Services
ModelStrike offers expert-led engagements covering AI agents, LLM applications, MCP integrations, and the architecture around them.
No two agent architectures are the same. Engagement scope, depth, and duration are set after we understand your system, its permissions, and what you need to demonstrate — internally or to customers.
A structured, hands-on assessment of your agent and everything it can reach. We map how instructions, data, and permissions flow through the system, then test where those boundaries break under adversarial pressure.
Good fit: Teams with an agent in, or close to, production who want a clear picture of real risk.
Goal-driven offensive testing that behaves like a motivated attacker. Rather than checking items off a list, we pursue realistic objectives — reaching data, triggering actions, escalating privileges — across the model, tools, and connected systems.
Good fit: Agents with broad tool access, sensitive data, or high-impact actions.
A focused review timed for launch or procurement. We assess the architecture and controls you plan to ship with, validate guardrails, and leave you with a prioritized plan and clearer answers for security questionnaires.
Good fit: Launches, major capability expansions, and enterprise security reviews.
MCP makes it easy to hand an agent new capabilities — and easy to hand over too much. We review the servers you build or depend on for exposed capabilities, authorization gaps, tool description manipulation, and unsafe handling of model-supplied input.
Good fit: Teams publishing MCP servers or connecting agents to internal or third-party MCP servers.
Not every LLM feature is a fully autonomous agent, but most still handle untrusted input and sensitive data. We test prompt handling, retrieval, output handling, and the application security around the model.
Good fit: Copilots, chat assistants, and retrieval-augmented features.
The cheapest time to fix an over-permissioned agent is before it ships. We work with your engineers to model trust boundaries, data flows, and high-impact actions, and recommend controls that fit your architecture.
Good fit: Teams designing a new agent or significantly expanding an existing one.
Tell us what your agent does and what it can reach. We'll recommend a scope that matches your architecture and timeline.