Pros of cti

• Comprehensive MITRE ATT&CK framework coverage
• Regular updates with new threat intelligence
• Structured data format (STIX) for easy integration

Cons of cti

• Requires more technical expertise to utilize effectively
• Less focus on ready-to-use detection rules
• May require additional processing for practical implementation

Code Comparison

cti (STIX format):

{
  "type": "attack-pattern",
  "id": "attack-pattern--7e150503-88e7-4861-866b-ff1ac82c4475",
  "created_by_ref": "identity--c78cb6e5-0c4b-4611-8297-d1b8b55e40b5",
  "created": "2017-05-31T21:30:54.127Z",
  "modified": "2020-03-30T01:59:46.726Z",
  "name": "Rundll32",
  "description": "Adversaries may abuse rundll32.exe to proxy execution of malicious code...",
  "kill_chain_phases": [
    {
      "kill_chain_name": "mitre-attack",
      "phase_name": "defense-evasion"
    }
  ]
}

security_content (YAML format):

name: Detect Rundll32 Execution
id: 12345678-1234-1234-1234-123456789012
version: 1
date: '2021-01-01'
author: Splunk
type: TTP
datamodel: []
description: This search detects potential abuse of rundll32.exe for malicious code execution.
search: |
  index=windows sourcetype=WinEventLog:Security EventCode=4688
  Process_Name="*\\rundll32.exe"
  | stats count by Computer, User, Process_Name, Process_Command_Line

Pros of TheHive

• Full-featured incident response platform with case management, alert handling, and collaboration tools
• Integrates with various security tools and threat intelligence platforms
• Highly customizable and extensible through APIs and plugins

Cons of TheHive

• Steeper learning curve and more complex setup compared to security_content
• Requires more resources to run and maintain as a full application stack
• Less focused on providing pre-built detection content

Code Comparison

TheHive (Scala):

def create(caze: Case): Future[Case] = {
  val createdCase = caze.copy(
    createdAt = Some(new Date().getTime),
    createdBy = Some(AuthContext.get.userId)
  )
  caseRepository.create(createdCase)
}

security_content (YAML):

name: Suspicious PowerShell Download
description: Detects suspicious PowerShell download commands
search: >-
  index=windows sourcetype=WinEventLog:PowerShell
  (CommandLine="*Net.WebClient*.DownloadFile*" OR CommandLine="*Net.WebClient*.DownloadString*")

The code snippets highlight the different focus areas of the two projects. TheHive's code relates to case management functionality, while security_content provides detection rules in YAML format.

Pros of ThreatHunter-Playbook

• More comprehensive threat hunting methodology, including data sources and detection logic
• Broader coverage of various platforms and technologies beyond Splunk
• Community-driven approach with contributions from diverse security professionals

Cons of ThreatHunter-Playbook

• Less frequent updates compared to Security Content
• May require more effort to implement due to its platform-agnostic nature
• Lacks the tight integration with Splunk's ecosystem

Code Comparison

ThreatHunter-Playbook (YAML format):

title: Suspicious PowerShell Download
id: 69d641e5-aa25-4275-b7aa-4dd4a9e833c3
description: Detects suspicious PowerShell download
detection:
  selection:
    EventID: 4104
    ScriptBlockText|contains:
      - 'Net.WebClient'
      - 'DownloadFile'
  condition: selection

Security Content (YAML format):

name: Detect Suspicious PowerShell Download
id: 5b2f3ed9-493e-4345-9c1a-3c3d45c0d367
search: >-
  index=windows EventCode=4104
  (ScriptBlockText="*Net.WebClient*" OR ScriptBlockText="*DownloadFile*")
  | stats count by Computer, User

Both repositories provide valuable resources for threat detection and hunting. ThreatHunter-Playbook offers a more comprehensive and platform-agnostic approach, while Security Content provides tighter integration with Splunk and more frequent updates. The choice between them depends on the specific needs and environment of the organization.

Pros of Sigma

• Vendor-agnostic rule format, supporting multiple SIEM and log management systems
• Larger community and broader adoption across the security industry
• More flexible and extensible, allowing for custom field mappings and rule transformations

Cons of Sigma

• Less integrated with Splunk-specific features and capabilities
• May require additional tools or converters for optimal use in Splunk environments
• Potentially steeper learning curve for Splunk-centric security teams

Code Comparison

Sigma rule example:

title: Suspicious Process Creation
detection:
    selection:
        EventID: 1
        Image|endswith:
            - '\cmd.exe'
            - '\powershell.exe'
    condition: selection

Security Content rule example:

<rule>
  <title>Suspicious Process Creation</title>
  <search>EventCode=1 (Image="*\\cmd.exe" OR Image="*\\powershell.exe")</search>
  <description>Detects suspicious process creation events</description>
</rule>

Both repositories provide valuable security content, but Sigma offers a more universal approach, while Security Content is tailored specifically for Splunk environments. Sigma's flexibility comes at the cost of additional complexity, whereas Security Content provides a more streamlined experience for Splunk users.

Pros of detection-rules

• More focused on Elastic-specific detections and integrations
• Includes a robust testing framework for rule validation
• Offers a wider variety of rule types, including machine learning jobs

Cons of detection-rules

• Less comprehensive coverage of different security domains
• Smaller community and fewer contributors
• More complex setup and configuration process

Code Comparison

detection-rules:

name: Suspicious Process Creation in Temp Folder
type: eql
risk_score: 50
description: Detects suspicious process creation in the Windows Temp folder

query: |
  process where event.type == "creation" and
    process.executable : "C:\\Windows\\Temp\\*"

security_content:

name: Suspicious Process Creation in Temp Folder
search: |
  index=windows sourcetype=WinEventLog:Security EventCode=4688
  New_Process_Name="C:\\Windows\\Temp\\*"
description: Detects suspicious process creation in the Windows Temp folder

Both repositories provide detection rules for security monitoring, but they cater to different platforms. detection-rules is tailored for Elastic Stack users, while security_content is designed for Splunk environments. The code examples show how each repository structures its rules, with detection-rules using EQL (Event Query Language) and security_content using Splunk's search syntax.