May 14, 2026

AI Agents & GenAI for
MSSPs: Boosting Cybersecurity
Efficiency and Customization at Scale

Transform Cybersecurity with Agentic AI – Strengthen your systems with autonomous threat detection and attack simulations,
Threat Actors Are Already Using AI—Why Aren’t You? – Phishing, deepfakes, exploits: Learn their tactics, defend smarter.
Real-World Applications & Live Demo – Build your own autonomous security workflows using tools like n8n and AutoGPT.

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One-Time Offer: Free for MSSPs.

Certified Training

CISA-listed cybersecurity trainings

Expert-led, niche training for practical applications

Companies Attended Trainings

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Applied GenAI and Agent Workflows for Modern MSSPs

Equip SOC Analysts with foundational and advanced understanding of Gen AI (Generative AI) and LLMs (Large Language Models) in cybersecurity.

AI Agents & GenAI for
MSSPs: Boosting Cybersecurity Efficiency and Customization at Scale

Training Details

Training Duration

3 Hour

Exam Requirement

Certificate Support

Yes

Module	Curriculum
Module 1 Introduction – Why AI is No Longer Optional for MSSPs	MSSP business challenges: staffing limits, thin margins, client expectations How AI unlocks 2x operational efficiency What is an AI Agent? How it differs from traditional tools GenAI as a contextual partner—not just a content generator What participants will learn and how to apply it in the first week
	2.1 Comparing Open-Source vs Commercial LLMs GPT-4, Claude, Mistral, LLaMA, Zephyr, Mixtral, Falcon Performance, cost, flexibility, compliance trade-offs When to choose open-source vs when to go commercial
Module 2 The GenAI Ecosystem – Models, Platforms & Practical Use	2.2 Using HuggingFace Without Deployment Browsing and evaluating models on HuggingFace Hub Using Gradio and Text Generation Inference for testing Building quick prototypes without local setup
	2.3 Private AI: Running Your Own LLMs Ollama: running Mistral, Phi-2, LLaMA-3 locally Using LangChain with local models Hardware and privacy considerations for in-house AI
Module 3 How Threat Actors Use AI for Offensive Purposes	AI-crafted phishing campaigns (hyper-personalized emails) Deepfake voice & video for social engineering Auto-generated malware and POCs with LLMs Example: prompt an LLM to write a buffer overflow exploit Jailbreak prompts and prompt injection techniques Using RAG (Retrieval-Augmented Generation) to search CVE datasets What defenders need to learn from attackers’ AI adoption
Module 4 Applying AI in Cybersecurity Operations (MSSP-Specific)	Alert triage and prioritization with LLMs Incident summaries and ticket generation Log analysis using AI anomaly detection AI-assisted rule creation (Sigma, KQL, YARA) Data enrichment via Whois, VirusTotal, GreyNoise Threat hunting with hypothesis-based queries
Module 5 Threat Intelligence Automation with AI	Parsing dark web forums with LLMs to extract IOCs Threat actor profiling through behavioral and linguistic patterns Auto-summarizing reports for clients Correlating intelligence from multiple sources Brand monitoring: tracking mentions and threats in real time Scheduled report generation based on client segment
Module 6 Hands-On AI Agent Use Cases (With Real Tools)	6.1 AI Agent Types and Platforms Open-source: CrewAI, LangGraph, Autogen Studio Commercial: Adept, Cognosys, AgentHub Low-code: n8n, Flowise, Superagent, TaskWeaver
	6.2 Practical Scenarios Using n8n Phishing Detection Engine Email → Parser → LLM classifier → Risk scorer → SIEM output Dark Web Monitoring Pipeline Scrape → LLM summarize → IOC extractor → Dashboard alert Custom Client Request Handler LLM + API + prompt chain to generate solutions on the fly RAG-based pipelines: building AI that learns from your knowledge base
Module 7 Understanding MCP – Modular Cybersecurity Platforms	MCP architecture: microservices + plugin layer + agent brain Secure deployment using Docker/Kubernetes Open-source components powering MCP (Streamlit, FastAPI, LangChain) Customizable reporting systems built with MCP Role of AI agents in modular solution delivery How MSSPs can evolve from service providers to platform providers
Module 8 Build-Your-Own AI Solutions	Create a Dark Web Monitoring tool in under a week Build an Attack Surface Management tool using LLMs and MCP servers Phishing Detection pipeline using AI + Email Analysis UI layer: Deepsite, Lovable, Replit for visual dashboards Backend: prompt engineering, API orchestration, vector storage On-demand solution building for MSSP clients without full product cycles
Module 9 AI-Powered Reporting and Custom Security Dashboards	Region, country, industry, and org-specific dashboards Integrating client data sources, logs, and intelligence feeds APIs for dynamic data pull (e.g., GeoIP, Threat Intel, CVE) Using MCP + Wipe Coding Tools (low-code) to build dashboards Visuals, recommendations, and summaries with GenAI How to generate executive-level reports weekly with zero analyst hours
Module 10 Everyday Productivity Tools for MSSP Teams	Meeting assistants (Fireflies, Otter, Fathom) for auto-notetaking Interview summarization and scoring (Metaview, Tactiq) AI role-playing tools for sales and SOC scenario training Using AI to write customer summaries, reports, marketing content Task automation with Notion AI, Superhuman, Magical AI Cross-team integrations: AI copilots for sales, marketing, and analysts

