Your Team's First Line of Defense Against AI Threats.
Custom AI security training and war game exercises - building the adversarial mindset and practical skills your security team needs to defend AI systems in production.
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AI security training addresses the fundamental human-layer gap in AI security programs. You can deploy the best detection rules, governance frameworks, and security tools - but if your security team doesn’t understand AI-specific attack techniques, and your engineers don’t build AI features with adversarial thinking, your defenses will have systematic blind spots.
The AI Knowledge Gap
Traditional security training has not kept pace with the AI deployment curve. Most security teams graduated from courses that cover network security, web application security, and cloud infrastructure. These are necessary skills - but they leave teams unprepared for the attack categories that are unique to AI systems.
Prompt injection is categorically different from SQL injection. An AI agent with tool access is categorically different from a web application. Adversarial machine learning is a research field that most security professionals have never studied. And yet these are the attack surfaces that need defending as organizations deploy AI at scale.
Training That Builds Real Skill
Our AI security training is built around hands-on learning, not passive presentation. The lab environment puts participants in the role of an attacker - crafting prompt injection sequences, attempting jailbreaks, exploiting tool permissions - so they develop the adversarial intuition that makes them effective defenders.
The AI War Game tabletop exercise is the capstone of every training engagement. We design a realistic attack scenario based on your actual AI architecture and facilitate your team through detecting, containing, and recovering from the simulated attack. The debrief identifies specific gaps in your detection capabilities, response procedures, and communication flows - giving you a concrete improvement agenda that goes beyond the training itself.
Security Culture for AI Organizations
Building AI security awareness across your organization - not just the security team - is increasingly necessary as AI features become standard across product, operations, and customer-facing systems. Engineers who understand why prompt injection is possible write more defensible AI applications. Product managers who understand the OWASP LLM Top 10 make better risk trade-off decisions. Executives who understand the AI threat landscape make governance decisions grounded in reality rather than assumption.
Our training tracks are designed for each audience - technical depth for security engineers, practical application for product teams, and risk-framing for leadership - without requiring every group to sit through material designed for someone else.
Engagement Phases
Needs Assessment
Stakeholder interviews to understand the audience technical level, AI stack in use, training objectives, and specific AI threats relevant to your organization. Curriculum tailored accordingly.
Curriculum Design
Custom training materials, lab environment design, AI War Game scenario development based on your actual AI architecture and threat profile. All materials aligned to your tech stack.
Delivery
Training sessions, hands-on lab exercises in isolated environment, and AI War Game tabletop exercise facilitation. Structured for the specific audience: security team, engineers, executives, or mixed.
Follow-up
Post-training assessment, follow-up Q&A session, resource kit delivery, and recommended learning path for continuing skill development.
Deliverables
Before & After
| Metric | Before | After |
|---|---|---|
| Team Capability | No AI security knowledge - traditional security skills only | Hands-on AI attack and defense skills built in 1-2 days |
| Incident Readiness | AI incident response untested - no AI-specific scenarios | Team has run AI War Game tabletop - response gaps identified and documented |
| Secure Development | Engineers building AI features with no security training | Engineers understand prompt injection, excessive agency, and secure AI design patterns |
Tools We Use
Frequently Asked Questions
Who is this training designed for?
We offer three distinct audience tracks: Security Team Training (covering AI attack techniques, detection methods, and incident response), Engineering & Product Training (covering secure AI development, OWASP LLM Top 10 awareness, and threat modeling for AI features), and Executive & Leadership Training (covering AI risk landscape, governance requirements, and risk-informed decision making). Most organizations benefit from delivering at least two tracks to different audiences.
What is the AI War Game exercise?
The AI War Game is a facilitated tabletop exercise where your team defends against a simulated AI attack scenario. We design the scenario around your actual AI architecture - a realistic attack chain that starts with an initial access vector (for example, indirect prompt injection through a document your agent reads) and escalates through your real systems. Your team must detect the attack, contain it, investigate, and recover - discovering gaps in your detection capabilities and response procedures in a safe simulation environment.
Can the training be customized for our specific AI stack?
Yes - customization is the foundation of the service. During the needs assessment phase, we review your AI architecture, identify the attack techniques most relevant to your specific deployment, and design training scenarios around your actual systems. A team using LLM agents with tool access gets different scenario training than a team deploying a customer-facing chatbot. The hands-on labs use configurations that mirror your real environment.
Do you offer remote delivery?
Yes. Training and the AI War Game tabletop can be delivered fully remote via video conference with shared lab access. Remote delivery works well for distributed teams. For hands-on lab exercises, we provision cloud-based lab environments accessible to all participants before the session begins.
What ongoing resources are provided after training?
The AI Security Resource Kit includes a curated reading list of adversarial ML papers, books, and blog posts by attack category; a tools reference guide covering open-source AI security tools your team can use; MITRE ATLAS and OWASP LLM Top 10 reference cards; a structured learning path for continuing skill development; and access to a 30-minute follow-up Q&A session two weeks after training delivery.
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