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Analize malware from S3 in bulk

Analize malware from S3 in bulk​

Overview​

This workflow automates large-scale malware analysis by retrieving malware samples from AWS S3 storage and processing them through dual Windows environments (Windows 7 and Windows 10) in the Zynap sandbox. It performs bulk analysis operations, tracks processing across multiple samples, consolidates results from both analysis environments, and stores comprehensive reports back to S3 for centralized threat intelligence management.

How It Works​

  1. S3 Authentication and Setup: Initializes secure connection to AWS S3 using Zynap-provided credentials and configures access parameters for malware sample retrieval.

  2. File Enumeration: Executes script to scan and enumerate all malware samples stored in the designated S3 bucket, creating a processing queue for bulk analysis.

  3. Parallel Environment Processing: Distributes malware samples across two concurrent Windows sandbox environments, performing identical analysis operations on both platforms for comprehensive behavioral comparison:

    Branch A - Windows 7 Sandbox:

    • Sample Upload: Retrieves samples from S3 and uploads them to Windows 7 sandbox environment
    • Entity ID Extraction: Processes upload responses to extract unique entity_id for analysis job tracking
    • Hash Generation: Calculates and retrieves SHA256 hash values for sample identification
    • Status Monitoring: Continuously monitors analysis progress using entity_id until completion
    • Result Preparation: Consolidates analysis data for cross-platform correlation

    Branch B - Windows 10 Sandbox:

    • Sample Upload: Retrieves the same samples and uploads them to Windows 10 sandbox environment
    • Entity ID Extraction: Processes upload responses to extract unique entity_id for analysis job tracking
    • Hash Generation: Calculates and retrieves SHA256 hash values for sample identification
    • Status Monitoring: Continuously monitors analysis progress using entity_id until completion
    • Result Preparation: Consolidates analysis data for cross-platform correlation

  4. Result Consolidation: Merges analysis results from both Windows 7 and Windows 10 environments, creating comprehensive behavioral profiles that show malware behavior across different OS versions.

  5. Report Generation: Compiles unified analysis reports combining findings from both sandbox environments with detailed behavioral comparisons and threat classifications.

  6. S3 Result Storage: Uploads consolidated analysis reports and detailed findings back to designated S3 storage location for centralized access and long-term retention.

  7. Final AWS Integration: Completes the workflow by ensuring all processed data and reports are properly stored in S3 with appropriate metadata and access controls.

Who is this for?​

  • Security teams managing large-scale malware sample collections requiring bulk analysis capabilities
  • Threat intelligence analysts processing high-volume malware datasets from multiple sources
  • Incident response teams analyzing malware campaigns affecting both legacy and modern Windows environments
  • Malware researchers conducting comparative analysis across different Windows operating system versions
  • Organizations with centralized S3-based malware repositories requiring automated processing workflows
  • SOC analysts managing enterprise-scale threat detection with bulk sample analysis requirements

What problem does this workflow solve?​

  • Eliminates manual processing of large malware sample collections by automating bulk retrieval, analysis, and result storage across S3 infrastructure
  • Provides comprehensive cross-platform analysis by simultaneously testing malware behavior on both Windows 7 and Windows 10 environments for complete coverage
  • Reduces analysis bottlenecks by processing multiple samples in parallel while maintaining detailed tracking and correlation across different analysis environments
  • Streamlines enterprise malware analysis operations by integrating with existing S3-based storage infrastructure and providing centralized result management
  • Ensures consistent analysis methodology across large sample sets while maintaining detailed behavioral comparisons between different Windows operating system environments
  • Note: S3 authentication credentials must be requested from Zynap team, and specific workflow nodes require client-side configuration updates before deployment