AI security evaluation
Adversarial evaluation of AI models and agentic systems, from model behavior to tools and surrounding application controls.
Model red teaming
Prompt injection
Agent and tool security
Data exposure
Evaluation design
Expertise
We focus on security questions that require careful manual investigation, practical validation, and direct communication with the teams responsible for the technology.
Selected focus
Testing considers the model, application logic, tools, data flows, and user trust assumptions as one connected system.
Can untrusted content redirect the system?
Can tools be used outside intended authority?
What sensitive context can be exposed?
Threat model and test plan
Reproducible findings
Mitigation priorities
Adversarial evaluation of AI models and agentic systems, from model behavior to tools and surrounding application controls.
Model red teaming
Prompt injection
Agent and tool security
Data exposure
Evaluation design
Manual analysis of web applications and APIs with an emphasis on business logic, authorization, and practical impact.
Web applications
API security
Access control
Business logic
Product security
Assessment of trust boundaries across cloud services, identity systems, exposed infrastructure, and security-sensitive configurations.
Cloud services
Identity and access
Attack surface
Trust boundaries
Configuration review
H-One performs testing only with explicit authorization, an agreed scope, and clear rules of engagement.
Common questions
Automation can support coverage and repeatable checks, but the core of the work is manual investigation of security assumptions, system behavior, and practical attack paths.
Start a conversation
Tell us what you are building, the question you need answered, and where an independent security perspective could help.
Contact H-One