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Threat Hunting Professional Training In Hyderabad
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In Infosectrain, Grab the Threat Hunting Training to achieve a deep understanding of Threat Hunting techniques and the role of Threat Hunters. Our training is curated with the in-depth concepts of Threat Hunting methods and helps you to get certified for the Cyber Threat Hunting Professional exam.

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Course Highlights

  • 40-Hour LIVE Instructor-led Training
  • AI-Assisted Workflows Embedded Across Every Module
  • Integrated Capstone: Simulate a Real Enterprise Breach End-to-End
  • Hands-on Labs Across Threat Hunting, Forensics, Malware Analysis
  • Build and Test YARA Rules, SOAR Playbooks & Detection Logic
  • Master the Investigation Lifecycle: From Alert to Executive Reporting
  • Learn from Industry Experts with Real-World DFIR Experience
  • Career Guidance, Mentorship, Extended Post Training Support
  • Access to Recorded Sessions

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Course Description

Security threats don’t wait, and neither should your investigations. The Advanced Threat Hunting Digital Forensics & Incident Response (DFIR) Training from InfosecTrain is built for security professionals ready to move beyond alert triage and take full ownership of enterprise-scale investigations. Participants develop elite, hands-on skills across threat hunting, digital forensics, incident response, and detection engineering, tackling real attack scenarios from first alert to final report.

AI-assisted workflows are embedded throughout, teaching participants to accelerate investigations without compromising analytical judgment. The course culminates in an integrated capstone challenge that simulates a realistic enterprise breach, from the first alert through to containment, reporting, and post-incident detection backlog creation.

Target Audience

This training is ideal for:

  • SOC Analysts
  • Tier 1 analysts who want to move into strong Tier 2 roles
  • Tier 2 analysts who want to become advanced Tier 3 analysts
  • Security analysts who want to move beyond alert triage into full investigation ownership
  • Security professionals who are looking to equip AI-based workflows
  • Incident Responders
  • Responders who want stronger endpoint, identity, memory, disk, and network investigation skills
  • Analysts who need to produce clear technical and executive reports
  • Threat Hunters
  • Professionals who want to build ATT&CK-based hunt hypotheses
  • Detection Engineers
  • Security engineers building SIEM, EDR, and SOAR detections
  • Forensic analysts who want to expand into enterprise threat hunting
  • Managers who want to understand what strong L2 and L3 capability should look like

Pre-Requisite

Participants are recommended to have:

  • Basic understanding of Windows and Linux OS
  • Familiarity with networking concepts, SOC operations, and common attack techniques
  • Exposure to log analysis, DFIR concepts, and SIEM query writing
  • Basic scripting knowledge: PowerShell, Python, or Linux command line
  • Willingness to use and validate AI-assisted workflows
  • At least 1 year of experience in IT, SOC, security, or equivalent hands-on lab experience
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Course Objectives

Upon successful completion of the training, participants will be able to:

  • Build and execute ATT&CK-driven threat hunting hypotheses across enterprise environments
  • Detect and investigate persistence, lateral movement, and credential abuse using multi-source telemetry
  • Hunt identity-based threats across endpoint, Active Directory, and cloud environments, including M365, Entra ID, and AWS
  • Perform memory and disk forensics to uncover hidden threats, attacker activity, and forensic artifacts
  • Analyze network traffic to identify C2 communication, beaconing, DNS tunneling, and data exfiltration
  • Conduct malware triage and analyst-level reverse engineering to extract IOCs and behavioral indicators
  • Write and tune production-grade detections across SIEM, EDR, and SOAR platforms
  • Build and automate SOC workflows using SOAR playbooks and AI-assisted tooling
  • Apply AI-assisted workflows to accelerate investigations while maintaining full analyst validation
  • Produce executive-ready and technically defensible incident reports
  • Manage the full incident response lifecycle from initial alert to containment and post-incident detection backlog

