FOR577: LINUX Incident Response and Threat Hunting Expert - Led Video Course
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1. Introduction to Linux Incident Response
1.1 What is Incident Response?
1.2 Importance of Linux in Enterprise Environments
1.3 Key Differences: Windows vs. Linux Incident Response
1.4 Threat Landscape for Linux Systems
1.5 Common Attack Vectors in Linux
1.6 Linux Distributions in the Wild
1.7 Incident Response Life Cycle
1.8 Roles and Responsibilities
1.9 Legal and Regulatory Considerations
1.10 Overview of Course Structure
2. Linux Architecture Fundamentals
2.1 Kernel Overview
2.2 User Space vs. Kernel Space
2.3 Process Management
2.4 File System Hierarchy
2.5 Systemd and Init Systems
2.6 User and Group Management
2.7 Permissions and Ownership
2.8 Network Stack Basics
2.9 Devices and Modules
2.10 Logs and Audit Trails
3. Preparation: Building Your IR Toolkit
3.1 Essential Tools for Linux IR
3.2 Live Response Tools
3.3 Forensic Imaging Tools
3.4 Log Collection Utilities
3.5 Memory Acquisition Tools
3.6 Scripting Languages for IR
3.7 Setting Up an IR Workstation
3.8 Tool Validation and Testing
3.9 Building a Response Jump Kit
3.10 Documentation and Templates
4. Threat Hunting Concepts
4.1 What is Threat Hunting?
4.2 Proactive vs. Reactive Approaches
4.3 Hypothesis-Driven Hunting
4.4 Data Sources for Hunting
4.5 Indicators of Compromise (IOCs)
4.6 Tactics, Techniques, and Procedures (TTPs)
4.7 MITRE ATT&CK for Linux
4.8 Leveraging Threat Intelligence
4.9 Hunt Team Structures
4.10 Measuring Hunt Effectiveness
5. Evidence Acquisition Principles
5.1 Order of Volatility
5.2 Live vs. Dead Box Analysis
5.3 Imaging Drives
5.4 Memory Acquisition
5.5 Network Traffic Capture
5.6 Preserving Chain of Custody
5.7 Avoiding Evidence Contamination
5.8 Documenting Acquisition Steps
5.9 Handling Encrypted Data
5.10 Legal/Ethical Considerations
6. Live Response on Linux
6.1 When to Perform Live Response
6.2 Live Response vs. Forensic Imaging
6.3 Collecting System Information
6.4 Capturing Process Listings
6.5 Gathering Network Connections
6.6 Collecting Memory Dumps
6.7 Extracting Log Files
6.8 Copying Key Artifacts
6.9 Minimizing Footprint
6.10 Automating Live Response
7. File System Forensics
7.1 Common Linux File Systems
7.2 EXT4, XFS, BTRFS Overview
7.3 File Metadata Analysis
7.4 Hidden and Deleted Files
7.5 Journaling and Recovery
7.6 Time Stamps and Timelines
7.7 File Carving Techniques
7.8 Searching for Malicious Files
7.9 File Permission Attacks
7.10 Forensic Tools for File Systems
8. Memory Forensics
8.1 Why Memory Matters
8.2 Memory Acquisition Techniques
8.3 Linux Memory Structures
8.4 Process Extraction from Memory
8.5 Analyzing Loaded Modules
8.6 Detecting Rootkits in Memory
8.7 Memory Forensics Tools
8.8 Network Artifacts in Memory
8.9 Malware Hunting in RAM
8.10 Memory Analysis Case Studies
9. Log Analysis for Incident Response
9.1 Key Linux Log Files
9.2 Syslog and rsyslog
9.3 Journald and Systemd Logs
9.4 Authentication Logs
9.5 Application Logs
9.6 Log Rotation and Retention
9.7 Searching and Filtering Logs
9.8 Correlating Log Events
9.9 Detecting Log Tampering
9.10 Tools for Log Analysis
10. User and Authentication Investigations
10.1 Understanding /etc/passwd and /etc/shadow
10.2 User Account Enumeration
10.3 Investigating Sudo Usage
10.4 SSH Authentication Analysis
10.5 Reviewing PAM Configurations
10.6 Identifying Suspicious Users
10.7 Privilege Escalation Techniques
10.8 User Session Tracking
10.9 Last Logins and Failed Attempts
10.10 Detecting Account Compromise
