AI RED TEAM
See your AI the way an adversary does
AI introduce unique attack surfaces across models, pipelines, and supporting infrastructure. We evaluate these systems across every stage of the lifecycle, breaking them down into individual components to identify vulnerabilities unique to AI alongside traditional infrastructure risks.
Trusted by frontier AI developers
We serve as red team of record for multiple frontier AI companies and participate in OpenAI’s Trusted Access for Cyber program. We partner with the UK’s AI Security Institute (AISI) to evaluate frontier model capabilities, applying the same adversary expertise that informs enterprise security to the emerging attack surface of AI systems.
AI security testing that goes beyond the model
Standard security testing wasn’t built to find AI-specific vulnerabilities. But most AI-focused assessments ignore the identity systems, API integrations, and attack paths that connect the model to the networks, credentials, and data it can access.
AI did not make least privilege or deny-by-default less important. It made ignoring them more dangerous. A misconfigured AI system doesn’t just create exposure; it can act on it, across every system it can reach.
We evaluate the full stack: Model behavior under adversarial conditions, non-human identity controls, API integration points, and supporting infrastructure, each assessed from the perspective of a compromised user against objectives tied to actual business risk. That coverage extends into production, with red team exercises running against live AI systems to test whether detection and response hold up under realistic adversarial conditions.
The SpecterOps difference
Full lifecycle coverage
We assess AI systems at every stage, from design through production. Finding a vulnerability before release means fixing issues on your terms.
Beyond the model
The security concern is blast radius: what a compromised AI system can reach next. We test the full stack, not just the model itself.
Attack path expertise
Mapping chains of abusable conditions is foundational to our practice. We apply that methodology to AI pipelines, tracing how initial access enables environment-wide pivot.
Ahead of the threat
Engagements with frontier AI companies, including OpenAI’s Trusted Access for Cyber program, keep our understanding of AI attack surfaces ahead of the threat landscape.
Test and exercise
A playbook never exercised is just a hypothesis. We run red team operations against production AI systems and structured exercises that build lasting response capability.
Leading adversarial discovery
Our practitioners are at the front lines of adversarial discovery. BloodHound, Certified Pre-Owned, SCCM research, and GhostWorks make up our track record.
Red teaming AI systems
Getting started
Our AI red team assessments cover the full stack, from model behavior under adversarial conditions to supporting infrastructure, evaluated against the attack surfaces adversaries are actively targeting. Engagements span design through production and include threat modeling, direct model inference assessments, penetration testing, and red team operations run against production systems. Each concludes with a written report and out brief presentation for your team.