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.
Cyber 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.
This 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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Joe Fleurat is the Director of Intelligence at UKG with over 20 years of experience in global intelligence and cyber defense leadership. After 12 years in the US Intelligence Community as a counterterrorism analyst and intelligence officer for the FBI and Defense Intelligence Agency, he moved into the private sector to help build and scale holistic threat intelligence teams. In his current role, Joe is responsible for UKG's Threat Intelligence, Insider Prevent, Threat Hunting, and M&A Security Due Diligence missions. Outside of his corporate responsibilities, Joe volunteers as a task force analyst with Skull Games, providing analytic and operational support to law enforcement for human trafficking interdiction. Joe holds a Juris Doctor from Suffolk University Law School, a Certificate of Terrorism Studies from the University of St. Andrews in Scotland and is a Certified Cyber Counterintelligence Analyst.
Austin Nowak is a Detection Engineer & Data Scientist at UKG and holds dual bachelor's in Math & Physics and a master's in Computer Science, focusing on Machine Learning & Data Science. With over 15 years of teaching STEM subjects and more than 6 years in the security industry, Austin has worked in both startup and enterprise environments where he led multiple security data science projects, handled data strategy and management, managed technology platforms, and established security compliance programs.
Dennis Chow is an experienced security engineer and manager who has led global security teams in Fortune 500 industries with over 14 years of experience. Dennis started from an IT and security analyst background, working upwards to engineering, architecture, and consultancy in blue- and red-team-focused roles. In 2015, the US Department of Health and Human Services awarded Dennis a grant to standardize cyber threat intelligence sharing for the entire US healthcare vertical. In that time, Dennis achieved over 30 certifications and became GIAC Security Expert #288. During his time at Amazon Web Services (AWS), Dennis worked as a professional services consultant, focusing on security transformation for detection-focused automation.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Paperback. Etat : new. Paperback. 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 FeaturesBuild multi-agent AI pipelines to automate the cyber threat intelligence lifecycleAutomate threat intelligence workflows for collection and cross-source corroborationApply Structured Analytic Techniques to automated threat intelligence workflowsBook 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 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 learnBuild multi-agent AI pipelines for CTI workflowsAutomate intelligence requirements and collection planningCorroborate cross-source threat signals to score breach fidelityScaffold Structured Analytic Techniques with AI agentsGenerate argument maps and tailored intelligence reportsAutomate secure primary research, forecasting, and threat huntingWho 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. Supercharge your cyber threat intelligence operations by building multi-agent AI workflows. Build automated pipelines to collect and validate threat signals, apply structured analysis, and scale adversary research using Python. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781806020317
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Paperback. Etat : new. Paperback. 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 FeaturesBuild multi-agent AI pipelines to automate the cyber threat intelligence lifecycleAutomate threat intelligence workflows for collection and cross-source corroborationApply Structured Analytic Techniques to automated threat intelligence workflowsBook 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 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 learnBuild multi-agent AI pipelines for CTI workflowsAutomate intelligence requirements and collection planningCorroborate cross-source threat signals to score breach fidelityScaffold Structured Analytic Techniques with AI agentsGenerate argument maps and tailored intelligence reportsAutomate secure primary research, forecasting, and threat huntingWho 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. Supercharge your cyber threat intelligence operations by building multi-agent AI workflows. Build automated pipelines to collect and validate threat signals, apply structured analysis, and scale adversary research using Python. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9781806020317
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Paperback. Etat : new. Paperback. 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 FeaturesBuild multi-agent AI pipelines to automate the cyber threat intelligence lifecycleAutomate threat intelligence workflows for collection and cross-source corroborationApply Structured Analytic Techniques to automated threat intelligence workflowsBook 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 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 learnBuild multi-agent AI pipelines for CTI workflowsAutomate intelligence requirements and collection planningCorroborate cross-source threat signals to score breach fidelityScaffold Structured Analytic Techniques with AI agentsGenerate argument maps and tailored intelligence reportsAutomate secure primary research, forecasting, and threat huntingWho 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. Supercharge your cyber threat intelligence operations by building multi-agent AI workflows. Build automated pipelines to collect and validate threat signals, apply structured analysis, and scale adversary research using Python. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9781806020317
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Taschenbuch. Etat : Neu. Applied AI in Cyber Threat Intelligence | Build agentic workflows to scale the intelligence lifecycle | Joe Fleurat (u. a.) | Taschenbuch | Englisch | 2026 | Packt Publishing | EAN 9781806020317 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 136447736
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Paperback. Etat : New. Supercharge your cyber threat intelligence operations by building multi-agent AI workflows. Build automated pipelines to collect and validate threat signals, apply structured analysis, and scale adversary research using Python. N° de réf. du vendeur LU-9781806020317
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