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2-Day Training: AI SecureOps: Attacking & Defending AI Applications & Agents
Wednesday November 4, 2026 9:00am - 5:00pm PST
TBA
2-Day Training: November 3-4, 2026
Level: Intermediate
Trainers: Abhinav Singh

To register, please purchase your training ticket here. Training and conference are two separate ticket purchases.

Can prompt injections lead to complete infrastructure takeovers? Could AI agents, MCP-connected tools, or poisoned external context be abused to compromise backend services? Can data poisoning in AI copilots impact a company’s stock? Can jailbreaks create false crisis alerts in security systems? This immersive, CTF-styled training in GenAI, LLM, agent, and MCP security dives into these pressing questions. Engage in realistic attack-and-defense scenarios focused on real-world threats, from prompt injection and remote code execution to backend compromise, tool abuse, unsafe agent orchestration, trust and authorization failures. Tackle hands-on challenges with live AI applications to understand vulnerabilities and build robust defenses. Learn how to build a comprehensive security pipeline, master AI red and blue team strategies, secure tool-connected and agentic systems, implement resilient guardrails for LLMs, and handle incident response for AI-based threats. You will also explore governance, Responsible AI, and enterprise security patterns for modern AI ecosystems.

By the end of this training, you will be able to:

- Exploit vulnerabilities in AI applications to achieve code and command execution, uncovering scenarios such as instruction injection, agent control bypass, remote code execution for infrastructure takeover, as well as chaining multiple agents for goal hijacking.
- Conduct AI red-teaming using adversary simulation, OWASP LLM Top 10, and MITRE ATLAS frameworks, while applying AI security and ethical principles in real-world scenarios.
- Execute and defend against adversarial attacks, including prompt injection, data poisoning, jailbreaks, agentic attacks, and insecure tool-connected workflows.
- Perform advanced AI red and blue teaming through multi-agent auto-prompting attacks, implementing a 3-way autonomous system consisting of attack, defend, and judge models.
- Build and deploy enterprise-grade LLM defenses, including custom guardrails for input/output protection, security benchmarking, penetration testing of LLM agents, and defensive controls for MCP-enabled integrations.
- Understand MCP fundamentals and assess how they expand the attack surface of modern AI systems.
- Establish a comprehensive LLM SecOps process to secure the supply chain from adversarial attacks and create a robust threat model for enterprise applications, including AI systems connected to external tools and data sources through MCP-like architectures.
- Implement an incident response and risk management plan for enterprises developing or using AI services.
Speakers
avatar for Abhinav Singh

Abhinav Singh

Cyber Security Research in AI,Cloud & Data., Wingback Security
Abhinav Singh is a security leader, founder of Wingback Security, and a globally recognized speaker and trainer focused on securing enterprise AI systems. He has been involved with AI fellowship and research communities including MATS, PIBBSS, CSA, AIUC, and the Foresight Institute... Read More →
Wednesday November 4, 2026 9:00am - 5:00pm PST
TBA
  2-Day Training

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