AI Red Teaming
Find vulnerabilities before attackers do
We systematically attack your AI systems using the same techniques as malicious actors. Prompt injection, model extraction, adversarial inputs — we test them all so you can fix them first.
Quick Answers
What is AI Red Teaming?
Systematic adversarial testing of AI systems to identify vulnerabilities before malicious actors exploit them. We simulate real attacks to find weaknesses in your models, APIs, and data pipelines.
Why do AI systems need security testing?
AI systems face unique threats: prompt injection can leak confidential data, adversarial inputs cause failures, model extraction steals IP. Traditional security testing doesn't cover these attack vectors.
What's the difference from regular penetration testing?
AI red teaming focuses on ML-specific vulnerabilities: prompt manipulation, training data poisoning, model inversion, and output manipulation. We understand how models think — and how to break them.
What We Test For
Comprehensive coverage of AI-specific attack vectors
Prompt Injection
Testing for system prompt extraction, instruction override, and context manipulation that could expose confidential data or bypass safety controls.
Model Poisoning
Evaluating training pipeline security and detecting vulnerabilities that could allow adversarial data to corrupt model behavior.
Adversarial Attacks
Testing model robustness against crafted inputs designed to cause misclassification, hallucination, or complete system failure.
Model Extraction
Assessing exposure to model theft through API queries and preventing intellectual property from walking out the door.
What You Get
Proof of Exploitation
Documented evidence of successful attacks — not theoretical risks, but actual exploits demonstrated against your systems.
Attack Chain Documentation
Step-by-step breakdown: how we gained access, what data was exposed, and exactly how to prevent it.
Executive Briefing
2-hour session: we demonstrate attacks live, explain business impact, and provide prioritized remediation guidance.
Remediation Roadmap
Actionable fixes ranked by severity and effort, with implementation guidance for your security team.
Our Process
Reconnaissance
- • Map AI system attack surface
- • Identify all model endpoints and data flows
- • Review architecture and access controls
- • Define testing scope and rules of engagement
Active Testing
- • Execute prompt injection attacks
- • Test adversarial input handling
- • Attempt model extraction techniques
- • Probe for data leakage vulnerabilities
Reporting & Remediation
- • Document all findings with evidence
- • Deliver executive briefing
- • Provide remediation guidance
- • Verify critical fixes if requested
Who This Is For
AI red teaming is essential for organizations deploying AI in production environments.
Why Choose Kenaz
We bring something most red team services don't: a purpose-built platform. Mantis covers 10+ AI-specific attack categories with 500+ training pairs, then human red teamers go deep on the findings that matter. Every finding is mapped to EU AI Act Article 15 cybersecurity obligations, GDPR Article 32, and OWASP LLM Top 10 — so you don't just get a list of bugs, you get audit-ready evidence.
Learn more about Mantis →