Breaking LLM Safety: Jailbreaks, Agents, and Threats

• ​Modern LLM security failures are not edge cases, they emerge from how these systems are trained, scaled, and deployed.

• ​The talk breaks down famous jailbreaks and real-world attacks to show how safety guardrails are bypassed in practice.

• ​It explores how agentic systems and MCP expand the attack surface beyond prompts into memory, tools, and orchestration.

• ​We will examine patterns behind emergent misalignment and why well behaved models can fail in unexpected ways.

• ​Finally, the session covers concrete engineering strategies to anticipate, detect, and mitigate these threats before they scale.

​About the speaker:
Mohammed Arsalan is a generative AI consultant, prompt engineer, and AI safety researcher with over five years of experience at the intersection of LLM security, NLP, and adversarial AI. Based in Bengaluru, he is a multiple-time global hackathon winner across platforms like Hugging Face, Cohere, Adobe, and MachineHack, and a Microsoft AI Startup selectee. He actively shares research and real-world insights on emerging generative AI attacks with a large professional audience.
www.linkedin.com/in/sallu-mandya/

To attend online:

• ​⁠Add to calendar: https://bit.ly/4t73B1c

• ​Gmeet link: https://meet.google.com/uiq-zbyc-ubw?hs=122&authuser=0