AI Security for Autonomous AI Agents

About This Course

This course equips participants with essential knowledge and practical skills to secure autonomous AI agents operating across business systems, data sources, digital tools, and multi-step workflows. Learners will examine how platforms such as OpenClaw, Hermes Agent, and Paperclip enable AI agents to perform tasks, use tools, retain context, coordinate work, and collaborate within multi-agent environments.

Participants will explore security risks associated with autonomous agents, including prompt injection, malicious instructions, excessive permissions, confidential data exposure, unsafe tool execution, identity misuse, compromised memory, unauthorised system changes, and uncontrolled agent-to-agent communication. They will learn to assess the potential business impact of agent actions and identify vulnerabilities throughout the agent lifecycle.

The course covers practical safeguards such as identity and access management, least-privilege permissions, isolated execution, tool allowlists, secure credential handling, memory protection, action approval, activity logging, output validation, and emergency shutdown procedures. Learners will apply these controls to OpenClaw and Hermes Agent workflows and establish governance measures for coordinating and supervising multiple agents with Paperclip.

Through hands-on scenarios, participants will configure secure agent workflows, assess agent behaviour, investigate suspicious activities, respond to incidents, and improve security controls. Emphasis is placed on human oversight, accountability, privacy, transparency, ethical use, and compliance with organisational policies.

By the end of the course, learners will be able to evaluate risks and implement security controls for autonomous AI agents, enabling organisations to adopt OpenClaw, Hermes Agent, and Paperclip more safely and responsibly.