Deploying large language models (LLMs) is no longer experimental—it’s production. But with innovation comes exposure. Traditional security assessments don’t cut it here. Our AI Systems Security Assessment is built from the ground up to uncover threats unique to LLM pipelines, plugins, prompt handling, and model behavior.
This isn’t a generic pentest. It’s a deep dive into how your AI can be exploited—and how to stop it.
We start by mapping your LLM ecosystem—APIs, data sources, user flows, and all integration points. Then we identify attack vectors using a simplified STRIDE model tailored for LLMs. Think prompt injection, privilege escalation, jailbreak bypasses, and more.
We simulate real-world adversaries:
Executive summary with risks, impact, and recommended actions
Technical findings with PoC prompts and attack chains
Threat model diagrams and risk scoring
Remediation playbook prioritized by impact and exploitability
Enterprises deploying LLMs in production
Startups integrating LLMs into apps or APIs
Any org that can’t afford to get burned by AI gone rogue
We know that every day you have everything on the line, and that with so much at risk it can seem like adversaries have all the advantages. Together we can take the power back. Where other cybersecurity providers see a vendor and a customer, we see a united team of defenders who are stronger as one.
and that means XDR
The choice is yours: see LMNTRIX in an on demand demo or set up a customized demo or request a quote.