11. Process and Service Investigations
11.1 Listing Processes
11.2 Analyzing Running Services
11.3 Identifying Suspicious Processes
11.4 Parent-Child Process Relationships
11.5 Investigating Daemons
11.6 Detecting Process Injection
11.7 Process Persistence Mechanisms
11.8 Service Configuration Analysis
11.9 Comparing to Baselines
11.10 Tools for Process Analysis
12. Network Activity Analysis
12.1 Capturing Network Connections
12.2 Monitoring Open Ports
12.3 Analyzing Netstat and ss Output
12.4 Reviewing Firewall Rules
12.5 Investigating Network Traffic
12.6 DNS and Proxy Logs
12.7 Detecting Lateral Movement
12.8 Identifying Exfiltration Channels
12.9 Tools for Network Analysis
12.10 Network Forensics Case Study
13. Malware Triage on Linux
13.1 Types of Linux Malware
13.2 Common Infection Methods
13.3 Detecting Malicious Binaries
13.4 Analyzing Droppers and Payloads
13.5 Static vs. Dynamic Analysis
13.6 Reverse Engineering Basics
13.7 Sandboxing Malicious Samples
13.8 Indicators of Malware Persistence
13.9 Tools for Malware Detection
13.10 Reporting Malware Findings
14. Rootkit Detection
14.1 What is a Rootkit?
14.2 Types of Linux Rootkits
14.3 Common Indicators of Rootkits
14.4 Kernel vs. Userland Rootkits
14.5 Detecting Hidden Processes
14.6 Analyzing Kernel Modules
14.7 Rootkit Removal Techniques
14.8 Rootkit Detection Tools
14.9 Case Studies: Rootkit Incidents
14.10 Preventing Rootkit Infections
15. Persistence Mechanisms in Linux
15.1 Understanding Persistence
15.2 Modifying Init Scripts
15.3 Systemd Service Abuse
15.4 Cron Job Manipulation
15.5 SSH Key Backdoors
15.6 Sudoers and PAM Abuse
15.7 Malicious Kernel Modules
15.8 Network-Based Persistence
15.9 Detecting Persistence Techniques
15.10 Mitigating Persistence
16. Timeline Analysis
16.1 What is Timeline Analysis?
16.2 Sources of Timestamps
16.3 Creating a System Timeline
16.4 Tools for Timeline Generation
16.5 Correlating Events
16.6 Identifying Malicious Activity
16.7 Filtering Noise
16.8 Visualizing Timelines
16.9 Timeline Analysis Case Studies
16.10 Automating Timeline Creation
17. Bash and Shell History Analysis
17.1 Location of Shell Histories
17.2 Analyzing .bash_history
17.3 Zsh and Other Shells
17.4 Timestamps in History Files
17.5 Detecting History Manipulation
17.6 Recovering Deleted History
17.7 Identifying Malicious Commands
17.8 Correlating with Other Artifacts
17.9 Automating Shell History Analysis
17.10 Best Practices for Shell Forensics
18. Detection of Data Exfiltration
18.1 Common Exfiltration Techniques
18.2 Monitoring Outbound Traffic
18.3 Unusual Protocols and Ports
18.4 Large Data Transfers
18.5 Covert Channels
18.6 DNS Tunneling
18.7 Data Compression and Encryption
18.8 Log Analysis for Exfiltration
18.9 Tools for Detecting Exfiltration
18.10 Mitigation Strategies
19. Incident Scoping and Impact Assessment
19.1 Defining Incident Scope
19.2 Identifying Affected Assets
19.3 Data Sensitivity Assessment
19.4 Mapping Lateral Movement
19.5 Determining Initial Compromise
19.6 Estimating Business Impact
19.7 Communicating Findings
19.8 Reporting Requirements
19.9 Lessons Learned
19.10 Continuous Improvement
20. Containment Strategies
20.1 What is Containment?
20.2 Stopping Lateral Movement
20.3 Isolating Hosts
20.4 Blocking Malicious Traffic
20.5 Disabling Compromised Accounts
20.6 Removing Persistence
20.7 Ensuring Business Continuity
20.8 Temporary vs. Permanent Containment
20.9 Communicating with Stakeholders
20.10 Documenting Containment Actions
21. Eradication and Recovery
21.1 Defining Eradication
21.2 Removing Malicious Artifacts
