Red Teams & Security Researchers

AI Red-Teaming: Test AI Systems Before Attackers Do

GTK Cyber's AI red-teaming course teaches security professionals to find vulnerabilities in AI systems through prompt injection, jailbreaking, robustness testing, and adversarial ML techniques.

Learn About AI Red-Teaming Browse All Courses

Every AI System Is an Attack Surface

Organizations are deploying AI rapidly: chatbots with access to internal data, AI agents that take actions, LLM-powered analysis tools embedded in security workflows. Few of them have been tested adversarially.

The attack surfaces are real and exploitable now: prompt injection, jailbreaking, indirect instruction injection, model evasion, data extraction. These aren’t theoretical vulnerabilities. They’re being exploited in production systems today.

The security profession is just beginning to develop the methodology to test for them systematically.

What AI Red-Teaming Covers

GTK Cyber’s AI red-teaming training teaches practitioners to assess AI systems across the full threat surface:

LLM and Generative AI

  • Prompt injection, direct and indirect
  • Jailbreaking and safety control bypass
  • System prompt extraction
  • Data leakage from retrieval-augmented systems
  • Multi-turn attack chains

Classical ML and AI Models

  • Adversarial input crafting
  • Model evasion techniques
  • Feature manipulation attacks
  • Robustness evaluation frameworks
  • Data poisoning concepts

Assessment Methodology

  • Threat modeling for AI systems
  • Structured red team frameworks for LLMs
  • Reporting and communicating AI risk
  • Remediation approaches and their limitations

Taught by Practitioners

GTK Cyber instructors don’t teach these techniques from academic papers. They apply them in real assessments and bring that operational experience into the training environment.

Every lab is hands-on. You test real AI systems, craft real attacks, and build the judgment needed to adapt these techniques to the specific systems you’ll encounter in your work.

Prerequisites

Security practitioners with red team, penetration testing, or adversarial research backgrounds. Basic Python familiarity is helpful. No ML background required.

Relevant Courses

intermediate 4 days

AI Cyber Bootcamp

Intensive 4-day bootcamp covering AI, machine learning, and data science applied to modern cybersecurity challenges.
advanced 2 days

AI Red-Teaming

Adversarial testing of AI systems: prompt injection, robustness evaluation, and red-team frameworks.

Frequently Asked Questions

What is AI red-teaming?
AI red-teaming is the systematic adversarial testing of AI systems to identify vulnerabilities, failure modes, and unexpected behaviors. It applies the red team mindset (find the weaknesses before attackers do) to AI-specific attack surfaces like prompt injection, jailbreaking, model evasion, and data extraction.
Who should take AI red-teaming training?
Security professionals on red teams or penetration testing teams, researchers evaluating AI systems for clients, security engineers responsible for AI applications that handle sensitive data or take consequential actions, and anyone tasked with assessing the security posture of AI systems in their organization.
Do I need a machine learning background?
No. GTK Cyber's AI red-teaming course is designed for security practitioners who understand adversarial thinking but need to apply it to AI systems. We teach the AI fundamentals needed to understand failure modes without requiring prior ML expertise.
What AI systems does the training cover?
The training covers large language models (LLMs) and their applications (chatbots, AI agents, RAG systems), as well as classical ML models used in security tools (anomaly detectors, classifiers, scoring systems). The techniques apply to AI systems built on any major platform.

Learn About AI Red-Teaming

Contact us about custom training for your team or upcoming public courses.

Get in Touch