This hunt targets potential misconfigurations or placeholder artifacts in Azure Sentinel where legacy code comments or test strings persist in production environments, indicating a lack of rigorous change management. Proactively hunting for these anomalies allows the SOC team to reduce alert noise and identify opportunities to harden their detection logic before such artifacts obscure critical security signals.
rule MALW_Rebirth_Vulcan_ELF {
meta:
description = "Detects Rebirth Vulcan variant a torlus NextGen MALW"
description = "Just adjust or omit below two strings for next version they code :) @unixfreaxjp"
date = "2018-01-21"
strings:
$spec01 = "vulcan.sh" fullword nocase wide ascii
$spec02 = "Vulcan" fullword nocase wide ascii
condition:
all of them
and is__elf
and is__str_Rebirth_gen3
and is__hex_Rebirth_gen3
and is__bot_Rebirth_gen3
and filesize < 300KB
}
This YARA rule can be deployed in the following contexts:
This rule contains 2 string patterns in its detection logic.
Based on the detection rule title and logic provided (Just adjust or omit below two strings for next version they code :) @unixfreaxjp), it appears this rule is designed to detect specific text patterns in file contents, commit messages, or log entries that match a conversational or review-style string (likely containing emojis like :), mentions like @unixfreaxjp, and phrases about “next version”).
Here are 4 specific false positive scenarios in an enterprise environment where legitimate activities would trigger this rule:
Developer Code Review Comments in Pull Requests
@unixfreaxjp) to ensure visibility before merging.source is identified as a CI/CD platform (e.g., GitHub Actions, GitLab Runner) or filter by user agent containing “git-review” and restrict the action type to comment.created.Scheduled Documentation Update Jobs
@unixfreaxjp into the “Changelog” section of the documentation page to notify stakeholders about pending code adjustments.process_name matches known automation tools like jenkins-agent, `