Course Content

  • Module 1: Enterprise Threat Hunting and DFIR Operating Model
    • Modern SOC L2 and L3 responsibilities
    • Threat hunting vs detection engineering vs incident response
    • Investigation lifecycle from alert to executive reporting
    • ATT&CK-driven hypothesis building
    • Evidence types in enterprise investigations
    • Telemetry quality and blind spot mapping
    • Analyst decision-making during uncertainty
    • Common mistakes in L2 to L3 escalation
    • Building an investigation notebook
    • AI usage boundaries in real investigations
    • Hands-On Labs:
      • Build the analyst investigation workspace
      • Map an enterprise attack story to ATT&CK
      • Convert a weak SOC alert into a full investigation plan
      • Create a telemetry coverage and blind spot matrix
      • Use AI to generate hypotheses, then manually validate or reject them
  • Module 2: Production Telemetry, Log Normalization, and SIEM Hunting
    • Windows event logs that actually matter
    • Sysmon and EDR-style telemetry
    • Authentication telemetry from endpoints and domain controllers
    • DNS, proxy, firewall, VPN, and web logs
    • Cloud and identity log concepts
    • OCSF style normalization thinking
    • Time synchronization and timestamp issues
    • Field mapping across SIEM platforms
    • Detection logic portability
    • Query writing strategy for SPL, KQL, EQL, Sigma, and SQL style syntax
    • Hands-On Labs:
      • Ingest or load the prebuilt enterprise telemetry pack
      • Normalize raw logs into investigation-ready fields
      • Write the same hunt across SPL, KQL, EQL, and Sigma
      • Use AI to translate queries, then test for logic drift
      • Build a reusable hunt notebook
  • Module 3: Detection Engineering in Production
    • Detection engineering lifecycle
    • Detection objective and data requirement
    • Behavior-based vs IOC-based detection
    • Atomic detection vs correlation detection
    • Thresholds, baselines, and suppression logic
    • False positive analysis
    • Detection testing with replayed attack data
    • Detection tuning without killing visibility
    • Detection documentation
    • Converting hunts into production detections
    • Hands-On Labs:
      • Write a detection from an ATT&CK technique
      • Test detection against clean and malicious telemetry
      • Tune noisy detection without losing true positives
      • Convert detection into Sigma and SIEM-specific logic
      • Use AI to draft detection logic, then perform analyst QA
  • Module 4: Advanced Persistence Hunting
    • Registry run keys and autoruns
    • Services and drivers
    • Scheduled tasks
    • WMI event subscriptions
    • DLL search order hijacking
    • COM hijacking
    • Startup folders and logon scripts
    • PowerShell profile abuse
    • Living off the land persistence
    • Persistence timeline reconstruction
    • Hands-On Labs:
      • Hunt registry persistence using endpoint telemetry
      • Investigate suspicious scheduled tasks
      • Detect WMI event subscription persistence
      • Identify COM hijacking indicators
      • Build a persistence timeline from multiple artifacts
      • Use AI to cluster persistence evidence, then verify manually
  • Module 5: Identity Threat Hunting (Endpoint and Cloud)
    • Windows authentication essentials for hunters
    • LSASS access and credential dumping indicators
    • Credential theft via LOLBins
    • DPAPI and browser credential theft indicators
    • Reading AD attack signatures without a range: Kerberoasting (4769 RC4), AS-REP roasting (4768 no preauth), Pass-the-Hash (4624 type 3 NTLM anomalies), DCSync (4662 replication GUIDs), Golden and Silver Ticket
    • Service account and privileged account abuse hunting
    • Cloud identity attacks: OAuth illicit consent grant, device code phishing, AiTM session and token theft, MFA fatigue, PRT abuse, Golden SAML
    • Hands-On Labs:
      • Analyze failed and successful authentication chains
      • Investigate LSASS access from endpoint telemetry
      • Identify Kerberoasting and DCSync signatures in prebuilt DC logs
      • Hunt OAuth consent abuse and malicious inbox rules in M365
      • Detect AiTM token theft and MFA fatigue in sign-in logs
      • Use AI to suggest pivots & then validate using raw evidence
  • Module 6: Lateral Movement and Remote Execution Hunting
    • Admin share abuse
    • PsExec style execution
    • WMI remote execution
    • PowerShell remoting
    • RDP abuse
    • SMB lateral movement patterns
    • WinRM activity
    • Remote service creation
    • VPN and jump server investigations
    • Lateral movement chain reconstruction
    • Source host, target host, and user mapping
    • Hands-On Labs:
      • Hunt remote service creation
      • Investigate WMI-based lateral movement
      • Trace RDP movement through logs
      • Identify suspicious SMB admin share activity
      • Use AI to build an ATT&CK Flow Graph
  • Module 7: Network Threat Hunting and C2 Detection
    • Network hunting methodology
    • DNS hunting
    • HTTP and HTTPS beaconing
    • TLS and certificate indicators
    • Domain fronting concepts
    • Suspicious user agents
    • Long connection and low-and-slow patterns
    • DNS tunneling
    • Data exfiltration signals
    • PCAP to SIEM workflow
    • Network timeline reconstruction
    • Statistical hunting without overcomplication
    • Hands-On Labs:
      • Detect beaconing using proxy and DNS logs
      • Hunt DNS tunneling from noisy traffic
      • Analyze PCAP for C2 behavior
      • Detect suspicious TLS patterns
  • Module 8: Malware Triage and Analyst-Level Reverse Engineering