21.3 Patching Vulnerabilities
21.4 Re-imaging Systems
21.5 Password Resets
21.6 Recovery Planning
21.7 System Hardening
21.8 Monitoring Post-Recovery
21.9 User Communication
21.10 Finalizing Incident Documentation
22. Post-Incident Activities
22.1 Lessons Learned Meetings
22.2 Updating Response Plans
22.3 Improving Detection Mechanisms
22.4 Training and Awareness
22.5 Reporting to Management
22.6 Legal and Regulatory Follow-up
22.7 Retrospective Threat Hunting
22.8 Updating Playbooks
22.9 Sharing with Information Sharing Groups
22.10 Conducting Tabletop Exercises
23. Hunting for Fileless Malware
23.1 Understanding Fileless Malware
23.2 Memory-Resident Attacks
23.3 Living-off-the-Land Techniques
23.4 Detecting Abnormal Processes
23.5 Volatile Data Collection
23.6 Log Analysis for Fileless Attacks
23.7 Case Study: Fileless Intrusion
23.8 Prevention Techniques
23.9 Automating Fileless Malware Detection
23.10 Reporting Fileless Threats
24. SSH Attack Investigations
24.1 Common SSH Threats
24.2 Brute Force Attacks
24.3 SSH Key Abuse
24.4 Investigating SSH Configs
24.5 Log Analysis for SSH Activity
24.6 Detecting Backdoored Binaries
24.7 SSH Honeypots
24.8 Network Traffic Analysis
24.9 Mitigating SSH Attacks
24.10 Best Practices for SSH Security
25. Privilege Escalation Techniques
25.1 Understanding Privilege Escalation
25.2 Sudo and SUID Exploitation
25.3 Kernel Exploits
25.4 Misconfigured Services
25.5 Credential Dumping
25.6 Environmental Variable Attacks
25.7 Exploiting World Writable Files
25.8 Detecting Escalation Attempts
25.9 Mitigating Privilege Escalation
25.10 Case Study: Escalation Attack
26. Web Shells and Backdoors
26.1 What are Web Shells?
26.2 Common Web Shells in Linux
26.3 Backdoor Implantation Techniques
26.4 Detecting Web Shells
26.5 Log Analysis for Web Shell Activity
26.6 File Integrity Monitoring
26.7 Analyzing Web Server Logs
26.8 Preventing Web Shell Deployment
26.9 Tools for Web Shell Detection
26.10 Reporting Web Shell Incidents
27. Advanced Malware Analysis
27.1 Dynamic Analysis Techniques
27.2 Static Analysis of ELF Binaries
27.3 Reverse Engineering with Ghidra
27.4 Behavioral Analysis
27.5 Sandboxing Malware
27.6 YARA Rules for Malware
27.7 Memory Dump Analysis
27.8 Network Indicators in Malware
27.9 Reporting and Documentation
27.10 Case Study: ELF Malware
28. Container Security and Incident Response
28.1 Introduction to Containers
28.2 Common Container Threats
28.3 Container Escape Techniques
28.4 Investigating Compromised Containers
28.5 Analyzing Container Logs
28.6 Memory and File System Analysis
28.7 Container Runtime Security Tools
28.8 Network Segmentation in Containers
28.9 Incident Response Playbooks for Containers
28.10 Best Practices for Container IR
29. Cloud-Based Linux IR
29.1 Understanding Cloud Environments
29.2 Major Cloud Providers
29.3 Cloud-Specific Attack Vectors
29.4 Collecting Evidence from Cloud VMs
29.5 Storage and API Forensics
29.6 Cloud Logging and Monitoring
29.7 IAM and Access Keys
29.8 Cloud Network Analysis
29.9 Response Coordination with CSPs
29.10 Legal Considerations in the Cloud
30. Automated Threat Detection
30.1 Introduction to SIEM
30.2 Log Forwarding and Centralization
30.3 Integrating Linux with SIEM
30.4 Writing Detection Rules
30.5 Alert Tuning and Management
30.6 Automated Response Playbooks
30.7 Event Correlation Techniques
30.8 Machine Learning for Detection
30.9 Open Source Detection Tools
30.10 Building a Detection Pipeline
31. Threat Intelligence Integration
31.1 What is Threat Intelligence?
31.2 Types of Threat Intelligence
