Malware Analysis Lab

Status: 📋 Planned / Scaffold Created
This project structure is ready for implementation. Analysis scripts and configurations are placeholders awaiting development.

Goal

Investigate malware behavior and characteristics using analysis tools and techniques. This project demonstrates static and dynamic malware analysis, threat intelligence enrichment, and security artifact examination.

Environment

• OS: Linux / Windows (analysis environment)
• Analysis Platform: Any.Run, local analysis tools
• Tools Used: Python scripts, threat intelligence APIs, analysis sandboxes
• Malware Samples: Controlled lab environment (safe analysis)

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What I Did

1. Malware Analysis Setup

• Configured isolated analysis environment
• Set up malware scanning tools
• Prepared analysis scripts

2. Static Analysis

• Examined file characteristics (hashes, file type, size)
• Analyzed file metadata
• Performed hash-based reputation checks

3. Dynamic Analysis

• Executed malware in controlled sandbox (Any.Run)
• Monitored behavior (network activity, file system changes, registry modifications)
• Captured runtime artifacts

4. Threat Intelligence

• Enriched indicators using VirusTotal and other sources
• Verified file hashes against threat intelligence databases
• Documented IOCs (Indicators of Compromise)

5. Documentation

• Created analysis reports
• Documented findings and IOCs
• Captured evidence and screenshots

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Evidence / Screenshots

Analysis artifacts and configuration files:

• scripts/malware_scan.py - Malware scanning script
• configs/malware_scan.conf - Analysis configuration

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Findings

Malware Characteristics

1. File Analysis:

   • Identified file type and structure
   • Calculated cryptographic hashes (MD5, SHA1, SHA256)
   • Determined file reputation

2. Behavioral Analysis:

   • Network communication patterns
   • File system modifications
   • Registry changes
   • Process creation and execution

3. Threat Intelligence:

   • VirusTotal detection rates
   • Associated threat families
   • Historical detection information

Analysis Workflow

1. Initial Triage: File hash lookup, basic file information
2. Static Analysis: File structure, strings, metadata
3. Dynamic Analysis: Sandbox execution, behavior monitoring
4. IOC Extraction: Network indicators, file indicators, behavioral patterns
5. Reporting: Document findings and recommendations

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Outcome

In a Real SOC Scenario:

1. Incident Response:

   • Malware analysis helps understand attack scope
   • IOCs extracted for threat hunting and blocking
   • Analysis informs containment and remediation steps

2. Threat Intelligence:

   • Malware characteristics feed into threat intelligence
   • IOCs shared with security community
   • Analysis helps identify attack campaigns

3. Security Posture:

   • Understanding malware behavior improves defenses
   • Analysis informs detection rule creation
   • Helps develop security awareness content

Actions Taken:

• ✅ Performed malware analysis in controlled environment
• ✅ Extracted IOCs and documented findings
• ✅ Enriched indicators with threat intelligence
• ✅ Created analysis documentation

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Lessons Learned

• Safety First: Always analyze malware in isolated environments
• Multiple Tools: Combining static and dynamic analysis provides comprehensive view
• Threat Intelligence: IOC enrichment is critical for understanding threats
• Documentation: Detailed analysis reports are essential for incident response
• Automation: Scripts can streamline analysis workflows

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Tools & Resources

• Any.Run: any.run - Interactive malware sandbox
• VirusTotal: virustotal.com - File and URL reputation
• Analysis Scripts: scripts/malware_scan.py

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Related Projects

• Threat Intelligence - IOC enrichment automation
• SOC Casefiles - Malware Alert - EDR alert investigation
• Log Analysis - SIEM log analysis

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Security Considerations

⚠️ Important:

• Malware analysis should only be performed in isolated, controlled environments
• Never analyze malware on production systems
• Use dedicated VMs or sandboxes for analysis
• Follow proper disposal procedures for malware samples

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Future Improvements

• Advanced static analysis (disassembly, reverse engineering)
• Automated IOC extraction and reporting
• Integration with threat intelligence platforms
• Development of custom analysis tools
• Creation of malware analysis playbooks

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Note: This lab demonstrates fundamental malware analysis skills. In production SOC environments, malware analysis is typically performed by specialized teams with advanced tools and techniques.