IronWind can capture the OS version and computer name of the compromised host.7
Discovery54 detection rules
Standing S9029
Reach is how much of ATT&CK this malware touches. Coverage is how well defended each thing it does is, as a median per technique rather than a total — a total would just restate the reach. Each figure is ranked against all 825 ATT&CK software entries only where that population actually spreads. Where most of the population shares one value, a percentile would rank the tie instead of the entity, so the raw value is shown and no rank is claimed.
Reach
Techniques944th pct
44th percentile · 56% of 825 ATT&CK software entries have more Enterprise techniques.
Tactics432nd pct
32nd percentile · 68% of 825 ATT&CK software entries have more tactics spanned.
Threat group161% tie · 22 values
61% of the population shares a single value across only 22 distinct values, so a percentile here would rank the tie, not the entity.
Campaigns085% tie · 8 values
85% of the population shares a single value across only 8 distinct values, so a percentile here would rank the tie, not the entity.
Coverage
Rules / technique47medTop 9%
91st percentile · 91% of 825 ATT&CK software entries have this many detection rules per technique or fewer.
Tests / technique6med
IronWind detections S9029
396 distinct rules cover the 9 techniques recorded for this malware. 296 Sigma · 100 Splunk.
9 covered by at least one rule396 distinct rules in total
Showing 1-50 of 300+ rules
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Title
Description
Category
Status
Event
OS
Product
MITRE ATT&CK
CVEs
Severity
Author
Created
Updated
ID
Refs
Detects when AppLocker "Audit only" enforcement mode reports that an Application, DLL, Script, MSI, or Packaged-App would have been blocked if AppLocker "Enforce rules" enforcement mode was enabled.
The following analytic detects the use of CertUtil.exe with the 'decode' argument, which may indicate an attempt to decode a previously encoded file, potentially containing malicious payloads. (...)
Adversaries may communicate using application layer protocols associated with web traffic to avoid detection/network filtering by blending in with existing traffic. (...)
The following analytic identifies the execution of the "whoami" command with the "/group" flag, where the results are passed to the "find" command in order to look for a the string "12288". (...)
This analytic detects potential reconnaissance activities on Cisco ASA devices by identifying execution of multiple information-gathering "show" commands within a short timeframe. (...)
This analytic detects the usage of the Utility osascript on a macOS device initiated a network connection lasting longer than 10 minutes (600 seconds). (...)
The following analytic detects the use of known suspicious SSL certificates in any observed event where the SSL_CertFingerprint field is present. (...)
The following analytic detects connections with a high Encrypted Visibility Engine (EVE) threat confidence score, indicating potentially malicious behavior within encrypted traffic. (...)
The following analytic detects the use of `cmd.exe /c` to execute commands, a technique often employed by adversaries and malware to run batch commands or invoke other shells like PowerShell. (...)
The following analytic identifies the use of named-pipe impersonation for privilege escalation, commonly associated with Cobalt Strike and similar frameworks. (...)
Detects creation of specific system DLL files that are usually not present on the system (or at least not in system directories) but may be loaded by legitimate processes. (...)
The following analytic identifies specific GET or HEAD requests to web servers that indicate reconnaissance attempts to find vulnerable JBoss servers. (...)
The following analytic detects executions of cmd.exe spawned by processes that are commonly abused by attackers and do not typically launch cmd.exe. (...)
The following detects the execution of cscript.exe or wscript.exe processes spawned by cmd.exe, leveraging Endpoint Detection and Response (EDR) telemetry mapped to the Endpoint data model, with additional contextual filtering to improve fidelity and reduce false positives. (...)
Adversaries may attempt to enumerate software for a variety of reasons, such as figuring out what security measures are present or if the compromised system has a version of software that is vulnerable.
Adversaries may attempt to enumerate software for a variety of reasons, such as figuring out what security measures are present or if the compromised system has a version of software that is vulnerable.