Catalog
method#Security#Analytics#Observability#Reliability

Malware Analysis

A methodical approach to identify, classify and assess malicious software using static, dynamic and forensic techniques.

Malware analysis is a structured method set for identifying, classifying and assessing malicious software.
Established
High

Classification

  • High
  • Technical
  • Technical
  • Intermediate

Technical context

SIEM (e.g., Splunk, Elastic)Endpoint Detection & Response (EDR) systemsThreat intelligence feeds and YARA repositories

Principles & goals

Preserve evidence firstReproducibility of analysesDefence by insight
Run
Team, Domain

Use cases & scenarios

Compromises

  • Risk of accidental spread if isolation is insufficient
  • False indicators lead to false positives and wasted resources
  • Privacy breaches from improper data handling
  • Segregation of analysis and production networks
  • Automated pre-processing for prioritization
  • Document analysis steps and artifacts

I/O & resources

  • Samples (binaries, scripts), memory dumps
  • Network and system logs
  • Prior knowledge: IOC lists, threat intelligence feeds
  • Analysis report with TTPs and IoCs
  • Signatures/YARA rules and SIEM correlations
  • Recommendations for hardening and detection

Description

Malware analysis is a structured method set for identifying, classifying and assessing malicious software. It combines static and dynamic techniques, sandboxing and forensic examination to reveal behavior, indicators and persistence mechanisms. The method covers analysis workflows, tools and evidence handling while accounting for legal and organizational constraints.

✔

  • Improves detection and response capabilities during incidents
  • Enables more precise signatures and hunting rules
  • Supports forensic chains of custody and traceability

✖

  • High time and resource requirements for complex samples
  • Limited usefulness for heavily obfuscated or polymorphic samples
  • Legal constraints when handling malware evidence

  • Time-to-analyze

    Average time from sample intake to final analysis report.

  • Detection coverage

    Proportion of analyzed samples that yielded actionable IoCs or signatures.

  • Reproducibility rate

    Percentage of analyses that produce consistent results under defined conditions.

Analysis of a banking trojan variant

Static decryption of configuration, dynamic observation of network communication, and creation of YARA rules.

Sandbox-based classification of a packer

Detection of packing methods via behavioral tests, unpacking and restoring the original binary.

Forensic analysis of a memory dump

Extraction of runtime strings, DLL injections and volatile network connections to reconstruct the attack chain.

1

Set up an isolated analysis environment with sandboxing and monitoring.

2

Define intake and chain-of-custody processes for samples.

3

Deploy automated baseline scans and dynamic sandboxes.

4

Train analysts in static and dynamic analysis.

5

Integrate analysis outputs into SIEM/EDR workflows.

6

Regularly review and adjust signatures and playbooks.

⚠️ Technical debt & bottlenecks

  • Outdated analysis environments and unpatched VM snapshots
  • Lack of automation for pre-processing and prioritization
  • Missing documentation of analysis scripts and playbooks
Manual reverse-engineering capacitySandbox instance scalingLegal and privacy approvals
  • Sharing malware samples in internal file shares without isolation
  • Automatically blocking without IOC validation
  • Using outdated signatures as sole defense
  • False negatives with packed or obfuscated samples
  • Overestimating sandbox results as fully representative
  • Loss of context due to incomplete telemetry
Reverse engineering and assembly knowledgeNetwork protocols and traffic analysisForensic methods and evidence preservation
Isolation and secure sandboxing infrastructureReliable telemetry and log collectionReproducible analysis pipelines and versioning
  • • Network access for dynamic analysis often restricted
  • • Legal rules for evidence handling vary by region
  • • Tool licensing and operational costs