Malware Forensics
Malicious Software Analysis and Investigation
What is Malware Forensics?
Malware Forensics: The process of identifying, analyzing, and understanding malicious software to determine its functionality, origin, impact, and attribution in forensic investigations.
- Static Analysis: Examining malware without execution
- Dynamic Analysis: Observing malware behavior during execution
- Reverse Engineering: Understanding malware functionality
- Attribution: Identifying malware authors and campaigns
Types of Malware
Viruses
- File infectors
- Boot sector viruses
- Macro viruses
- Polymorphic viruses
Worms
- Network worms
- Email worms
- USB worms
- Blended threats
Trojans
- Remote Access Trojans (RATs)
- Banking Trojans
- Information stealers
- Droppers and loaders
Advanced Threats
- Ransomware
- Rootkits
- Bootkits
- Fileless malware
Malware Analysis Process
Analysis Methodology:
- Sample Acquisition: Obtain malware specimens safely
- Static Analysis: Examine without execution
- Dynamic Analysis: Observe runtime behavior
- Code Analysis: Reverse engineer functionality
- Network Analysis: Study communication patterns
- Attribution Analysis: Identify threats and campaigns
- Documentation: Report findings and IOCs
Static Analysis Techniques
Static Analysis: Examining malware without executing it, focusing on file properties, strings, and code structure.
Static Analysis Steps:
- File Properties: Hash values, file size, compilation timestamps
- PE Header Analysis: Import/export tables, sections, resources
- String Analysis: Extract readable strings and encoded data
- Entropy Analysis: Identify packed or encrypted sections
- Signature Detection: YARA rules and pattern matching
Static Analysis Tools:
• file - Identify file types
• strings - Extract readable text
• hexdump - Binary analysis
• objdump - Disassemble executables
• peframe - PE file analysis
Dynamic Analysis Environment
Sandbox Requirements:
- Isolated Environment: Virtual machines with network isolation
- Monitoring Tools: Process, file, and network monitors
- Restoration Capability: Quick snapshot recovery
- Analysis Tools: Debuggers and system monitors
- Internet Simulation: Fake services for malware interaction
Dynamic Analysis Observations:
- Process creation and injection
- File system modifications
- Registry changes
- Network communications
- API calls and system interactions
Behavioral Analysis
Behavior Categories:
- Persistence: Maintaining presence on infected systems
- Evasion: Avoiding detection by security tools
- Communication: Command and control interactions
- Data Collection: Information gathering activities
- Payload Delivery: Distributing additional malware
Behavioral Indicators:
• Registry autorun keys modification
• Service installation
• Process hollowing or injection
• Network beaconing patterns
• File encryption activities
• Credential harvesting
Reverse Engineering
Reverse Engineering: Analyzing compiled malware to understand its source code logic and functionality.
Disassembly Tools
- IDA Pro (Interactive DisAssembler)
- Ghidra (NSA's reverse engineering suite)
- Radare2 (Open-source framework)
- x64dbg (Windows debugger)
Analysis Techniques
- Control flow analysis
- Data flow analysis
- Function identification
- Algorithm reconstruction
Assembly Code Example:
mov eax, [ebp+var_4] ; Load variable
cmp eax, 100h ; Compare with 256
jle short loc_401234 ; Jump if less or equal
call DecryptPayload ; Call decryption function
Packing and Obfuscation
Evasion Techniques:
- Packing: Compressing executable to hide content
- Encryption: Encrypting malware payload
- Polymorphism: Self-modifying code
- Anti-Analysis: Detecting analysis environments
- Code Obfuscation: Making code difficult to understand
Unpacking Strategies:
- Generic unpacking with OEP detection
- Automated unpacking tools (UPX, etc.)
- Manual unpacking with debuggers
- Memory dumping at runtime
- Entropy analysis for packed sections
Network Behavior Analysis
Network Communications:
- C&C Communication: Command and control server interaction
- Data Exfiltration: Stealing sensitive information
- Updates and Downloads: Receiving new payloads
- Peer-to-Peer: Decentralized communication networks
- DNS Requests: Domain name resolution patterns
Network Analysis Tools:
• Wireshark - Packet capture and analysis
• tcpdump - Command-line packet capture
• Fiddler - HTTP/HTTPS proxy analysis
• Burp Suite - Web application security testing
• INetSim - Internet simulation for malware analysis
Memory Forensics for Malware
Memory Analysis: Examining system memory to identify malware presence, injection techniques, and hidden processes.
