Orangeworm is a group that has targeted organizations in the healthcare sector in the United States, Europe, and Asia since at least 2015, likely for the purpose of corporate espionage.[1] Reverse engineering of Kwampirs, directly associated with Orangeworm activity, indicates significant functional and development overlaps with Shamoon.[2]
2
TechniquesBottom 8%
2
TacticsBottom 10%
8
Tools & malwareTop 24%
0
CampaignsNone recorded
Enterprise ATT&CK only. Any Mobile or ICS rows on the same ATT&CK page are not carried.
Reach is how much of ATT&CK this group 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 176 ATT&CK groups 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
Techniques2Bottom 8%
8th percentile · 92% of 176 ATT&CK groups have more Enterprise techniques.
Tactics2Bottom 10%
10th percentile · 90% of 176 ATT&CK groups have more tactics spanned.
Tools & malware8Top 24%
76th percentile · 76% of 176 ATT&CK groups have this many tools and malware or fewer.
Campaigns089% tie · 4 values
89% of the population shares a single value across only 4 distinct values, so a percentile here would rank the tie, not the entity.
Coverage
Rules / technique57medTop 3%
97th percentile · 97% of 176 ATT&CK groups have this many detection rules per technique or fewer.
Tests / technique3.5med53rd pct
53rd percentile · 53% of 176 ATT&CK groups have this many atomic tests per technique or fewer.
Data comps / technique4med65% tie · 12 values
65% of the population shares a single value across only 12 distinct values, so a percentile here would rank the tie, not the entity.
Mitigations / technique3med43% tie · 11 values
43% of the population shares a single value across only 11 distinct values, so a percentile here would rank the tie, not the entity.
5 of 8 axes carry an honest rank on this page. Coverage medians are taken across this group’s 2 Enterprise techniques.
Range
Technique Campaign use over its cumulative rule count.
Adversaries may communicate using application layer protocols associated with web traffic to avoid detection/network filtering by blending in with existing traffic. (...)
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. (...)
Detects a threat actor creating a file named `iertutil.dll` in the `C:\Program Files\Internet Explorer\` directory over the network for a DCOM InternetExplorer DLL Hijack scenario.
Detects the execution of SharpMove, a .NET utility performing multiple tasks such as "Task Creation", "SCM" query, VBScript execution using WMI via its PE metadata and command line options.
HTTP request smuggling is a technique for interfering with the way a web site processes sequences of HTTP requests that are received from one or more users. (...)
The following analytic detects HTTP POST requests containing heavily encoded data in the post body, specifically looking for sequences of hex-encoded bytes or base64-encoded strings. (...)
This detection identifies rapid-fire POST request attacks where an attacker sends more than 20 POST requests within a 5-second window, potentially attempting to exploit race conditions or overwhelm request handling. (...)
Detects attempts to exploit a request smuggling technique against IIS that leverages a Windows quirk where requests for reserved Windows device names such as "/con" trigger an early server response before the request body is received. (...)
This Splunk query analyzes web logs to identify and categorize user agents, detecting various types of Remote Monitoring and Mangement applications. (...)
This Splunk query analyzes web access logs to identify and categorize non-browser user agents, detecting various types of security tools, scripting languages, automation frameworks, and suspicious patterns. (...)
The following analytic identifies the use of suspicious command-line parameters associated with Impacket tools, such as `wmiexec.py`, `smbexec.py`, `dcomexec.py`, and `atexec.py`, which are used for lateral movement and remote code execution. (...)