Cybersecurity
AI security
Assistants and agents act on data and call tools. That changes the threat model. We assess how AI features handle untrusted input, who they act as, what they can reach, and what happens when they are tricked.
Why AI features need their own review
A language model cannot reliably tell instructions from data. Anything it reads, such as a web page, a document or an email, can contain instructions that change its behavior. That is why prompt injection sits at the top of the OWASP Top 10 for LLM Applications, and why the security of an AI feature depends mostly on what surrounds the model: authorization, tool permissions, data boundaries and logging.
We test those surroundings. We ask what identity the application uses, what data it can retrieve, what tools it can call, and which of those actions need human approval. We align findings to OWASP guidance for LLM applications and the NIST AI Risk Management Framework. We do not claim proprietary AI security tooling.
Services
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LLM security assessments
Test chatbots, copilots and LLM-backed features for prompt injection, data leakage, unsafe output handling and excessive permissions.
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AI red teaming
Adversarial testing of AI systems against defined harms: security abuse, data exposure, unsafe actions and policy bypass.
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AI agent security
Review agents that plan and call tools: identity, tool permissions, approvals, memory, isolation and audit.
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RAG security
Review retrieval-augmented generation: document-level authorization, poisoning, embedding exposure and leakage through answers.
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MCP security assessment
Review Model Context Protocol servers and clients: tool design, authentication, command execution, data exposure and supply chain.
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AI security architecture
Design the controls around AI features: gateways, identity, data boundaries, evaluation, monitoring and governance.
An AI application and its trust boundaries
- User and external content Untrusted input
- Application and orchestration Prompts, policies
- Model gateway Provider, logging, limits
- Retrieval and data stores Per-user authorization
- Tools and APIs Least privilege, approvals
Questions people ask
Can you test any model?
We test the application around the model: prompts, retrieval, tools, permissions and data flows. We do not claim to test or certify the models themselves.
Do you provide an AI security platform?
No. Our work is assessment, architecture and engineering advice. We do not sell proprietary AI security products.
Related
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API penetration testing
Testing REST, GraphQL and internal APIs for broken authorization, tenant isolation failures, token weaknesses and business-logic abuse.
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Consulting and GRC
Security strategy, architecture review, security engineering and implementation, and readiness support for NIST CSF, SOC 2, ISO 27001, PCI DSS, HIPAA and CMMC.
Need to understand your security exposure?
Speak with a security expert
Talk through your environment and goals. We reply to scope the work before anything is tested.
Speak with a security expertPlan an assessment
Answer a few questions and get a structured preliminary scope you can send us.
Use the plannerUnder attack right now?
Call the US office and tell us what you are seeing. Do not wait for a form reply.
Incident response