FOR610: Reverse-Engineering Malware: Malware Analysis Tools and Techniques Expert - Led Video Course
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1.0 Introduction to Malware Analysis
1.1 Course Overview
1.2 What is Malware Analysis?
1.3 Types of Malware
1.4 Motivations Behind Malware Creation
1.5 The Malware Analysis Process
1.6 Static vs. Dynamic Analysis
1.7 Legal and Ethical Considerations
1.8 Required Skills and Background
1.9 Malware Analysis Lab Setup
1.10 Introduction to Case Studies
2.0 Building a Malware Analysis Lab
2.1 Hardware and Software Requirements
2.2 Virtual Machines vs. Physical Machines
2.3 Networking Setups (Isolated, Bridged, NAT)
2.4 Snapshots and Rollbacks
2.5 Lab Operating Systems
2.6 Essential Tools Overview
2.7 Safe Malware Handling Practices
2.8 Lab Automation Basics
2.9 Internet Simulation in Labs
2.10 Lab Clean-Up and Maintenance
3.0 Windows Internals for Malware Analysts
3.1 Windows Architecture Overview
3.2 Windows File System Basics
3.3 Windows Registry Structure
3.4 Processes and Threads
3.5 Windows Services
3.6 DLLs and Their Roles
3.7 Windows APIs
3.8 User vs. Kernel Mode
3.9 Windows Security Features
3.10 Common Windows Attack Vectors
4.0 Introduction to Assembly Language
4.1 Why Learn Assembly?
4.2 Assembly Language Basics
4.3 Registers and Memory
4.4 Instruction Sets (x86/x64)
4.5 Control Flow Instructions
4.6 Function Calls and Stack Usage
4.7 Common Assembly Idioms
4.8 Disassembly Tools
4.9 Practice: Reading Simple Assembly
4.10 Assembly in Malware
5.0 Static Analysis Fundamentals
5.1 What is Static Analysis?
5.2 Basic File Identification
5.3 Hashing and Checksums
5.4 PE File Structure
5.5 Strings Analysis
5.6 Embedded Resources
5.7 Import/Export Table Analysis
5.8 Recognizing Obfuscation
5.9 Static Indicators of Maliciousness
5.10 Common Pitfalls in Static Analysis
6.0 Dynamic Analysis Fundamentals
6.1 What is Dynamic Analysis?
6.2 Setting Up a Safe Environment
6.3 Process Monitoring Tools
6.4 File System Monitoring
6.5 Registry Monitoring
6.6 Network Traffic Analysis
6.7 API Monitoring
6.8 Behavioral Logging
6.9 Identifying Persistence Mechanisms
6.10 Limitations of Dynamic Analysis
7.0 PE File Analysis
7.1 PE File Format Overview
7.2 Headers and Sections
7.3 Import Address Table
7.4 Export Address Table
7.5 Resources and Data Directories
7.6 Analyzing Section Characteristics
7.7 Packed vs. Unpacked Binaries
7.8 Tools for PE Analysis
7.9 Manual PE Parsing
7.10 Common PE File Anomalies
8.0 Malware Classification and Families
8.1 Malware Taxonomy
8.2 Viruses
8.3 Worms
8.4 Trojans
8.5 Rootkits
8.6 Ransomware
8.7 Spyware and Adware
8.8 Fileless Malware
8.9 Polymorphic and Metamorphic Malware
8.10 Family Identification Techniques
9.0 Using Disassemblers (IDA Pro, Ghidra, etc.)
9.1 Introduction to Disassemblers
9.2 IDA Pro Interface Basics
9.3 Ghidra Overview
9.4 Loading Binaries
9.5 Navigating Code and Data
9.6 Graph Views and Functions
9.7 Renaming Functions and Variables
9.8 Scripting in Disassemblers
9.9 Plugins and Extensions
9.10 Best Practices for Disassembly
10.0 Debugging Malware (OllyDbg, x64dbg, WinDbg)
10.1 Introduction to Debuggers
10.2 Setting Up OllyDbg
10.3 Using x64dbg
10.4 Introduction to WinDbg
10.5 Breakpoints and Stepping
10.6 Memory and Stack Inspection
10.7 Reverse Engineering with Debuggers
10.8 Anti-Debugging Techniques
