Red Teaming Services for AI Systems & Agents

Shipping Large Language Model features on a tight schedule leaves gaps that standard application security work was never built to catch. Your guardrails hold against the payloads your team thought to try.

An attacker who spends an afternoon rephrasing, role-playing, and hiding instructions inside a document usually finds a way through. We look for the phrasings nobody on your side thought of.

Models repeat what they have seen, and not every leak is a copied secret. We check whether your system can be talked into returning training data, another tenant’s records, system prompts, or credentials held in context.

We also look at whether AI outputs drift into harmful outputs a moderation layer should have caught. Where a retrieval layer is involved, we test whether document permissions survive the trip through the model.

Automated tools, multi-turn ones included, attack generic goals: get the model to say something it shouldn’t. They don’t know that your agent can issue refunds, which tenant’s records would end a deal, or which document a customer can slip into your index.

We run automation for breadth and put our engineers on the attacks that depend on knowing your system.

An agent with a calendar integration is a scheduling assistant. The same agent with write access to your billing system is something else, and its attack surface grows with every tool it can call. We map what each agent can actually reach, then test whether an attacker can steer it into unauthorized actions.

Security questionnaires now ask about prompt injection, training data handling, and agent identity, and a growing share point straight at your risk posture under the EU AI Act. A generic application pentest report does not answer those questions. You need evidence written against AI-specific threats, in a form your buyer’s vendor-risk team will accept.

You change a system prompt on Tuesday and add a tool on Thursday. The report from last quarter now describes a system that no longer exists. Keeping system integrity intact against that pace of change takes an ongoing effort. We scope testing so it can be repeated against what you are actually running.

You have an established security program, and AI is the part of it nobody has tested yet. We extend what you already do to the AI layer and report in the format your existing process expects.

FinTech, HealthTech, and insurance teams face AI questions on top of existing obligations. We produce findings your auditors and your customers’ vendor-risk teams can read, and map them to the frameworks they already use.

You've raised your early rounds and your AI product is already winning users. Now an enterprise prospect wants proof of security before they'll sign, and speed alone won't get you there. A scoped engagement gives you defensible evidence without slowing the roadmap.

You have a tool producing green dashboards and a suspicion it is not telling you much. These are red teaming services AI security leads use to find out what an actual attacker would achieve.