MITRE ATT&CK - Техника Алгоритмы генерирования доменных имен

Куда я попал?

SECURITM это SGRC система, автоматизирующая процессы в службах информационной безопасности. SECURITM помогает построить и управлять ИСПДн, КИИ, ГИС, СМИБ/СУИБ, банковскими системами защиты.
А еще SECURITM это место для обмена опытом и наработками для служб безопасности.

Подробнее

Наш канал

Dynamic Resolution: Алгоритмы генерирования доменных имен

Other sub-techniques of Dynamic Resolution (3)

ID	Название
.001	Быстрая смена IP-адресов для DNS-записи
.002	Алгоритмы генерирования доменных имен
.003	Расчет на основе DNS

Adversaries may make use of Domain Generation Algorithms (DGAs) to dynamically identify a destination domain 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 to block, track, or take over the command and control channel, as there potentially could be thousands of domains that malware can check for instructions.(Citation: Cybereason Dissecting DGAs)(Citation: Cisco Umbrella DGA)(Citation: Unit 42 DGA Feb 2019) 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.(Citation: Cybereason Dissecting DGAs)(Citation: Cisco Umbrella DGA)(Citation: Talos CCleanup 2017)(Citation: Akamai DGA Mitigation) 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.(Citation: Talos CCleanup 2017)(Citation: FireEye POSHSPY April 2017)(Citation: ESET Sednit 2017 Activity)

ID: T1568.002

Относится к технике: T1568

Тактика(-и): Command and Control

Платформы: Linux, macOS, Windows

Требуемые разрешения: User

Источники данных: Network Traffic: Network Traffic Flow

Версия: 1.0

Дата создания: 10 Mar 2020

Последнее изменение: 11 Mar 2022

Название	Описание
Примеры процедур
Aria-body	Aria-body has the ability to use a DGA for C2 communications.(Citation: CheckPoint Naikon May 2020)
QakBot	QakBot can use domain generation algorithms in C2 communication.(Citation: Trend Micro Qakbot May 2020)
Doki	Doki has used the DynDNS service and a DGA based on the Dogecoin blockchain to generate C2 domains.(Citation: Intezer Doki July 20)
MiniDuke	MiniDuke can use DGA to generate new Twitter URLs for C2.(Citation: ESET Dukes October 2019)
POSHSPY	POSHSPY uses a DGA to derive command and control URLs from a word list.(Citation: FireEye POSHSPY April 2017)
DarkWatchman	DarkWatchman has used a DGA to generate a domain name for C2.(Citation: Prevailion DarkWatchman 2021)
BONDUPDATER	BONDUPDATER uses a DGA to communicate with command and control servers.(Citation: FireEye APT34 Dec 2017)
APT41	APT41 has used DGAs to change their C2 servers monthly.(Citation: FireEye APT41 Aug 2019)
Ngrok	Ngrok can provide DGA for C2 servers through the use of random URL strings that change every 12 hours.(Citation: Zdnet Ngrok September 2018)
TA551	TA551 has used a DGA to generate URLs from executed macros.(Citation: Unit 42 TA551 Jan 2021)(Citation: Secureworks GOLD CABIN)
Conficker	Conficker has used a DGA that seeds with the current UTC victim system date to generate domains.(Citation: SANS Conficker)(Citation: Trend Micro Conficker)
CHOPSTICK	CHOPSTICK can use a DGA for Fallback Channels, domains are generated by concatenating words from lists.(Citation: ESET Sednit 2017 Activity)
Ursnif	Ursnif has used a DGA to generate domain names for C2.(Citation: ProofPoint Ursnif Aug 2016)
Milan	Milan can use hardcoded domains as an input for domain generation algorithms.(Citation: Accenture Lyceum Targets November 2021)
SombRAT	SombRAT can use a custom DGA to generate a subdomain for C2.(Citation: BlackBerry CostaRicto November 2020)
CCBkdr	CCBkdr can use a DGA for Fallback Channels if communications with the primary command and control server are lost.(Citation: Talos CCleanup 2017)
Grandoreiro	Grandoreiro can use a DGA for hiding C2 addresses, including use of an algorithm with a user-specific key that changes daily.(Citation: Securelist Brazilian Banking Malware July 2020)(Citation: ESET Grandoreiro April 2020)
ShadowPad	ShadowPad uses a DGA that is based on the day of the month for C2 servers.(Citation: Securelist ShadowPad Aug 2017)(Citation: Kaspersky ShadowPad Aug 2017)(Citation: FireEye APT41 Aug 2019)
Astaroth	Astaroth has used a DGA in C2 communications.(Citation: Cybereason Astaroth Feb 2019)
Bazar	Bazar can implement DGA using the current date as a seed variable.(Citation: Cybereason Bazar July 2020)
Shark	Shark can send DNS C2 communications using a unique domain generation algorithm.(Citation: ClearSky Siamesekitten August 2021)(Citation: Accenture Lyceum Targets November 2021)
Ebury	Ebury has used a DGA to generate a domain name for C2.(Citation: ESET Ebury Feb 2014)(Citation: ESET Ebury Oct 2017)