Training Goals

Hands-on Labs, Demos, and Interactive Discussions.

Demonstrate how threat actors exploit AI for offensive strategies and how SOC teams can counteract these with defensive AI techniques.

Empower SOC Analysts to automate routine tasks, accelerate incident response, and optimize threat detection using AI.

Introduce Agentic AI for automating SOC workflows and real-time threat intelligence.

Ensure compliance understanding while leveraging AI for regulatory adherence.

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Apply Now to Secure Your Spot – Limited Seats Available!

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Frequently Asked Questions

What is the main goal of the Mastering Cyber Security Sales Training?

The main goal is to equip MSSP sales teams with the skills to effectively sell cybersecurity services, identify and engage leads, and ultimately increase revenue.

Who should attend this training?

This training is ideal for SOC analysts, cybersecurity engineers, researchers, red-teamers, and AI-curious security professionals aiming to integrate real-world AI tools and agentic systems into their operational environments.

What topics are covered in the training?

The training covers LLM foundations, cloud vs local deployment, prompt engineering, AI red teaming, deepfake/phishing simulation, SOC automation (log parsing, playbook generation), threat intelligence clustering, compliance automation, and building AI agents using tools like n8n, Tracecat, and LLMStudio.

How long is the training program?

The core program spans 2 intensive day, structured into 5 modules with theory and hands-on labs. Participants can revisit content asynchronously, with full access to resources and lab environments.

What is the cost of the training?

Free for SOCRadar Customers, Partners, and the First 99 Applicants!

How does this training help improve sales strategies?

Will there be any hands-on exercises or practical workshops?

Absolutely. Every module includes lab sessions—such as deploying LLMs locally, crafting phishing emails with AI, generating IR playbooks, simulating prompt injections, parsing logs, and building multi-agent security workflows using real tools like LLMStudio, WormGPT, and Tracecat.

How can SOCRadar's tools and services be utilized in this training?

SOCRadar’s threat intel feeds, CVE insights, and brand monitoring data can be integrated into GenAI workflows using techniques covered in the training (like RAG, IOC enrichment, and automated bot monitoring), making threat detection and reporting even more contextual and actionable.

Is there any certification provided upon completion?

Yes. A certificate of completion is issued after participants complete the hands-on labs and key modules, which can be used to validate AI literacy in cybersecurity operations and shared on professional platforms.