    • Safe malware handling workflow
    • Static triage
    • Strings, imports, and sections
    • Packer and obfuscation indicators
    • Dynamic behavior analysis
    • Process, file, registry, and network behavior
    • YARA rule development
    • Disassembly and decompilation basics in Ghidra
    • Anti-analysis recognition as hunting signals
    • Injection and shellcode technique identification
    • Hands-On Labs:
      • Perform static triage of a suspicious binary
      • Identify process injection or hollowing indicators
      • Draft and test a YARA rule from RE findings
      • Ghidra: locate the C2 config and decode obfuscated strings
      • Manually unpack a simple packed sample
      • Identify the injection technique in a given binary
      • Use AI to summarize functions and behaviors from tool output
  • Module 9: Memory Forensics & Cloud Threat Hunting
    • Memory acquisition considerations
    • Volatility workflow
    • Process analysis
    • DLL and handle analysis
    • M365 Unified Audit Log huntin
    • Entra ID sign-in and audit hunting
    • AWS CloudTrail fundamentals
    • Cloud privilege escalation and lateral movement signals
    • Hands-On Labs:
      • Triage a memory image
      • Identify suspicious processes and parent-child anomalies
      • Extract command line and network indicators
      • Use AI to rank suspicious Volatility output
      • Hunt a malicious OAuth app plus exfil inbox rule in M365
      • Detect service principal credential addition in Entra audit
      • AWS EC2 Analysis & Forensics
  • Module 10: Disk Forensics and Enterprise Evidence Recovery
    • Evidence handling and forensic soundness
    • Disk image triage
    • MFT analysis
    • Prefetch
    • Amcache
    • ShimCache
    • UserAssist
    • Jump Lists
    • LNK files
    • ShellBags
    • Browser artifacts
    • Recycle Bin artifacts
    • Event log extraction
    • Registry hive analysis
    • Proving execution, file access, and data staging
    • Hands-On Labs:
      • Analyze a disk image for attacker activity
      • Prove execution using multiple artifacts
      • Prove file and folder access
      • Recover deleted or staged evidence
      • Use AI to reduce timeline noise, then manually validate key events
  • Module 11: Incident Response, Containment, and Case Management
    • Incident classification
    • Scoping the incident
    • Evidence priority
    • Containment decision making
    • Eradication planning
    • Communication during an active incident
    • Legal and compliance consideration
    • Case notes and chain of custody
    • Executive reporting vs technical reporting
    • Detection backlog creation after incident closure
    • Hands-On Labs:
      • Convert investigation findings into an incident scope
      • Build containment and eradication plan
      • Write an executive incident brief
      • Write a technical incident report
      • Create post-incident detection backlog
      • Use AI to draft the first report version
  • Module 12: AI-Assisted SOC Workflows
    • Where AI helps in DFIR
    • Where AI fails in DFIR
    • Evidence summarization
    • Query generation
    • Report drafting
    • IOC extraction
    • Detection explanation
    • Local LLM vs API-based workflow
    • Prompt injection risks in evidence
    • Hallucination control
    • Analyst validation loop
    • Hands-On Labs:
      • Build an AI-assisted investigation promptbook
      • Convert natural language questions into SIEM queries
      • Summarize noisy logs without losing evidence
      • Extract IOCs from malware and network notes
      • Build a case-specific AI evidence assistant using local files
  • Module 13: SOAR & Automation
    • SOAR fundamentals and playbook as code
    • Auto-triage and enrichment (VirusTotal, AbuseIPDB, OTX free APIs)
    • Alert to case automation
    • Hands-On Labs:
      • Build an enrichment and auto-triage playbook in n8n
      • Run a phishing alert through triage end-to-end
      • Using AI to draft playbook logic
  • Module 14: Integrated Capstone – Enterprise Breach Investigation
    • Scenario: A user endpoint is compromised through phishing. The attacker establishes persistence, steals credentials, moves laterally, accesses sensitive files, uses C2, and attempts data exfiltration.
    • Hands-On Challenge:
      • Start with a limited alert context
      • Identify initial access evidence
      • Confirm persistence
      • Investigate credential theft
      • Trace lateral movement
      • Scope affected users and hosts
      • Build incident timeline
      • Prepare containment plan
      • Prepare containment plan
  • Lab Requirements
    • To get the most out of this training, participants are recommended to have the following system configuration:
    • Hardware
      • Laptop or desktop with 8 GB RAM (16 GB recommended)
      • 350-500 GB free disk space
      • Windows 10/11, macOS, or Ubuntu
      • Admin rights to install tools
      • Stable internet connection
      • Virtualization support enabled
    • Lab Environment
      • A prebuilt lab environment is provided, including memory images, disk images, network captures, and malware samples. No prior setup is required; all datasets, tools, and lab files are ready from Day 1.
    • Tools
      • All required DFIR, network analysis, and forensics tools are covered during the course. Software installation is guided by the instructor as part of the training.
    • AI Setup
      • Supports both local and API-based AI setups, giving participants flexibility based on their hardware. Full guidance is provided during the course; no prior AI tool experience required.

