AI Phishing Defense Training
AI-generated phishing attacks are 96% as effective as human-crafted ones. Train your team to detect the threats that traditional training misses.
Start TrainingWhat You'll Learn
Four modules covering the new generation of AI-powered threats and practical defense strategies your team can apply immediately.
AI-Generated Email Detection
Learn why AI-crafted phishing emails bypass traditional red flags and how to use contextual analysis, behavioral indicators, and verification protocols to catch them.
Deepfake Voice & Video Defense
Understand how attackers clone voices and create real-time video deepfakes. Build verification procedures that protect against audio and visual impersonation attacks.
AI-Powered Social Engineering
Discover how attackers use AI to automate spear phishing at scale, generate personalized pretexts, and eliminate the language errors that once made phishing obvious.
AI Tool Security & Data Leakage
Protect your organization from data leaks through AI chatbots, shadow AI tools, and prompt injection attacks targeting AI assistants integrated into your workflows.
Course Modules
A structured learning path covering AI-generated threats, deepfake defense, and safe AI tool usage for your entire organization.
The AI Threat Landscape
- How LLMs generate convincing phishing
- AI translation removing language red flags
- Automated spear phishing at scale
- Real examples of AI-generated attacks
- Why traditional phishing training isn't enough
Detecting AI-Crafted Phishing
- Why AI emails lack traditional red flags
- Contextual analysis over grammar checking
- Behavioral indicators of AI-generated content
- Multi-factor verification for high-risk requests
- AI phishing simulation exercises
Deepfakes & Voice Cloning
- How attackers clone voices from public recordings
- Video deepfake technology and real-time manipulation
- The $25M deepfake CFO video call case study
- Verification protocols for voice and video requests
- When to demand in-person or secondary confirmation
Securing AI Tools & Preventing Data Leaks
- Risks of pasting company data into AI chatbots
- Shadow AI tools and unapproved integrations
- Prompt injection attacks targeting AI assistants
- Organizational AI use policies and guidelines
- Protecting intellectual property from AI training data
Real-World AI Attack Examples
These scenarios are based on actual AI-powered attacks that have already caused significant damage to organizations worldwide.
The AI-Written CEO Email
An LLM-generated email perfectly mimicked the CEO's writing style, referencing real projects and using correct internal terminology. No grammar errors, no urgency red flags - just a convincing request to update payment details.
The Cloned Voice Wire Transfer
Attackers cloned a CFO's voice from earnings call recordings and called the finance team requesting an urgent wire transfer. The voice was indistinguishable from the real executive.
The Personalized LinkedIn Campaign
AI scraped LinkedIn profiles to generate thousands of personalized connection requests and follow-up messages, each referencing the target's specific role, company, and recent posts.
The ChatGPT Data Leak
An employee pasted proprietary source code into a public AI chatbot for debugging help. The code appeared in the AI's training data and was later surfaced in responses to other users.
Essential for Every Team
AI-powered threats target everyone. This course prepares your entire organization to recognize and respond to the next generation of attacks.
Security Teams
Lead AI threat defense strategy
Finance & Legal
Defend against deepfake fraud
All Employees
Recognize AI-generated threats
IT & Engineering
Secure AI tool integrations
Common Questions
How is AI phishing different from traditional phishing?
Can we still use AI tools safely after this training?
How often are AI phishing tactics updated?
Is this relevant for technical teams too?
Stay Ahead of AI-Powered Threats
Traditional security training can't keep up with AI-generated attacks. Equip your team with the skills to detect what others miss.