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These datasets correspond to different log4shell e...

Date: 2021-01-27 ID: 987c92c7-defa-4a3a-baf4-3973501aec8c Author: Jose Hernandez Environment: attack_range Directory: Unknown

Description

These datasets correspond to different log4shell exploitation happening against a system, specifically it is a data set generated from the risk events produced by detections: 1. ESCU - Detect Outbound LDAP Traffic - Rule 2. ESCU - Log4Shell JNDI Payload Injection Attempt - Rule 3. ESCU - Wget Download and Bash Execution - Rule

MITRE ATT&CK Techniques

No MITRE techniques specified for this dataset.

Environment Details

Field Value
Environment attack_range
Directory Unknown
Test Date 2021-01-27

Datasets

The following datasets were collected during this attack simulation:

Dataset_1

  • Path: https://github.com/splunk/attack_data/raw/master/datasets/suspicious_behaviour/log4shell_exploitation/log4shell_correlation.txt
  • Sourcetype: stash
  • Source: stash

No specific detections currently use this attack data for testing. However, you can find related detections and analytics in our security content repository.

Usage Instructions

Replay with Splunk Attack Data

Replay attack data with replay.py from Splunk Attack Data.

1python replay.py --dataset https://github.com/splunk/attack_data/raw/master/datasets/suspicious_behaviour/log4shell_exploitation/log4shell_correlation.txt --index attack_data

Manual Import

  1. Download the dataset files from the paths listed above
  2. Configure your Splunk instance with the appropriate sourcetypes
  3. Import the logs using the Splunk Add Data wizard

Related Content

Find more detections and analytics for this attack technique in our security content repository.

Source: GitHub | Version: 1.0