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Course Benefits

Threat Hunting Professional Online Training Course

Here What people are saying about InfosecTrain

Sudhara Vipin

Course and training were excellent. The Training methodology incorporated by InfoSec Train helped me to understand the concepts effectively. Looking forward to experiencing more such learning experiences with this team!

Raghavendra Surya

Excellent trainer and course materials! Very useful for future reference as well. I expect more amazing training programs and offers from InfoSecTrain that will uplift my career potential and help me towards opportunities that I have always dreamt of.

Akhil Verma

Superb session. One of the best instructors I have ever met. Very humble down to earth and very professional to handle query from the participants.

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FAQs

1. What is the purpose of threat hunting?
Effective threat hunting shortens the time between intrusion and detection, allowing attackers to cause less harm.
2. What are the 5 steps of threat hunting?

The 5 steps of threat hunting are:

  • Hypothesis
  • Collect and Process Intelligence and Data
  • Trigger
  • Investigation
  • Response/Resolution
3. What are the most difficult aspects of threat hunting?
For most SOCs, the price of licences and data storage make collecting and storing all security data for real-time and historical analysis too expensive. Querying enormous amounts of data might take a long time to respond to.
4. What tool may be used in threat hunting?
  • Security Monitoring Tools- Firewalls, antivirus, and endpoint security solutions are examples of security monitoring technologies that collect data and monitor the network.
  • SIEM Solutions- Security Information and Event Management (SIEM), assist in the handling of raw security data and enable real-time threat analysis.
5. What is the broad definition of threat hunting?
Threat hunting is the practise of locating potential attackers before they can launch an assault. Threat hunting is a proactive strategy that blends human analysis and instinct with security technologies, analytics, and threat information.
6. Which method of threat hunting is regarded as the least difficult?
By far the most simple process of hunting is searching. Searching entails using preset search parameters to find data about certain items.
7. Is threat hunting and threat detection the same thing?
Threat detection is a way of detecting known threats that is usually automated, whereas threat hunting is a creative process with a flexible methodology that focuses on the hunter seeking the hacker.
8. Which method of threat hunting is the most proactive?
The technique of proactively searching through networks or datasets to discover and respond to sophisticated cyberthreats that circumvent standard rule- or signature-based security measures is known as proactive threat hunting.
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