IT Security
AI for SOC Analysts
This practical course helps professionals master AI for SOC analysts, alert enrichment, investigation support, detection tuning, reporting, and safe use controls. The program connects key concepts, real use cases, risks, tools, and operational decisions so participants can apply the learning in their work environment. It can be tailored to the organization’s sector, internal systems, participant maturity, and performance objectives.
Objectives
- Understand the concepts, challenges, and use cases related to AI for SOC analysts, alert enrichment, investigation support, detection tuning, reporting, and safe use controls.
- Identify the data, systems, processes, and stakeholders required for effective implementation.
- Assess risks, limitations, governance requirements, and practical control points.
- Use methods, tools, and templates to structure analysis and decision-making.
- Translate learning into action plans, recommendations, and measurable improvement opportunities.
- Adapt the approach to the operating context, team maturity, and business objectives.
Target audience
- Cybersecurity and IT security professionals
- SOC analysts, infrastructure teams, and operations teams
- Risk, audit, compliance, and governance professionals
- System, network, cloud, and OT administrators
- IT managers responsible for security posture
Program outline
A clear structure for the learning journey.
Outline points are grouped in one designed block instead of being treated as separate module cards.
01AI Use Cases for SOC Analysts and Detection Teams4 topics
- Foundation for AI Use Cases for SOC Analysts and Detection Teams: application, analysis, and review points linked to the module
- Terminology and decisions in AI Use Cases for SOC Analysts and Detection Teams: application, analysis, and review points linked to the module
- Inputs required for AI Use Cases for SOC Analysts and Detection Teams: application, analysis, and review points linked to the module
- Typical mistakes around AI Use Cases for SOC Analysts and Detection Teams: applied exercise and practical decision from a realistic scenario
02Alert Summarization, Entity Enrichment, and Investigation Support4 topics
- Current-state mapping for Alert Summarization, Entity Enrichment, and Investigation Support: application, analysis, and review points linked to the module
- Examples and scenarios involving Alert Summarization, Entity Enrichment, and Investigation Support: application, analysis, and review points linked to the module
- Diagnostic questions about Alert Summarization, Entity Enrichment, and Investigation Support: application, analysis, and review points linked to the module
- Evidence produced through Alert Summarization, Entity Enrichment, and Investigation Support: applied exercise and practical decision from a realistic scenario
03Prompting for Triage, Timelines, Hypotheses, and Reports4 topics
- Design considerations for Prompting for Triage, Timelines, Hypotheses, and Reports: application, analysis, and review points linked to the module
- Roles and responsibilities in Prompting for Triage, Timelines, Hypotheses, and Reports: application, analysis, and review points linked to the module
- Exceptions and constraints affecting Prompting for Triage, Timelines, Hypotheses, and Reports: application, analysis, and review points linked to the module
- Quality checks for Prompting for Triage, Timelines, Hypotheses, and Reports: applied exercise and practical decision from a realistic scenario
04AI Risks: Hallucination, Data Leakage, Prompt Injection, and Bias4 topics
- Operating model for AI Risks: Hallucination, Data Leakage, Prompt Injection, and Bias: application, analysis, and review points linked to the module
- Tools and workflow steps in AI Risks: Hallucination, Data Leakage, Prompt Injection, and Bias: application, analysis, and review points linked to the module
- Handoffs and approvals around AI Risks: Hallucination, Data Leakage, Prompt Injection, and Bias: application, analysis, and review points linked to the module
- Escalation points in AI Risks: Hallucination, Data Leakage, Prompt Injection, and Bias: applied exercise and practical decision from a realistic scenario
05Detection Engineering with AI Assistance4 topics
- Performance measures for Detection Engineering with AI Assistance: application, analysis, and review points linked to the module
- Review routines after Detection Engineering with AI Assistance: application, analysis, and review points linked to the module
- Improvement actions for Detection Engineering with AI Assistance: application, analysis, and review points linked to the module
- Sustaining discipline around Detection Engineering with AI Assistance: applied exercise and practical decision from a realistic scenario
06Human Review, Approval, Evidence Quality, and Governance4 topics
- Advanced scenarios in Human Review, Approval, Evidence Quality, and Governance: application, analysis, and review points linked to the module
- Failure patterns seen in Human Review, Approval, Evidence Quality, and Governance: application, analysis, and review points linked to the module
- Coordination challenges during Human Review, Approval, Evidence Quality, and Governance: application, analysis, and review points linked to the module
- Recovery actions for Human Review, Approval, Evidence Quality, and Governance: applied exercise and practical decision from a realistic scenario
07SOC Productivity Metrics and Safe AI Adoption4 topics
- Governance requirements for SOC Productivity Metrics and Safe AI Adoption: application, analysis, and review points linked to the module
- Data quality checks in SOC Productivity Metrics and Safe AI Adoption: application, analysis, and review points linked to the module
- Risk controls related to SOC Productivity Metrics and Safe AI Adoption: application, analysis, and review points linked to the module
- Value measures for SOC Productivity Metrics and Safe AI Adoption: applied exercise and practical decision from a realistic scenario
08AI-Assisted SOC Investigation Lab4 topics
- Implementation planning for AI-Assisted SOC Investigation Lab: application, analysis, and review points linked to the module
- Readiness questions before AI-Assisted SOC Investigation Lab: application, analysis, and review points linked to the module
- Pilot design for AI-Assisted SOC Investigation Lab: application, analysis, and review points linked to the module
- Lessons learned after AI-Assisted SOC Investigation Lab: applied exercise and practical decision from a realistic scenario
Materials provided
- ○ Slides used during the sessions
- ○ Group activities and practical exercises
- ○ Worksheets, checklists, and templates
- ○ Case studies relevant to the course
- ○ 4D Certificate of Completion issued by 4D Training & Consultancy
- ○ Post-course support for technical queries and guidance
Training Options
Programs can be delivered in-house, online, or in a blended format depending on your team's schedule, location, and learning objectives. When an external certificate or exam is included, certification rules and fees remain under the relevant awarding body's policies, while 4D provides the training and preparation support.
Why choose 4D
4D Training & Consultancy designs technical and professional programs around the client’s operating reality. The course can be adapted to sector requirements, internal systems, team capability, practical use cases, and the level of depth required by the audience.
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