31.3 Consuming TI Feeds on Linux
31.4 Integrating TI with SIEM
31.5 Enrichment of Events
31.6 IOCs vs. TTPs
31.7 Automating Threat Intelligence
31.8 Sharing and Collaboration
31.9 Case Study: Threat Intel in Action
31.10 Open Source Threat Intelligence Platforms
32. Forensics of Removable Media
32.1 Types of Removable Media
32.2 Imaging USB Drives
32.3 Identifying Malicious Media
32.4 File System Artifacts
32.5 Hidden Partitions
32.6 Recovering Deleted Data
32.7 Detecting Auto-run Infections
32.8 Log Correlation with Media Use
32.9 Tools for Media Forensics
32.10 Preventing Removable Media Attacks
33. Email-Based Attacks on Linux
33.1 Phishing and Linux Users
33.2 Malicious Attachments
33.3 Investigating Mail Logs
33.4 Analyzing Spam Filters
33.5 Spear Phishing Detection
33.6 Email Header Analysis
33.7 Investigating Compromised Accounts
33.8 Email-Based Malware
33.9 Reporting Email Attacks
33.10 User Awareness Training
34. Wireless and Bluetooth Threats
34.1 Linux Wireless Stack Overview
34.2 Common Wireless Attacks
34.3 Bluetooth Threats on Linux
34.4 Wireless Traffic Capture
34.5 Investigating Rogue Access Points
34.6 Detecting Unauthorized Devices
34.7 Wireless Log Analysis
34.8 Tools for Wireless IR
34.9 Mitigating Wireless Threats
34.10 Best Practices for Wireless Security
35. Insider Threat Investigations
35.1 Defining Insider Threats
35.2 Recognizing Behavioral Indicators
35.3 Log Analysis for Insider Activity
35.4 Data Access Monitoring
35.5 Detecting Privilege Misuse
35.6 File Transfer Analysis
35.7 User Session Tracking
35.8 Insider Threat Case Studies
35.9 Prevention and Detection Strategies
35.10 Legal and HR Coordination
36. Digital Evidence Management
36.1 Evidence Handling Principles
36.2 Chain of Custody Documentation
36.3 Secure Storage Practices
36.4 Evidence Integrity Verification
36.5 Evidence Tagging and Cataloging
36.6 Digital Evidence in Court
36.7 Maintaining Evidence Logs
36.8 Automated Evidence Management Tools
36.9 Policy Development
36.10 Training for Evidence Handling
37. Scripting for Incident Response
37.1 Benefits of Scripting
37.2 Bash Scripting Basics
37.3 Automating Data Collection
37.4 Parsing Logs with Python
37.5 Scripting for Timeline Analysis
37.6 Automating Malware Scanning
37.7 Scheduled Script Execution
37.8 Error Handling and Logging
37.9 Sharing and Version Control
37.10 Example IR Scripts
38. Physical Security Considerations
38.1 Physical Attack Vectors
38.2 Hardware Implants
38.3 BIOS and Firmware Attacks
38.4 Secure Server Rooms
38.5 Access Control Systems
38.6 Device Disposal and Data Wiping
38.7 Tamper Detection
38.8 Incident Response for Physical Breach
38.9 Policy and Training
38.10 Integrating Physical and Cyber IR
39. Legal and Regulatory Aspects
39.1 Understanding Legal Requirements
39.2 GDPR and Linux IR
39.3 Data Breach Notification Laws
39.4 Working with Law Enforcement
39.5 Evidence Admissibility
39.6 Privacy Considerations
39.7 Cross-Border Data Issues
39.8 Regulatory Frameworks
39.9 Documentation for Legal Cases
39.10 Legal Resources for IR Teams
40. Incident Response Playbooks
40.1 What is a Playbook?
40.2 Components of an IR Playbook
40.3 Playbook for Malware Outbreak
40.4 Playbook for Unauthorized Access
40.5 Playbook for Data Exfiltration
40.6 Playbook for Privilege Escalation
40.7 Playbook for Insider Threat
40.8 Reviewing and Updating Playbooks
40.9 Automating Playbook Execution
40.10 Playbook Documentation Templates
41. Linux Endpoint Detection and Response (EDR)
41.1 EDR Concepts for Linux
41.2 Open Source EDR Solutions