10.9 Bypassing Anti-Debugging
10.10 Debugging Automation
11.0 String Analysis Techniques
11.1 Extracting Strings
11.2 Unicode and ASCII Strings
11.3 Obfuscated and Encoded Strings
11.4 String Search Tools
11.5 Analyzing IOCs in Strings
11.6 YARA Rules for Strings
11.7 Contextual String Analysis
11.8 Strings as Malware Indicators
11.9 Automating String Extraction
11.10 String Analysis Limitations
12.0 File Packing and Obfuscation
12.1 What is Packing?
12.2 Popular Packers (UPX, ASPack, etc.)
12.3 Identifying Packed Files
12.4 Manual Unpacking
12.5 Automation Tools for Unpacking
12.6 Obfuscation Techniques
12.7 Deobfuscation Strategies
12.8 Packers vs. Cryptors
12.9 Detecting Custom Packers
12.10 Bypassing Obfuscation
13.0 Code Injection and Process Hollowing
13.1 Overview of Code Injection
13.2 Process Hollowing Explained
13.3 DLL Injection Techniques
13.4 Remote Thread Injection
13.5 API Hooking
13.6 Detecting Injection in Analysis
13.7 Analyzing Hollowed Processes
13.8 Common Tools for Detection
13.9 Case Studies
13.10 Mitigation Techniques
14.0 Analyzing Malicious Documents
14.1 Malicious Office Documents
14.2 Macros and Macro Analysis
14.3 Embedded Objects and Scripts
14.4 PDF Malware
14.5 Exploit Kits in Documents
14.6 Sandboxing Documents
14.7 Analyzing with OLETools
14.8 Indicators of Malicious Documents
14.9 Decoding Embedded Payloads
14.10 Document Malware Case Studies
15.0 Scripting for Malware Analysis (Python)
15.1 Why Script for Analysis?
15.2 Python Basics for Analysts
15.3 Automating Repetitive Tasks
15.4 Parsing PE Files with Python
15.5 Automating String Extraction
15.6 Scripting with Volatility
15.7 API Automation
15.8 Creating YARA Rules with Python
15.9 Building Analysis Pipelines
15.10 Publishing and Sharing Scripts
16.0 Network Traffic Analysis
16.1 Capturing Network Traffic
16.2 Wireshark Basics
16.3 Network Indicators of Compromise
16.4 HTTP/HTTPS Analysis
16.5 DNS Analysis
16.6 Malware C2 Protocols
16.7 PCAP Analysis Automation
16.8 Extracting Artifacts from Traffic
16.9 Identifying Exfiltration
16.10 Analyzing Encrypted Traffic
17.0 Behavioral Analysis Automation
17.1 Introduction to Automation
17.2 Cuckoo Sandbox Overview
17.3 Setting Up Automated Analysis
17.4 Submitting Samples
17.5 Automated Report Generation
17.6 Integrating Multiple Tools
17.7 Interpreting Automated Results
17.8 Scaling Automated Analysis
17.9 Troubleshooting Automation
17.10 Limitations and Future Trends
18.0 Anti-Analysis and Evasion Techniques
18.1 What is Anti-Analysis?
18.2 Common Evasion Techniques
18.3 Anti-VM Techniques
18.4 Anti-Debugging in Depth
18.5 Code Obfuscation
18.6 API Misdirection
18.7 Timing and Logic Bombs
18.8 Environmental Awareness
18.9 Bypassing Evasion
18.10 Future Trends in Evasion
19.0 Analyzing Persistence Mechanisms
19.1 What is Persistence?
19.2 Registry-Based Persistence
19.3 Scheduled Tasks
19.4 Services and Drivers
19.5 Startup Folder and Shortcuts
19.6 WMI-Based Persistence
19.7 DLL Search Order Hijacking
19.8 COM Hijacking
19.9 Fileless Persistence
19.10 Detecting and Removing Persistence
20.0 Rootkits and Stealth Malware
20.1 Rootkit Overview
20.2 Types of Rootkits
20.3 User-Mode vs. Kernel-Mode
20.4 Rootkit Detection Tools
20.5 Analyzing Rootkit Behavior
20.6 Common Rootkit Techniques
20.7 Bootkits and Firmware Attacks
20.8 Anti-Rootkit Strategies
20.9 Case Studies
