AI TRAINING

AI for Cybersecurity Operations

Equip SOC teams to deploy, tune, and defend AI-augmented threat detection and response workflows.

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Format: programme
Duration: 24-40h
Level: practitioner
Group size: 6-20
Price / participant: €3K-€5K
Group price: €18K-€45K
Audience: SOC analysts, threat intelligence analysts, security engineers, and CISOs at mid-to-large organisations
Prerequisites: Working experience in a SOC or security engineering role; familiarity with SIEM basics and common threat frameworks (MITRE ATT&CK); no prior ML knowledge required

What it covers

This practitioner-level programme trains security operations professionals to integrate AI and machine learning into core cybersecurity workflows, including threat detection, phishing prevention, and automated incident response via SIEM/SOAR platforms. Participants work through hands-on labs simulating real attack scenarios and learn to identify adversarial AI threats such as prompt injection and model poisoning targeting internal AI systems. The format combines instructor-led sessions with live tooling exercises on platforms like Microsoft Sentinel, Splunk, and CrowdStrike. Graduates leave with a repeatable AI-augmented SOC playbook they can deploy within their organisation.

What you'll be able to do

Configure an AI-based anomaly detection rule within a SIEM platform and explain the model's decision logic to stakeholders
Build and test an automated SOAR playbook that triages phishing alerts using an NLP classifier
Identify and document prompt injection vulnerabilities in an enterprise-facing AI assistant or copilot
Conduct a red-team exercise simulating adversarial attacks against an AI-augmented SOC tool and propose mitigations
Produce a governance checklist for deploying AI models in a regulated security operations environment

Topics covered

AI-powered threat detection: supervised and unsupervised anomaly detection models
SIEM/SOAR automation with AI: use cases in Microsoft Sentinel, Splunk SOAR, and Palo Alto XSOAR
Phishing and social engineering prevention using NLP-based classifiers
Adversarial AI threats: prompt injection, model poisoning, and data exfiltration via LLMs
Securing internal AI systems and copilots deployed in enterprise environments
Automated incident triage and response playbook design
Threat intelligence enrichment using generative AI and LLM-based analysis
Compliance and governance considerations for AI in security operations

Delivery

Delivered as a blended programme over three to five days on-site or via interactive remote sessions. Approximately 60% of time is hands-on lab work using pre-configured sandboxed environments replicating real SIEM/SOAR stacks. Participants receive a lab workbook, threat scenario library, and AI-augmented SOC playbook template. Remote delivery uses a dedicated virtual lab environment accessible throughout the programme. A follow-up Q&A session is typically offered four weeks post-training to review real-world implementation challenges.

What makes it work

Involving SOC tier-1 and tier-2 analysts alongside security architects to ensure operational buy-in and practical relevance
Running the training against the organisation's own (anonymised) log data and alert history to ground exercises in real context
Establishing a post-training AI model review cadence so detection models are retrained as threat landscapes evolve
Pairing training with a formal AI security policy update to embed new practices into SOC operating procedures

Common mistakes

Deploying AI detection models without baseline tuning, leading to alert fatigue from high false-positive rates
Overlooking adversarial threats specific to AI systems, leaving internal copilots and LLM integrations unaudited
Treating SOAR automation as a black box without analyst understanding, causing misplaced trust in automated triage decisions
Skipping governance and compliance review for AI tooling, creating liability under NIS2, GDPR, or sector-specific regulations

When NOT to take this

This programme is not the right fit for organisations that have not yet deployed a SIEM solution or established basic security monitoring practices, foundational security operations training should come first before introducing AI augmentation.

Providers to consider

Sources

Use cases this training unlocks

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