41.3 Agent-Based vs. Agentless EDR
41.4 Configuring Linux EDR
41.5 EDR Data Sources
41.6 Alerting and Response Capabilities
41.7 Integration with SIEM
41.8 EDR Use Cases
41.9 EDR Limitations on Linux
41.10 Evaluating EDR Products
42. Incident Response in Virtualized Environments
42.1 Overview of Virtualization
42.2 Hypervisor Security
42.3 Virtual Machine Forensics
42.4 Snapshot and Rollback Analysis
42.5 Analyzing Virtual Networks
42.6 Artifact Collection from VMs
42.7 Virtual Disk Analysis
42.8 Detecting VM Escape Attacks
42.9 IR Challenges in Virtual Environments
42.10 Best Practices for Virtual IR
43. Reporting and Communication
43.1 Importance of Reporting
43.2 Incident Reporting Templates
43.3 Executive Summary Writing
43.4 Detailed Technical Reporting
43.5 Communicating with Stakeholders
43.6 Regulatory Reporting
43.7 Lessons Learned Reports
43.8 Maintaining Communication Channels
43.9 Using Ticketing Systems
43.10 Effective Presentation Techniques
44. Advanced Log Correlation
44.1 What is Log Correlation?
44.2 Aggregating Logs from Multiple Sources
44.3 Time Synchronization Issues
44.4 Correlation Rules and Patterns
44.5 Detecting Multi-Stage Attacks
44.6 Log Correlation Tools
44.7 Automating Correlation Workflows
44.8 Visualization of Correlated Events
44.9 Case Study: Advanced Attack Detection
44.10 Continuous Improvement in Correlation
45. Incident Response Metrics and KPIs
45.1 Importance of Metrics
45.2 Time to Detect (TTD)
45.3 Time to Contain (TTC)
45.4 Time to Remediate (TTR)
45.5 False Positive Rates
45.6 Incident Volume Trends
45.7 Measuring Hunt Success
45.8 Reporting Metrics to Leadership
45.9 Benchmarking Against Industry
45.10 Using Metrics for Improvement
46. Incident Response in SCADA/ICS Environments
46.1 Overview of SCADA/ICS
46.2 Linux in Industrial Systems
46.3 Unique Threats in ICS
46.4 Evidence Collection Challenges
46.5 Incident Scenarios in ICS
46.6 Network Segmentation in ICS
46.7 Regulatory Compliance
46.8 Coordinating with Operations Teams
46.9 Case Study: ICS Incident
46.10 Best Practices for ICS IR
47. Digital Forensics Case Studies
47.1 Case Study: Ransomware on Linux
47.2 Case Study: Insider Data Theft
47.3 Case Study: SSH Key Abuse
47.4 Case Study: Web Shell Attack
47.5 Case Study: Rootkit Detection
47.6 Case Study: Lateral Movement
47.7 Case Study: Supply Chain Attack
47.8 Case Study: Cloud Compromise
47.9 Lessons Learned from Case Studies
47.10 Applying Lessons to IR Plans
48. Blue Team Collaboration and Exercises
48.1 What is a Blue Team?
48.2 Red vs. Blue Team Exercises
48.3 Tabletop Exercise Planning
48.4 Running Purple Team Drills
48.5 Communication During Exercises
48.6 Lessons Learned from Exercises
48.7 Documenting Exercise Outcomes
48.8 Continuous Training
48.9 Collaboration Tools
48.10 Building a Blue Team Culture
49. Emerging Trends in Linux Security and IR
49.1 Ransomware on Linux
49.2 Supply Chain Attacks
49.3 Advanced Persistent Threats (APTs)
49.4 Cloud-Native Threats
49.5 AI and Machine Learning in IR
49.6 Quantum Computing Impacts
49.7 Zero Trust in Linux Environments
49.8 Future of Threat Hunting
49.9 Automation and Orchestration
49.10 Preparing for the Next Decade
50. Capstone: Building a Linux IR and Threat Hunting Program
50.1 Program Structure and Governance
50.2 Building an IR Team
50.3 Developing IR Policies
50.4 Integrating Threat Hunting
50.5 Training and Skill Development
50.6 Tool Selection and Management
50.7 Building Response Playbooks
50.8 Metrics and Continuous Improvement
50.9 Executive and Board Reporting
50.10 Future-Proofing Your Program