20.10 Mitigating Rootkit Threats
21.0 Credential Theft and Keyloggers
21.1 Credential Theft Overview
21.2 Keylogger Techniques
21.3 Memory Scraping
21.4 Browser Credential Theft
21.5 Network-Based Theft
21.6 Password Dumpers
21.7 Analyzing Keylogger Samples
21.8 Detecting Credential Theft
21.9 Countermeasures
21.10 Case Studies
22.0 Ransomware Analysis
22.1 What is Ransomware?
22.2 Ransomware Families
22.3 Encryption Techniques
22.4 Payment and Communication Channels
22.5 Ransom Notes and Artifacts
22.6 Decryptor Analysis
22.7 Behavioral Patterns
22.8 Ransomware Detection
22.9 Mitigation and Recovery
22.10 Real-World Ransomware Cases
23.0 Spyware and Information Stealers
23.1 Spyware Overview
23.2 Information Stealer Techniques
23.3 Common Targets (Browsers, FTP)
23.4 Email and Messaging Stealers
23.5 Exfiltration Channels
23.6 Behavioral Analysis
23.7 Detecting Stealers
23.8 Stealer Case Studies
23.9 Prevention Strategies
23.10 Remediation Steps
24.0 Analyzing Network-Based Malware
24.1 Worms and Self-Propagation
24.2 Lateral Movement Techniques
24.3 Exploiting Network Vulnerabilities
24.4 Network Scanning
24.5 Network Protocol Abuses
24.6 Analyzing Network Payloads
24.7 Botnets and C2 Infrastructure
24.8 Network Forensics Tools
24.9 Detecting Network-Based Malware
24.10 Case Studies
25.0 Linux and Mac Malware Analysis
25.1 Linux Malware Overview
25.2 Mac Malware Overview
25.3 ELF File Analysis
25.4 Mach-O File Analysis
25.5 Static and Dynamic Tools
25.6 Common Persistence Techniques
25.7 Cross-Platform Malware
25.8 Reverse Engineering on Linux/Mac
25.9 Case Studies
25.10 Prevention and Mitigation
26.0 Reverse Engineering Mobile Malware
26.1 Android Malware Overview
26.2 iOS Malware Overview
26.3 APK and IPA File Structures
26.4 Static Analysis for Mobile
26.5 Dynamic Analysis for Mobile
26.6 Emulators and Sandboxes
26.7 Mobile Malware Behaviors
26.8 Popular Families
26.9 Case Studies
26.10 Mobile Security Best Practices
27.0 Memory Analysis and Volatility
27.1 Introduction to Memory Forensics
27.2 Memory Dump Acquisition
27.3 Memory Analysis Tools
27.4 Volatility Framework Basics
27.5 Process and DLL Detection
27.6 Malware Artifacts in Memory
27.7 Rootkit Detection in Memory
27.8 Automated Memory Analysis
27.9 Memory Analysis Case Studies
27.10 Limitations and Challenges
28.0 YARA and Signature-Based Detection
28.1 What is YARA?
28.2 Writing Basic YARA Rules
28.3 Advanced YARA Techniques
28.4 Testing and Debugging Rules
28.5 Integrating YARA in Workflows
28.6 YARA for Network Artifacts
28.7 Community Rule Sources
28.8 YARA Limitations
28.9 Signature Evasion Techniques
28.10 Future of Signature-Based Detection
29.0 Malware Attribution and Threat Intelligence
29.1 Why Attribute Malware?
29.2 Attribution Techniques
29.3 Threat Actor Profiling
29.4 Campaign Tracking
29.5 Intelligence Sources
29.6 IOCs and TTPs
29.7 Reporting Attribution
29.8 Attribution Pitfalls
29.9 Legal and Ethical Issues
29.10 Case Studies
30.0 Reverse Engineering Automation
30.1 Why Automate Reverse Engineering?
30.2 Scripting Disassemblers
30.3 Automating String and IOC Extraction
30.4 Batch Analysis
30.5 Automating Unpacking
30.6 Automated Behavioral Analysis
30.7 Custom Tool Development
30.8 Integrating Automation Tools
30.9 Measuring Automation Impact
30.10 Limitations of Automation
31.0 Advanced Static Analysis Techniques
