T1483: Domain Generation Algorithms
Adversaries may make use of Domain Generation Algorithms (DGAs) to dynamically identify a destination for command and control traffic rather than relying on a list of static IP addresses or domains. This has the advantage of making it much harder for defenders block, track, or take over the command and control channel, as there potentially could be thousands of domains that malware can check for instructions.[1][2][3]
DGAs can take the form of apparently random or “gibberish” strings (ex: istgmxdejdnxuyla.ru) when they construct domain names by generating each letter. Alternatively, some DGAs employ whole words as the unit by concatenating words together instead of letters (ex: cityjulydish.net). Many DGAs are time-based, generating a different domain for each time period (hourly, daily, monthly, etc). Others incorporate a seed value as well to make predicting future domains more difficult for defenders.[1][2][4][5]
Adversaries may use DGAs for the purpose of Fallback Channels. When contact is lost with the primary command and control server malware may employ a DGA as a means to reestablishing command and control.[4][6][7]
This ATT&CK object is revoked or deprecated in the current MITRE ATT&CK release.
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Domain Generation Algorithms
Adversaries may make use of Domain Generation Algorithms (DGAs) to dynamically identify a destination for command and control traffic rather than relying on a list of static IP addresses or domains. This has the advantage of making it much harder for defenders block, track, or take over the command and control channel, as there potentially could be thousands of domains that malware can check for instructions.[1][2][3]
DGAs can take the form of apparently random or “gibberish” strings (ex: istgmxdejdnxuyla.ru) when they construct domain names by generating each letter. Alternatively, some DGAs employ whole words as the unit by concatenating words together instead of letters (ex: cityjulydish.net). Many DGAs are time-based, generating a different domain for each time period (hourly, daily, monthly, etc). Others incorporate a seed value as well to make predicting future domains more difficult for defenders.[1][2][4][5]
Adversaries may use DGAs for the purpose of Fallback Channels. When contact is lost with the primary command and control server malware may employ a DGA as a means to reestablishing command and control.[4][6][7]
How security teams should use this page
Treat this object as behavior context, not an attribution claim. Validate the related groups, software, data sources, and mitigations against official ATT&CK relationships and your own telemetry before making control-coverage decisions.
Related techniques
This mirrors the MITRE pattern of making group, software, campaign, and technique relationships scannable. Relationship notes come from mirrored ATT&CK relationship text when available.
| Domain | ID | Name | Relationship / procedure |
|---|---|---|---|
| Enterprise | T1568.002 | Domain Generation Algorithms Sub-technique | This object revoked by Domain Generation Algorithms. |
All related ATT&CK context
Object version and sync metadata
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Imported snapshots across ATT&CK releases (1)
| Release | Bundle imported | Object version | Modified | Status | Raw hash |
|---|---|---|---|---|---|
| 19.1 | 1.1 | Current bundle Revoked | 5577465c47ae… |
Mirrored ATT&CK source object
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External references and citations
MITRE external references are preserved separately from Glexia analysis so citations remain traceable to their original source records.
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[1]
Cybereason Dissecting DGAs
Sternfeld, U. (2016). Dissecting Domain Generation Algorithms: Eight Real World DGA Variants. Retrieved February 18, 2019.
Open source URL -
[2]
Cisco Umbrella DGA
Scarfo, A. (2016, October 10). Domain Generation Algorithms – Why so effective?. Retrieved February 18, 2019.
Open source URL -
[3]
Unit 42 DGA Feb 2019
Unit 42. (2019, February 7). Threat Brief: Understanding Domain Generation Algorithms (DGA). Retrieved February 19, 2019.
Open source URL -
[4]
Talos CCleanup 2017
Brumaghin, E. et al. (2017, September 18). CCleanup: A Vast Number of Machines at Risk. Retrieved March 9, 2018.
Open source URL -
[5]
Akamai DGA Mitigation
Liu, H. and Yuzifovich, Y. (2018, January 9). A Death Match of Domain Generation Algorithms. Retrieved February 18, 2019.
Open source URL -
[6]
FireEye POSHSPY April 2017
Dunwoody, M.. (2017, April 3). Dissecting One of APT29’s Fileless WMI and PowerShell Backdoors (POSHSPY). Retrieved April 5, 2017.
Open source URL -
[7]
ESET Sednit 2017 Activity
ESET. (2017, December 21). Sednit update: How Fancy Bear Spent the Year. Retrieved February 18, 2019.
Open source URL -
[8]
Data Driven Security DGA
Jacobs, J. (2014, October 2). Building a DGA Classifier: Part 2, Feature Engineering. Retrieved February 18, 2019.
Open source URL -
[9]
Elastic Predicting DGA
Ahuja, A., Anderson, H., Grant, D., Woodbridge, J.. (2016, November 2). Predicting Domain Generation Algorithms with Long Short-Term Memory Networks. Retrieved April 26, 2019.
Open source URL -
[10]
Pace University Detecting DGA May 2017
Chen, L., Wang, T.. (2017, May 5). Detecting Algorithmically Generated Domains Using Data Visualization and N-Grams Methods . Retrieved April 26, 2019.
Open source URL -
[11]
mitre-attack T1483Open source URL
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