AI Security Audits

AI security audits, red-teamed.

Adversarial testing of LLM applications, AI agents, and MCP servers. Prompt injection, model abuse, tool misuse, and the chained-attack paths that automated red-team tools don’t find.

LLM apps · agents · MCP · senior red teamers

Why this exists

The AI threat model is moving daily.

New attack patterns emerge faster than benchmarks can codify them. Prompt injection, indirect prompt injection, MCP tool confusion, agent-to-agent attacks, supply-chain compromise via tool packages — the playbook a red team needs in 2026 looks nothing like the OWASP top 10 of three years ago. We’ve been tracking and publishing on the discipline since the start; see the research below.

Scope

What we test.

AI red teaming
MCP audits
Agent security
How pricing works

Scoped to your AI stack.

AI audits are sized to attack surface (number of tools, agents, MCP servers) and depth (single-shot red team vs ongoing engagement). Talk to us for a scope and quote.

FAQ

Questions.

Our published portfolio is heavier in smart contract and application security. Our AI red-team and MCP work is newer and largely behind NDAs. The depth shows up in our research output — see the related research below for a sample.

A structured red-team engagement against your LLM application, agent system, or MCP server. We probe for prompt injection, model abuse, tool misuse, data exfiltration, and chained-attack paths — then deliver a written report with reproductions and remediations.

Yes — see the dedicated MCP Security Audit page. We cover server hardening, tool authorization, schema design, and the trust model between the connecting client and the server.

Yes. AI agent toolchains pull in dozens of packages; we review the dependency graph and the trust assumptions on each tool the agent calls.

Yes. If your AI agent touches on-chain assets (a trading bot, an autonomous DeFi agent), the engagement spans both sides — book the Full-Stack Audit or talk to us about a custom scope.

Written report with attack chains, severity rationale, reproduction steps, and remediation guidance. Plus fix verification after you implement.

Ready when you are

Ready to red team?

Send us your LLM app or agent system and a target date. We’ll come back with a scope and a quote within 24 hours.