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Stanford University’s AI Security (XACS134) is an online, on-demand course designed for professionals seeking to understand AI vulnerabilities and defenses. Students learn to develop secure and trustworthy AI applications through a program that combines real-world case studies with practical exercises to teach them AI system security, adversarial threats, and their defense methods, and prompt injection and model extraction.
The Program offers:
Identify vulnerabilities in AI systems, including prompt injection, data poisoning, model extraction, and adversarial examples.
Understand how AI misapplications and overestimation of AI capabilities introduce risks.
Assess security implications of foundation models, retrieval-augmented systems, and multi-agent AI.
Apply emerging defenses, such as verifiable training, secure code generation, and prompt-level protections.
Analyze real-world breaches and misuse cases to understand threat patterns.
Explore ongoing research opportunities and innovations in AI security.
The course delivers its content online, enabling students to enroll at their convenience and access the materials for 60 days while studying at their chosen speed. The program charges a tuition fee of $545 and provides a detailed practical knowledge about AI security to cybersecurity professionals, software developers, and AI specialists.
Foundations of AI and Cybersecurity: Understanding AI’s dual-use nature and integration with traditional security principles.
AI System Architectures and Security Risks: Study foundation models, RAG, and agentic AI vulnerabilities.
Security Considerations for AI Misapplications: Learn risks of over-relying on AI or using it beyond the intended scope.
Adversarial Methods in AI Systems: Examine attacks during training, inference, and deployment.
Real-World AI Breaches, Attacks, and Misuses: Analyze incidents like deepfakes, model leaks, and AI agent vulnerabilities.
Defending and Verifying AI Systems: Implement prompt defenses, secure training, auditing, and cryptographic verification.
The Future of AI & Cybersecurity: Insights from industry experts on emerging architectures, security challenges, and skill development.
People who want to attend this training program need no previous coding skills because the program only requires them to have basic AI knowledge.
The program stands as appropriate training for professionals working in cybersecurity and artificial intelligence development and technical leadership roles.
The researchers want to study AI security through their work at the artificial intelligence laboratory in actual operational settings.
Stanford's AI Security course delivers academic excellence together with practical application. The program taught by Dan Boneh, Neil Daswani, and John Mitchell starts with practical exercises and actual security incidents and new protective measures. The program develops practical skills through system understanding, which modern AI and cybersecurity professionals need to succeed.
The program at Stanford University trains professionals to identify AI system weaknesses, which they will then analyze and resolve through mitigation techniques. The program provides students with online instruction, practical training, and real-world case studies to teach them how to create secure AI applications that can handle future security challenges.