Memory Artifacts:
- Process Lists: Hidden and modified processes
- Network Connections: Active and historical connections
- Code Injection: Process hollowing and DLL injection
- Rootkit Detection: Kernel-level modifications
- Cryptographic Keys: Encryption keys in memory
Memory Analysis Tools:
- Volatility Framework for memory analysis
- Rekall for advanced memory forensics
- Redline for memory and file analysis
- YARA for memory pattern matching
Ransomware Analysis
Ransomware Characteristics:
- File Encryption: Symmetric and asymmetric encryption
- Key Management: Key generation and storage
- Payment Systems: Cryptocurrency wallets
- Communication: Tor and anonymization networks
- Psychological Tactics: Countdown timers and threats
Ransomware Investigation:
- Identify encryption algorithms used
- Analyze key generation methods
- Trace cryptocurrency payments
- Examine ransom note content
- Study distribution methods
Attribution and Threat Intelligence
Attribution Indicators:
- Code Similarities: Shared functions and libraries
- Infrastructure: Common C&C servers and domains
- TTPs: Tactics, techniques, and procedures
- Language Artifacts: Error messages and strings
- Compilation Timestamps: Development schedules
- Certificates: Code signing certificate reuse
Threat Intelligence Sources:
• MITRE ATT&CK Framework
• VirusTotal Intelligence
• YARA Exchange
• Malware Information Sharing Platform (MISP)
• Commercial threat intelligence feeds
Automated Analysis Systems
Commercial Sandboxes
- Cuckoo Sandbox
- Joe Sandbox
- FireEye AX
- Falcon Sandbox
Online Analysis Services
- VirusTotal
- Hybrid Analysis
- Any.run
- Malwr (archived)
Automated Analysis Benefits:
- Rapid initial assessment
- Consistent analysis methodology
- Large-scale sample processing
- IOC extraction and sharing
- Baseline for manual analysis
Mobile Malware Analysis
Mobile Platforms:
- Android APK Analysis: Dalvik bytecode and native code
- iOS App Analysis: Mach-O binaries and Swift code
- Cross-Platform: React Native and hybrid apps
- IoT Firmware: Embedded system malware
Mobile Analysis Tools:
• APKTool - Android APK reverse engineering
• Frida - Dynamic instrumentation toolkit
• MobSF - Mobile Security Framework
• Jadx - DEX to Java decompiler
• class-dump - iOS class information extraction
Incident Response Integration
Malware in IR Process:
- Detection: Malware signatures and behavioral detection
- Analysis: Rapid malware triage and analysis
- Containment: IOC-based blocking and isolation
- Eradication: Complete malware removal
- Recovery: System restoration and monitoring
- Lessons Learned: Signature and rule updates
IOC Development:
- File hashes (MD5, SHA-1, SHA-256)
- Network indicators (IPs, domains, URLs)
- Registry keys and values
- File paths and names
- Process names and behaviors
Legal and Ethical Considerations
Legal Framework: Malware analysis must comply with legal restrictions on malware possession, analysis, and distribution.
Legal Considerations:
- Authorized Analysis: Proper legal authority for malware examination
- Safe Handling: Preventing malware spread during analysis
- Data Protection: Protecting victim information in samples
- Expert Testimony: Court presentation of findings
- Chain of Custody: Evidence handling procedures
Malware Analysis Best Practices
Safety Practices
- Isolated analysis environments
- Network segmentation
- Snapshot and restore procedures
- Secure sample storage
- Access control and monitoring
Analysis Quality
- Comprehensive documentation
- Reproducible analysis methods
- Peer review processes
- Tool validation and calibration
- Continuous learning and training
Future of Malware Analysis
Emerging Challenges:
- AI-Powered Malware: Machine learning-based evasion
- Fileless Attacks: Memory-only malware execution
- Cloud-Native Threats: Container and serverless malware
- Quantum-Resistant Encryption: New cryptographic methods
- IoT Proliferation: Embedded system malware growth
Analysis Evolution:
- AI-assisted analysis and classification
- Cloud-based analysis platforms
- Automated report generation
- Real-time threat intelligence integration
- Cross-platform analysis capabilities
Key Takeaways
Critical Points:
- Multi-Method Approach: Combine static, dynamic, and behavioral analysis
- Safe Environment: Isolated and controlled analysis infrastructure
- Comprehensive Documentation: Detailed analysis reports and IOCs
- Threat Intelligence: Attribution and campaign identification
- Continuous Learning: Keeping pace with malware evolution
Malware Analysis Excellence: Combine technical expertise, proper methodology, and safety practices to effectively analyze malicious software and provide actionable intelligence for cybersecurity defense.

