type: x-mitre-data-component
spec_version: 2.1
id: x-mitre-data-component--167b48f7-76e9-4fcb-9e8d-7121f7bf56c3
created: 2021-10-20T15:05:19.271Z
created_by_ref: identity--c78cb6e5-0c4b-4611-8297-d1b8b55e40b5
revoked: no
external_references: source_name: mitre-attack
url: https://attack.mitre.org/datacomponents/DC0011
external_id: DC0011
object_marking_refs: marking-definition--fa42a846-8d90-4e51-bc29-71d5b4802168
modified: 2025-10-21T15:10:28.402Z
name: Malware Content
description: Code, strings, signatures, and other identifying characteristics of a malicious payload stored within a malware repository. It includes both static (file-based) and dynamic (behavioral or execution-based) components that can be analyzed for threat intelligence, detection, and prevention purposes. Examples:

- Static Analysis:
 - Executable Code: Analyze binary data to identify unique patterns, obfuscated code, or embedded resources.
 - Strings Extraction: Use tools like strings or YARA rules to identify hardcoded URLs, IPs, filenames, or suspicious function calls.
 - Signatures: Extract cryptographic hashes (MD5, SHA256) of files to track known malware variants or detect previously unseen samples.
- Dynamic Analysis:
 - Behavioral Observations: Monitor execution traces to capture API calls, registry modifications, or network traffic patterns indicative of malicious behavior.
 - Memory Analysis: Examine memory dumps to uncover injected code or runtime-decrypted payloads.
 - Artifacts: Record file system changes, process creation events, and command-line arguments.
- Threat Intelligence Integration:
 - Campaign Attribution: Associate observed code snippets or signatures with known APT campaigns or ransomware families.
 - Indicator Sharing: Share identified Indicators of Compromise (IOCs) with threat intelligence platforms (e.g., MISP, OpenCTI).
- Examples of Malware Content:
 - Embedded C2 domains (e.g., malicious-domain.com hardcoded in the payload).
 - Fileless malware indicators, such as PowerShell scripts invoking Invoke-Mimikatz.
 - Malware-specific signatures, such as unique PE header values for a particular strain.

*Data Collection Measures:*

- Collection from Public Malware Repositories:
 - VirusTotal: Obtain samples for static analysis.
 - Hybrid Analysis: Gather execution data from sandbox analysis.
 - Any.Run: Access interactive malware execution traces.
 - MalwareBazaar: Download malware samples for research and signature generation.
 - Automate data extraction using repository APIs (e.g., VirusTotal API for hash lookups or sample retrieval).
- Internal Malware Labs:
 - Sandbox Environments: Use dynamic malware analysis tools such as Cuckoo Sandbox or Joe Sandbox to execute and monitor malware in a controlled environment. Capture runtime behavior logs, memory dumps, and file system changes.
 - Reverse Engineering: Disassemble binaries with tools like IDA Pro, Ghidra, or Radare2 to identify malicious functionality and extract code patterns.
- EDR/Endpoint Telemetry:
 - Collect samples of malicious binaries or scripts from infected endpoints using tools like CrowdStrike, Carbon Black, or SentinelOne.
 - Extract memory-resident payloads from live systems for analysis.
- Threat Intelligence Platforms:
 - Gather contextual metadata for identified malware using tools like OpenCTI, Recorded Future, or ThreatConnect. Participate in intelligence-sharing groups such as ISACs (e.g., FS-ISAC, IT-ISAC).
- Custom Data Collection Pipelines: Use open-source tools like malwoverview or Maltrail to automate sample downloads, hash extraction, and IOC generation.
x_mitre_modified_by_ref: identity--c78cb6e5-0c4b-4611-8297-d1b8b55e40b5
x_mitre_deprecated: no
x_mitre_domains: enterprise-attack
x_mitre_version: 2.0
x_mitre_attack_spec_version: 3.3.0
x_mitre_log_sources: name: Malware Repository
channel: None