Session 4 of 7

The sessions collectively addressed agentic AI threat modeling, focusing on vulnerabilities in multi-agent systems across various platforms, including Palo Alto Networks, Cisco, and the Maestro framework. 

Key topics included memory manipulation, tool misuse, and identity misconfigurations, with specific attack scenarios illustrating how malicious actors can manipulate agents to perform unauthorized actions, escalate privileges, or compromise data integrity. Mitigation strategies emphasized threat modeling, enhanced identity management, proactive monitoring, and implementing security layers like dual token standardization. Additionally, the discussions underscored the importance of integrating security measures during the design phase to safeguard against evolving agentic threats.