AI Security & Risk Assessment
Protecting data and AI systems from emerging risks
We design secure AI solutions and assess existing systems for sensitive data exposure, unauthorised access and attack scenarios specific to AI.
AI security mapSystem under control
Model and business logic
What we assess
Risk does not exist only inside the model
An AI system includes data, prompts, APIs, access permissions, external services, logs and storage. Its security depends on how these components interact and where the boundaries of trust are placed.
Sensitive Data Exposure
Confidential information may be disclosed to a model, an external API or a user without the necessary permissions.
Prompt Injection
Direct or indirect instructions may manipulate the model and change the system’s intended behaviour.
Excessive Permissions
An AI tool may receive broader access to documents, actions and internal systems than the process actually requires.
Insecure Integrations
Security gaps may emerge between models, plugins, APIs, CRM platforms, databases and third-party services.
Logs & Vector Stores
Sensitive information may remain in prompt histories, logs, embeddings, vector stores, caches or backups.
Architecture & Trust Boundaries
Systemic risks may exist in data routes, authorisation logic and the way trusted and untrusted components interact.
How we can help
Secure implementation and assessment of existing systems
We can join a project before an AI solution is launched or assess infrastructure that is already operating.
Secure AI Implementation
We design AI architecture around the types of data involved, user roles, access levels, models, APIs, logs and external integrations.
- data and component mapping
- access boundaries and user roles
- secure model and API integrations
- logging, validation and monitoring
AI Security Assessment
We examine an existing system, identify realistic risk scenarios and prepare a prioritised plan for reducing them.
- architecture and data flows
- permissions and authorisation
- prompt injection and data exposure
- AI-specific attack scenarios
What you receive
A clear view of the risks and a practical order of action
The result is not a generic list of possible threats. It is a specific explanation of what requires protection, where the most relevant risks are located and which changes need to be implemented first.
Data and Access Map
What data the system processes, where it travels and which users, services and models can access it.
Prioritised Risks
Risks classified according to their likelihood, potential impact and relevance to the business process.
Remediation Plan
A practical sequence of technical and organisational changes designed to reduce the identified risks.
Example output
What an AI security assessment could produce
For example, suppose an AI assistant uses internal company documents. The assessment materials could include:
Data and access map
Which documents the assistant can access, which roles use them and which external services the system calls.
Risk scenarios
What happens when someone attempts to obtain information without the required permissions and which data could be exposed.
Prioritised fixes
Which permissions and data flows need restricting and what to retest after changes.
This is an illustrative example, not a finding about a real system. The report content depends on the agreed assessment scope.
Assessment process
From system context to a prioritised security plan
The depth and scope of the assessment depend on the architecture, data types, integrations and the role AI plays in the business process.
Context
We establish the purpose of the system, its users, data, actions, integrations and security requirements.
Architecture Map
We document the components, data flows, trust boundaries, permissions and external dependencies.
Assessment
We evaluate realistic scenarios involving data exposure, prompt attacks, excessive permissions and unauthorised actions.
Recommendations
We prepare a prioritised, technically practical plan for strengthening the system.
AI security check
When to assess an AI system
An assessment is particularly relevant when AI has access to sensitive information, internal systems or actions that affect business data.
- Processes customer or employee data
- Uses confidential internal documents
- Connects to CRM, ERP or internal databases
- Can create, change or delete information
- Uses external models or APIs
- Stores prompts, responses or embeddings
- Provides different access levels to different users
- Is moving from prototype to production
AI security assessment
Identify and reduce the real risks in your AI system
We will determine which data, components and integrations require protection, where the relevant risk scenarios are located and which changes need to be implemented first.
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