Контрмера	Описание
Контрмеры
Network Intrusion Prevention	Use intrusion detection signatures to block traffic at network boundaries.
Restrict Web-Based Content	Restrict use of certain websites, block downloads/attachments, block Javascript, restrict browser extensions, etc.
Domain Generation Algorithms Mitigation	This technique may be difficult to mitigate since the domains can be registered just before they are used, and disposed shortly after. Malware researchers can reverse-engineer malware variants that use DGAs and determine future domains that the malware will attempt to contact, but this is a time and resource intensive effort.(Citation: Cybereason Dissecting DGAs)(Citation: Cisco Umbrella DGA Brute Force) Malware is also increasingly incorporating seed values that can be unique for each instance, which would then need to be determined to extract future generated domains. In some cases, the seed that a particular sample uses can be extracted from DNS traffic.(Citation: Akamai DGA Mitigation) Even so, there can be thousands of possible domains generated per day; this makes it impractical for defenders to preemptively register all possible C2 domains due to the cost. In some cases a local DNS sinkhole may be used to help prevent DGA-based command and control at a reduced cost. Network intrusion detection and prevention systems that use network signatures to identify traffic for specific adversary malware can be used to mitigate activity at the network level. Signatures are often for unique indicators within protocols and may be based on the specific protocol used by a particular adversary or tool, and will likely be different across various malware families and versions. Adversaries will likely change tool C2 signatures over time or construct protocols in such a way as to avoid detection by common defensive tools. (Citation: University of Birmingham C2)

Обнаружение

Detecting dynamically generated domains can be challenging due to the number of different DGA algorithms, constantly evolving malware families, and the increasing complexity of the algorithms. There is a myriad of approaches for detecting a pseudo-randomly generated domain name, including using frequency analysis, Markov chains, entropy, proportion of dictionary words, ratio of vowels to other characters, and more.(Citation: Data Driven Security DGA) CDN domains may trigger these detections due to the format of their domain names. In addition to detecting a DGA domain based on the name, another more general approach for detecting a suspicious domain is to check for recently registered names or for rarely visited domains. Machine learning approaches to detecting DGA domains have been developed and have seen success in applications. One approach is to use N-Gram methods to determine a randomness score for strings used in the domain name. If the randomness score is high, and the domains are not whitelisted (CDN, etc), then it may be determined if a domain is related to a legitimate host or DGA.(Citation: Pace University Detecting DGA May 2017) Another approach is to use deep learning to classify domains as DGA-generated.(Citation: Elastic Predicting DGA)

Ссылки

Связанные риски

Ничего не найдено

Каталоги

Мы используем cookie-файлы, чтобы получить статистику, которая помогает нам улучшить сервис для вас с целью персонализации сервисов и предложений. Вы может прочитать подробнее о cookie-файлах или изменить настройки браузера. Продолжая пользоваться сайтом, вы даёте согласие на использование ваших cookie-файлов и соглашаетесь с Политикой обработки персональных данных.