Rising Sun is a modular backdoor that was used extensively in Operation Sharpshooter between 2017 and 2019. Rising Sun infected at least 87 organizations around the world, including nuclear, defense, energy, and financial service companies. Security researchers assessed Rising Sun included some source code from Lazarus Group's Trojan Duuzer.[1]
20
TechniquesTop 20%
6
Tactics53rd pct
0
Threat groupsNone recorded
1
Campaignunranked
Enterprise ATT&CK only. Any Mobile or ICS rows on the same ATT&CK page are not carried.
Rising Sun has identified the OS product name from a compromised host by searching the registry for SOFTWARE\MICROSOFT\Windows NT\ CurrentVersion | ProductName.3
Rising Sun can detect the username of the infected host.7
Discovery47 detection rules
Standing S0448
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
Techniques20Top 20%
80th percentile · 80% of 825 ATT&CK software entries have this many Enterprise techniques or fewer.
Tactics653rd pct
53rd percentile · 53% of 825 ATT&CK software entries have this many tactics spanned or fewer.
Threat groups061% 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.
Campaign185% 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 / technique21med49th pct
49th percentile · 51% of 825 ATT&CK software entries have more detection rules per technique.
Tests / technique5.5med45th pct
45th percentile · 55% of 825 ATT&CK software entries have more atomic tests per technique.
Data comps / technique4med54% 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 / technique0medBottom 17%
17th percentile · 83% of 825 ATT&CK software entries have more mitigations per technique.
5 of 8 axes carry an honest rank on this page. Coverage medians are taken across this malware’s 20 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.
This detection uses Windows security events to detect suspicious access attempts to the registry key values and sub-keys of Azure AD Health service agents (e.g AD FS). (...)
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 potentially suspicious large volumes of data sent by the connection initiator on flows from internal to external networks. (...)