31.1 Cross-Referencing Code
31.2 Control Flow Graph Analysis
31.3 Data Flow Analysis
31.4 Symbolic Execution
31.5 Code Similarity Detection
31.6 Function Identification
31.7 API Call Emulation
31.8 Decompiler Usage
31.9 Advanced Obfuscation Handling
31.10 Reporting Findings
32.0 Advanced Dynamic Analysis Techniques
32.1 Dynamic Instrumentation
32.2 Code Coverage Analysis
32.3 API Tracing
32.4 Memory Breakpoints
32.5 System Call Monitoring
32.6 Emulation vs. Virtualization
32.7 Custom Sandbox Development
32.8 Handling Anti-VM/Evasion
32.9 Dynamic Decryption
32.10 Combining Dynamic and Static Results
33.0 Analyzing Malicious Scripts
33.1 JavaScript Malware
33.2 PowerShell Malware
33.3 VBScript and Batch Files
33.4 Script Obfuscation
33.5 Automated Script Analysis
33.6 Indicators in Scripts
33.7 Decoding and Deobfuscation
33.8 Script Sandboxing
33.9 Script-Based Attacks
33.10 Script Analysis Tools
34.0 Analyzing Exploit Kits
34.1 What is an Exploit Kit?
34.2 Exploit Kit Architecture
34.3 Common Vulnerabilities Targeted
34.4 Payload Delivery Mechanisms
34.5 Traffic Patterns
34.6 Sandboxing Exploit Kits
34.7 Indicators in Exploit Kits
34.8 Reverse Engineering Exploit Kit Code
34.9 Case Studies
34.10 Prevention and Detection
35.0 Dealing with Encrypted and Obfuscated Payloads
35.1 Common Encryption Algorithms
35.2 Payload Extraction Techniques
35.3 Manual Decryption
35.4 Automated Decryption Tools
35.5 Obfuscation Layers
35.6 Dynamic Unpacking
35.7 Identifying Key Material
35.8 Code Flow for Decryption
35.9 Payload Reconstruction
35.10 Reporting Decrypted Findings
36.0 Reverse Engineering Network Protocols
36.1 Custom Protocols in Malware
36.2 Analyzing Protocol Traffic
36.3 Protocol Reverse Engineering Tools
36.4 Identifying Command and Control Patterns
36.5 Protocol Emulation
36.6 Decoding Protocol Messages
36.7 Encryption in Protocols
36.8 Building Protocol Parsers
36.9 Reporting Protocol Findings
36.10 Case Studies
37.0 Reverse Engineering Web-Based Malware
37.1 Webshells Overview
37.2 JavaScript and HTML Malware
37.3 Phishing Kits
37.4 Analyzing Web Payloads
37.5 Web Application Vulnerabilities
37.6 Detecting Web-Based C2
37.7 Webshell Detection Techniques
37.8 Forensic Analysis of Web Servers
37.9 Web-Based Malware Case Studies
37.10 Mitigation Strategies
38.0 Malware Reporting and Documentation
38.1 Importance of Documentation
38.2 Structure of a Malware Report
38.3 Describing Technical Findings
38.4 IOC Documentation
38.5 Attribution and Context
38.6 Visualizing Analysis Results
38.7 Collaboration and Review
38.8 Sharing with Stakeholders
38.9 Open Source Intelligence Sharing
38.10 Automation in Reporting
39.0 Incident Response and Malware Analysis
39.1 Role of Malware Analysis in IR
39.2 Triage and Prioritization
39.3 Collecting Evidence
39.4 Live vs. Dead Analysis
39.5 Communicating with Stakeholders
39.6 Coordinating with IR Teams
39.7 Reporting and Documentation
39.8 Lessons Learned
39.9 Long-Term Remediation
39.10 Case Studies
40.0 Legal and Ethical Considerations
40.1 Legal Regulations
40.2 Intellectual Property Issues
40.3 Responsible Disclosure
40.4 Handling Sensitive Data
40.5 Collaboration with Law Enforcement
40.6 Privacy Considerations
40.7 Ethical Boundaries
40.8 Chain of Custody
40.9 International Law
40.10 Case Studies
41.0 Malware Sandbox Evolution
