SocGholish is a JavaScript-based loader malware that has been used since at least 2017. It has been observed in use against multiple sectors globally for initial access, primarily through drive-by-downloads masquerading as software updates. SocGholish is operated by Mustard Tempest and its access has been sold to groups including Indrik Spider for downloading secondary RAT and ransomware payloads.[1][2][3][4]
19
TechniquesTop 23%
7
Tactics68th pct
1
Threat groupunranked
0
CampaignsNone recorded
Enterprise ATT&CK only. Any Mobile or ICS rows on the same ATT&CK page are not carried.
SocGholish has used WMI calls for script execution and system profiling.15
Execution71 detection rules
Standing S1124
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
Techniques19Top 23%
77th percentile · 77% of 825 ATT&CK software entries have this many Enterprise techniques or fewer.
Tactics768th pct
68th percentile · 68% of 825 ATT&CK software entries have this many tactics spanned or fewer.
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 / technique17med40th pct
40th percentile · 60% of 825 ATT&CK software entries have more detection rules per technique.
Tests / technique5med42nd pct
42nd percentile · 58% of 825 ATT&CK software entries have more atomic tests per technique.
Data comps / technique5med54% tie · 11 values
54% of the population shares a single value across only 11 distinct values, so a percentile here would rank the tie, not the entity.
Mitigations / technique2medTop 9%
91st percentile · 91% of 825 ATT&CK software entries have this many mitigations per technique or fewer.
5 of 8 axes carry an honest rank on this page. Coverage medians are taken across this malware’s 19 Enterprise techniques.
Range
Technique Campaign use over its cumulative rule count.
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 execution of tools commonly exploited by cybercriminals, such as those used for unauthorized access, network scanning, privilege escalation, password dumping or data exfiltration. (...)
Detects the Linux-specific execution chain of the plain-crypto-js malicious npm dependency by Axios NPM package, including payload download via curl and detached execution using nohup and python3. (...)
Detects the macOS-specific execution chain of the plain-crypto-js malicious npm dependency in Axios NPM Package, including AppleScript execution via osascript, payload download, permission modification, execution, and cleanup.
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 unexpected outbound network connections initiated by known webserver processes such as `httpd.exe`, `nginx.exe`, or `tomcat.exe` to common file sharing or public content hosting services like GitHub, Discord CDN, Transfer.sh, or Pastebin. (...)
The following analytic detects potential reverse shell activity by identifying connections involving ports commonly associated with remote access tools, shell listeners, or tunneling utilities. (...)
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 potentially suspicious large volumes of data sent by the connection initiator on flows from internal to external networks. (...)
This analytic identifies Snort intrusion signatures that have been triggered by ten or more distinct internal IP addresses within a one-hour window. (...)