LLM & AI Penetration Testing
Break your AI before attackers do
We attack your LLM features, AI agents, and MCP servers the way a real adversary would, and a certified human tester proves every finding with a working exploit before it reaches your report.
LLMs turn untrusted text into actions, which quietly breaks the assumptions your old security model was built on. A single crafted prompt buried in a support ticket, a PDF, or a web page your agent reads can leak data, call tools it should never touch, or take actions on a user's behalf. We test the whole system, the model, the prompts, retrieval, the tools, and the MCP layer that wires them together, and we exploit what we find so you see the real blast radius instead of a theoretical warning.
What we test
Where we focus.
Prompt injection (direct and indirect)
Malicious instructions typed straight in, or smuggled through documents, emails, and web content your model ingests.
Jailbreaks and guardrail bypass
Role-play, encoding, and multi-step attacks that push the model past its safety and policy limits.
Tool and function-call abuse
Coercing an agent to invoke tools, APIs, or shell actions well outside its intended authority.
MCP server and tool security
Auth, scope, and input handling on Model Context Protocol servers, plus poisoned tool descriptions and confused-deputy paths.
Insecure output handling
Model output rendered downstream as HTML, SQL, or code, opening XSS, SSRF, and injection in the app around it.
RAG and data poisoning
Tainted documents and embeddings that steer answers, plant backdoors, or exfiltrate context across users.
Sensitive data and PII leakage
System prompts, secrets, training data, and other users' data pulled back out through the model or its logs.
Agent authorization boundaries
Whether one user, tenant, or session can reach data and actions that belong to another through the agent.
How it works
From scope to retest.
Scope on a short call
We map your models, agents, tools, MCP servers, and trust boundaries, then fix the price and timeline before any testing starts.
Attack the full stack
Certified testers run manual adversarial testing across the OWASP LLM Top 10, backed by our in-house AI engine for breadth, and exploit each weakness end to end.
Report with proof
You get every finding with a working proof of concept, the exact prompts and payloads, real business impact, and a fix mapped to SOC 2, ISO 27001, PCI DSS, and HIPAA controls.
Retest for free
Once your team ships fixes, we re-run the same attacks, confirm each issue is closed, and issue an attestation, at no extra cost.
What you get
In your report.
- ✓Executive summary plus technical findings, written for both the board and the engineers who fix them
- ✓A working proof-of-concept for every exploited finding, with the exact prompts and payloads to reproduce it
- ✓Severity ratings and prioritized, LLM-specific remediation guidance
- ✓Every finding mapped to SOC 2, ISO 27001, PCI DSS, and HIPAA controls
- ✓A free retest and a signed attestation letter once your fixes are verified
Questions
Answers, up front.
Do you test agents and MCP servers, or just a chatbot?
Both. We test single-prompt features, multi-step agents, and the MCP servers and tools they call, including auth, scope, and poisoned tool definitions. The agent and tool layer is where most real damage happens, so it gets the most attention.
Will testing corrupt our production data or model?
No. We scope destructive actions up front and test against staging or a sandboxed environment wherever a tool call can write, delete, or spend. Anything with real-world side effects is agreed with you before we run it.
Is this just an automated scanner run?
No. Our AI engine adds speed and coverage, but a certified human tester validates and signs off on every finding. You never chase a false positive or a bug that no attacker could actually reach.
Ready to put it to the test?
Scope your llm / ai engagement on a short call. Fixed price, fixed timeline, and an auditor-ready report in days.
Book a scoping call →