41.1 History of Sandboxing
41.2 Types of Sandboxes
41.3 Sandbox Detection and Evasion
41.4 Advanced Sandboxing Techniques
41.5 Cloud-Based Sandboxes
41.6 Open Source vs. Commercial
41.7 Integrating Sandboxes in Workflows
41.8 Sandbox Automation
41.9 Limitations and Future Trends
41.10 Case Studies
42.0 Threat Hunting with Malware Analysis
42.1 What is Threat Hunting?
42.2 Hunting for Malware IOCs
42.3 Leveraging Malware Analysis Findings
42.4 Automated IOC Distribution
42.5 Threat Intelligence Integration
42.6 Proactive vs. Reactive Hunting
42.7 Data Sources for Hunting
42.8 Collaboration with SOCs
42.9 Reporting and Feedback Loops
42.10 Case Studies
43.0 Supply Chain Attacks and Malware
43.1 Understanding Supply Chain Attacks
43.2 Case Studies in Supply Chain Malware
43.3 Analysis of Compromised Software
43.4 Code Signing Abuse
43.5 Detecting Supply Chain Malware
43.6 Reverse Engineering Software Updates
43.7 Mitigating Supply Chain Risks
43.8 Reporting Supply Chain Incidents
43.9 Collaboration with Vendors
43.10 Future Trends
44.0 Malware Analysis in Cloud Environments
44.1 Cloud Malware Threats
44.2 Analyzing Cloud-Based Attacks
44.3 Cloud Forensics Tools
44.4 Cloud-Specific Persistence
44.5 Reverse Engineering Cloud Malware
44.6 API Abuse in Cloud
44.7 Cloud Sandbox Environments
44.8 Incident Response in Cloud
44.9 Reporting Cloud Malware
44.10 Future Directions
45.0 Reverse Engineering IoT Malware
45.1 IoT Malware Landscape
45.2 IoT Firmware Analysis
45.3 Common IoT Attacks
45.4 Static Analysis of IoT Binaries
45.5 Dynamic IoT Analysis
45.6 Protocols in IoT Attacks
45.7 IoT Botnets
45.8 Malware Persistence in IoT
45.9 Case Studies
45.10 IoT Security Best Practices
46.0 Advanced Persistence and Lateral Movement
46.1 Advanced Persistence Techniques
46.2 Fileless Attacks
46.3 Credential Dumping
46.4 Lateral Movement via Malware
46.5 Pass-the-Hash Attacks
46.6 Remote Code Execution
46.7 Pivoting Techniques
46.8 Detection and Response
46.9 Case Studies
46.10 Prevention Strategies
47.0 Reverse Engineering Ransomware Encryption
47.1 Understanding Ransomware Encryption
47.2 Common Algorithms Used
47.3 Key Management and Storage
47.4 Static Analysis of Crypto Code
47.5 Dynamic Crypto Analysis
47.6 Extracting Keys from Memory
47.7 Decryptor Development
47.8 Analyzing Ransomware Samples
47.9 Case Studies
47.10 Reporting and Coordination
48.0 Advanced Deobfuscation Techniques
48.1 Common Obfuscation Methods
48.2 Pattern Recognition
48.3 Automated Deobfuscation Tools
48.4 Manual Deobfuscation Steps
48.5 Code Normalization
48.6 Symbol Recovery
48.7 Dynamic Deobfuscation
48.8 Deobfuscation in Scripts
48.9 Reporting Cleaned Code
48.10 Case Studies
49.0 Career Development for Malware Analysts
49.1 Roles and Responsibilities
49.2 Building Skills and Knowledge
49.3 Certifications and Training
49.4 Networking in the Industry
49.5 Contributing to Open Source
49.6 Publishing Research
49.7 Job Hunting Strategies
49.8 Professional Ethics
49.9 Continuous Learning
49.10 Career Pathways
50.0 Future of Malware Analysis
50.1 Emerging Malware Trends
50.2 AI and Machine Learning in Analysis
50.3 Automated Reverse Engineering
50.4 Advanced Persistent Threats
50.5 Cloud and IoT Challenges
50.6 Malware-as-a-Service
50.7 Global Collaboration
50.8 Threat Intelligence Evolution
50.9 Preparing for the Future
50.10 Continuous Improvement