AI red teaming services in the UAE
We run independent, expert-led red team campaigns against LLMs, agents, and the systems built around them. We do not build the models we test, which is the point: the team that ships an AI system cannot be the same team that signs off on whether it is safe. Based in the UAE, working with teams in Dubai, Abu Dhabi, and globally.
What AI red teaming is, and what it is not
AI red teaming is adversarial testing of an AI system to find how it fails before attackers or ordinary users do. We put the system under deliberate pressure and document what breaks, how, and how badly.
It is not a one-time checklist, and it is not a generic vulnerability scan of your infrastructure. It is behavioural: we attack the model and the logic around it, not just the servers it runs on.
What we test
We test the full surface of a modern AI deployment, not just the chat box.
- LLMs and the prompts, system messages, and guardrails around them
- Autonomous agents that call tools, hold memory, and chain steps
- Retrieval and RAG systems over private or regulated corpora
- Tool-chain and function-calling integrations
- Multi-turn flows where the attack builds across several messages
Frameworks we map every finding to
Every finding is traceable to a recognised source technique, so your auditors and your engineers are reading the same map.
- OWASP LLM Top 10
- MITRE ATLAS adversarial techniques
- NIST AI 100-2e2025 adversarial-ML taxonomy
- UAE AI Charter, where the principle is testable against system behaviour
Our coverage
Coverage spans direct and indirect prompt injection, multi-turn agentic attacks, tool-chain compromise, data exfiltration (training-data extraction, system-prompt leakage, and membership inference where the system handles PII), and over-refusal calibration.
We build on the open red-team tooling the field already uses, including Garak from NVIDIA and PyRIT from Microsoft for the heavy adversarial automation, Promptfoo for adversarial replay, and TextAttack for NLP-specific attacks, with custom Lattice/AI attacks layered on where the engagement calls for it.
How an engagement runs
A red-team engagement typically runs 2 to 12 weeks depending on scope. Every finding gets a CVSS-aligned severity score, and every report we deliver is signed and dated.
You receive a findings report and a patch playbook with explicit rerun criteria, so your team knows what to fix and how we will confirm it is fixed.
Why independence matters
Vendors who build AI cannot independently grade it, and internal teams cannot either. We exist to be the third signature on whether an AI system is ready to ship.
Independence is contractual, not just a claim. We will put that attestation in writing for your auditors, and we turn down work we cannot put our name on.
Based in the UAE, working globally
We are a UAE-based firm and work with teams across Dubai, Abu Dhabi, and the wider MENA region, as well as clients elsewhere. Regulatory context (CBUAE, DIFC, the UAE AI Charter) is something we work in, not something we translate from a distance.
Who signs the report.
Lattice/AI is an independent AI evaluation firm, founded and led by Rahul Srivastava. For seventeen years he has made it his work to find how systems fail before the people who rely on them do, and he built Lattice/AI to bring that discipline to AI.
His research on AI safety is published and peer-reviewed, he contributes to Microsoft PyRIT, the open framework Microsoft built for adversarial AI testing, and his findings have carried enough weight for a major model vendor to ship a fix in response. What you are hiring is judgment proven in the open, with a name attached to it, not a logo.
Every engagement ends in a signed, dated report that shows what failed next to what passed. Here is the format we ship: a sample scorecard.
Questions buyers ask.
What is AI red teaming?
Adversarial testing of an AI system to surface failures before attackers or users do. We attack the model and the logic around it under realistic conditions and document every finding with a severity score.
How is AI red teaming different from a penetration test?
A penetration test targets infrastructure and application security. AI red teaming targets the behaviour of the model and the agent: prompt injection, tool misuse, data leakage through generation, and unsafe actions. The two are complementary, not the same.
How long does an LLM red team engagement take?
Typically 2 to 12 weeks, depending on the number of systems in scope, whether agents and tool chains are involved, and the depth of coverage you need.
Do you test agents and RAG systems, not just chatbots?
Yes. We test autonomous agents, tool and function-calling chains, and retrieval or RAG systems, including multi-turn attacks that a single-prompt chatbot test never reaches.
Can you sign an independence attestation for our auditors?
Yes. Independence is contractual. We provide a written attestation, and we do not build the systems we are grading on the same engagement.
Do you work with companies outside the UAE?
Yes. We are UAE-based and work globally. Much of our regulatory depth is UAE-specific, but the red-team methodology applies wherever you ship.
Tell us what’s under contract.
Three sentences is usually enough. Tell us what you are trying to ship, when it has to land, and the thing that scares you about it.