Malware Forensics

Malicious Software Analysis and Investigation

Malware Attacks Detailed

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:

  1. Sample Acquisition: Obtain malware specimens safely
  2. Static Analysis: Examine without execution
  3. Dynamic Analysis: Observe runtime behavior
  4. Code Analysis: Reverse engineer functionality
  5. Network Analysis: Study communication patterns
  6. Attribution Analysis: Identify threats and campaigns
  7. 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.