AI & Agentic Red Teaming
We adversarially evaluate your AI systems — Large Language Models, Retrieval-Augmented Generation pipelines, and Autonomous Agents — to discover critical vulnerabilities before threat actors exploit them. Our assessments go beyond automated scanning: we think like nation-state adversaries targeting your AI infrastructure.
What We Test
Our Process
Scoping & Threat Modeling
We map your AI architecture — models, vector stores, agent tools, API endpoints — and identify the most realistic threat scenarios for your industry.
Adversarial Testing
Manual and semi-automated testing across all attack vectors. We craft bespoke payloads targeting your specific models, guardrails, and business logic.
Impact Assessment
Every finding is classified by real business impact: data breach potential, financial exposure, compliance risk, and reputational damage.
Remediation Report
Detailed technical report with actionable fixes, prioritized by risk. Includes proof-of-concept exploits, remediation code snippets, and architecture recommendations.
Validation Retest
We retest all critical and high findings after your team implements fixes, confirming effective remediation.
Aligned Frameworks & Standards
Frequently Asked Questions
What AI systems can you test?+
We test any AI system: ChatGPT/OpenAI integrations, custom LLMs (Llama, Mistral), RAG pipelines (Pinecone, Weaviate, ChromaDB), autonomous agents (LangChain, CrewAI, AutoGPT), AI-powered APIs, and multimodal systems.
How is this different from a traditional pentest?+
Traditional pentesting focuses on network/web vulnerabilities. AI Red Teaming targets the unique attack surface of AI systems: prompt manipulation, knowledge base poisoning, model behavior exploitation, and agent goal corruption. Different skills, different methodology.
Do you need access to the model weights?+
No. We primarily perform black-box and gray-box assessments through the same interfaces your users and integrations use. This simulates realistic attack scenarios. White-box assessments are available for custom-trained models.
How long does an AI Red Team engagement take?+
Typical engagements range from 2-4 weeks depending on the complexity of your AI systems. A single LLM integration may take 2 weeks; a multi-agent system with RAG and tool use may require 4+ weeks.
Is your AI infrastructure secure?
Most AI systems have critical vulnerabilities that automated tools can't find. Let our Red Team discover them before threat actors do.