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Full Description
Transform cyber threat intelligence operations with multi-agent AI workflows. Automate intelligence collection, corroborate threat signals, apply structured analysis, and produce tailored, high-fidelity intelligence at scale.
Key Features
Build multi-agent AI pipelines to automate the cyber threat intelligence lifecycle
Automate threat intelligence workflows for collection and cross-source corroboration
Apply Structured Analytic Techniques to automated threat intelligence workflows
Book DescriptionCyber threat intelligence teams face growing volumes of data, evolving adversaries, and increasing demands for timely analysis. Applied AI in Cyber Threat Intelligence is your engineering toolkit for transforming manual intelligence processes into scalable workflows using agentic AI and Python.
Designed for threat intelligence analysts, security engineers, and SOC practitioners, this book takes a practical approach to operationalizing threat intelligence with multi-agent AI systems. You will build specialized AI agents that automate the intelligence lifecycle. Using with the Google Agent Development Kit (ADK) alongside Machine Learning techniques, you will build automated systems that score intelligence requirements, generate structured collection plans, and corroborate cross-source signals to determine breach fidelity.
You will also integrate Structured Analytic Techniques (SATs) into your AI pipelines to mitigate cognitive bias. You will build agents that generate visual argument maps, tailor intelligence products for different audiences, automate secure primary research, forecast threat actor behavior, and strengthen threat hunting operations. By the end of this book, you will be able to develop practical AI-powered cyber threat intelligence workflows that improve scale, consistency, and decision support.What you will learn
Build multi-agent AI pipelines for CTI workflows
Automate intelligence requirements and collection planning
Corroborate cross-source threat signals to score breach fidelity
Scaffold Structured Analytic Techniques with AI agents
Generate argument maps and tailored intelligence reports
Automate secure primary research, forecasting, and threat hunting
Who this book is forThis book is for cyber threat intelligence analysts looking to scale their daily workflows with agentic AI and automation. Security engineers, detection engineers, and SOC practitioners seeking to automate intelligence operations will also benefit. To get the most out of the hands-on projects, you should have an intermediate understanding of cybersecurity, experience with threat intelligence methodologies, and basic Python 3.x scripting skills. No prior expertise in AI expert is required.
Contents
Table of Contents
Applying the Intelligence Lifecycle to Cybersecurity
Scoping Automation for Threat Intelligence
Discovering The Science of Data
Grasping the Machine Learning Fundamentals
Diving into Artificial Intelligence
Prioritizing with Planning and Direction
Automating Data Collection
Processing Data Artifacts
Applying Analytic Techniques
Automating Intelligence Production
Amplifying Intelligence Dissemination
Applying Feedback Loops
Putting it all Together
Building and Using Predictive Analytics
Augmenting Threat Hunting Campaigns
Integrating with the Detection Engineering Pipeline
Automating Primary Research
Understanding Ethics, Privacy, & Emerging Threats
