in the product, rather than relying only on a model being asked to behave differently.
AI security is a planned focus at BreachQuill. Research and availability updates will appear as the work develops.
Different disciplines.
One questioning mindset.