AI Agents for Cybersecurity

In this course, you’ll learn how to harness the power of AI agents to transform cybersecurity. We’ll explore how autonomous systems can perceive, reason, and act in real time, far beyond the limits of traditional, manual defences.

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Course curriculum

1. Segment 00: Reading - Welcome to the Course: Course Overview
2. Segment 01: Welcome and Course Goals
1. Segment 02: Chapter Introduction
2. Segment 03: The Transformative Potential of AI and LLMs in Cybersecurity
3. Segment 04: Defining Large Language Models (LLMs) and their Architectures
4. Segment 05: Evolution of AI in Cybersecurity: From ML to Agentic AI
1. Segment 06: What are AI Agents? Definition, Characteristics, and Workflow
2. Segment 07: LLMs as the "Brain" of AI Agents: Capabilities and Limitations
3. Segment 08: Agent Autonomy Levels in Cybersecurity
4. Segment 09: Multi Agent Systems: Collaboration and Complexity
5. Segment 10: Memory and Learning in AI Agents
6. Segment 11: Adapting LLMs for Cybersecurity: Fine-Tuning, Prompt Engineering, and Augmentation
1. Segment 12: Types of Datasets in LLM for Security: Code-Based, Text-Based, and Combined
2. Segment 13: Data Pre-processing and Representation for Cybersecurity AI Models
3. Segment 14: Addressing Data Scarcity: LLMs for Data Augmentation in Cybersecurity
4. Segment 15: Reading - The Rise of AI Agents: Anticipating Cybersecurity Opportunities, Risks, and the Next Frontier
5. Segment 16: Hands-On-Learning: Drafting an AI Agent Architecture for Real-Time Threat Prioritization
6. Segment 17: Quiz - Foundations of AI Agents in Cybersecurity
1. Segment 18: Chapter Introduction
2. Segment 19: Real-Time Detection of Cyber Threats with AI
3. Segment 20: Automated Vulnerability Detection and Analysis
4. Segment 21: Malware Analysis and Classification with AI Agents
1. Segment 22: Network Intrusion Detection and Attack Classification
2. Segment 23: Detecting and Defending Against Phishing Attacks and Deceptive Language
3. Segment 24: Leveraging AI for Threat Intelligence and Attack Surface Management
1. Segment 25: AI for System Log Analysis and Anomaly Detection
2. Segment 26: Reverse Engineering and Binary Analysis with AI Assistance
3. Segment 27: AI for Understanding Security and Privacy Policies
4. Segment 28: Reading - Advancing Cybersecurity Operations with Agentic AI Systems
5. Segment 29: Hands-On-Learning: Analysing Phishing Attack with LLM
6. Segment 30: Quiz - AI Agents in Cybersecurity Operations (Detection & Analysis)
1. Segment 31: Chapter Introduction
2. Segment 32: Automating Vulnerability Repair and Patch Generation
3. Segment 33: Streamlining Incident Response Workflows and Playbooks
4. Segment 34: Post-Attack Analysis and Root Cause Identification with AI
1. Segment 35: AI for Proactive Defence and Threat Hunting
2. Segment 36: AI- Powered Risk Management and Predictive Analytics
3. Segment 37: Optimizing Cybersecurity Investments and Compliance Automation
4. Segment 38: Adaptive Decision Making and Continuous Learning in SOC Agents
5. Segment 39: Reading - How AI Agents Could Revolutionize the SOC With Human Help
6. Segment 40: Hands-On-Learning: AI-Powered Cybersecurity Analysis Activity
7. Segment 41: Quiz - AI Agents in Cybersecurity Operations (Response & Management)
1. Segment 42: Chapter Introduction
2. Segment 43: Overview of AI Agent Security Challenges: The Four Knowledge Gaps
3. Segment 44: Inherent AI-Related Vulnerabilities: Adversarial AI, Data Poisoning, and Misalignment
4. Segment 45: Agent-Specific Threats: Prompt Injection, Jailbreaking, and Supply Chain Vulnerabilities
1. Segment 46: Challenges in LLM Interpretability, Trustworthiness, and Ethical Usage
2. Segment 47: Addressing Bias and Fairness in AI Agents
3. Segment 48: Designing Responsible AI: Governance Models and Human-in-the-Loop (HITL)
1. Segment 49: Expanding LLM Capabilities and Multimodal AI
2. Segment 50: Security for LLMs and Proactive Self-Defence
3. Segment 51: The Roadmap for AI Agents in Cybersecurity: Opportunities and Future Research
4. Segment 52: Reading - Security Vulnerabilities in Autonomous AI Agents
5. Segment 53: Hands-On-Learning: Prompt Injection Attack Simulation
6. Segment 54: Quiz - Security, Ethics, and Future of AI Agents in Cybersecurity
7. Segment 55: Course Wrap-up Video
8. Segment 56: AI Agent Architecture Design for Enterprise SOC Integration

About this course

Free
57 lessons
4 hours of video content

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AI Agents for Cybersecurity

Course curriculum

Chapter 1: Introduction

Chapter 2: Introduction to AI and LLMs in Cybersecurity

Chapter 3: Core Concepts of AI Agents

Chapter 5: Datasets and Data Handling for AI Agents in Cybersecurity

Chapter 6: AI Agents in Threat Detection

Chapter 7: AI Agents in Network and Social Engineering Security

Chapter 8: Advanced Analysis Capabilities

Chapter 9: AI Agents in Incident Response

Chapter 10 : Enhancing Security Operations Centre's (SOCs) with Agentic AI

Chapter 11: Security Risks and Vulnerabilities of AI Agents

Chapter 12: Ethical Considerations and Governance Frameworks

Chapter 13: Future Directions and Advanced Concepts

About this course

Discover your potential, starting today