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.
How much does an AI Red Team assessment cost?+
Pricing depends on the complexity and number of AI systems being tested. A focused assessment of a single LLM integration typically starts at $15,000-$25,000. Multi-agent systems with RAG pipelines, tool use, and complex guardrails range from $30,000-$60,000+. We provide detailed scoping and transparent pricing after an initial consultation.
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.