T1499 Endpoint Denial of Service
Adversaries may perform Endpoint Denial of Service (DoS) attacks to degrade or block the availability of services to users. Endpoint DoS can be performed by exhausting the system resources those services are hosted on or exploiting the system to cause a persistent crash condition. Example services include websites, email services, DNS, and web-based applications. Adversaries have been observed conducting DoS attacks for political purposes4 and to support other malicious activities, including distraction2, hacktivism, and extortion.6
An Endpoint DoS denies the availability of a service without saturating the network used to provide access to the service. Adversaries can target various layers of the application stack that is hosted on the system used to provide the service. These layers include the Operating Systems (OS), server applications such as web servers, DNS servers, databases, and the (typically web-based) applications that sit on top of them. Attacking each layer requires different techniques that take advantage of bottlenecks that are unique to the respective components. A DoS attack may be generated by a single system or multiple systems spread across the internet, which is commonly referred to as a distributed DoS (DDoS).
To perform DoS attacks against endpoint resources, several aspects apply to multiple methods, including IP address spoofing and botnets.
Adversaries may use the original IP address of an attacking system, or spoof the source IP address to make the attack traffic more difficult to trace back to the attacking system or to enable reflection. This can increase the difficulty defenders have in defending against the attack by reducing or eliminating the effectiveness of filtering by the source address on network defense devices.
Botnets are commonly used to conduct DDoS attacks against networks and services. Large botnets can generate a significant amount of traffic from systems spread across the global internet. Adversaries may have the resources to build out and control their own botnet infrastructure or may rent time on an existing botnet to conduct an attack. In some of the worst cases for DDoS, so many systems are used to generate requests that each one only needs to send out a small amount of traffic to produce enough volume to exhaust the target’s resources. In such circumstances, distinguishing DDoS traffic from legitimate clients becomes exceedingly difficult. Botnets have been used in some of the most high-profile DDoS attacks, such as the 2012 series of incidents that targeted major US banks.5
In cases where traffic manipulation is used, there may be points in the global network (such as high traffic gateway routers) where packets can be altered and cause legitimate clients to execute code that directs network packets toward a target in high volume. This type of capability was previously used for the purposes of web censorship where client HTTP traffic was modified to include a reference to JavaScript that generated the DDoS code to overwhelm target web servers.3
For attacks attempting to saturate the providing network, see Network Denial of Service.
Item | Value |
---|---|
ID | T1499 |
Sub-techniques | T1499.001, T1499.002, T1499.003, T1499.004 |
Tactics | TA0040 |
Platforms | Azure AD, Containers, Google Workspace, IaaS, Linux, Office 365, SaaS, Windows, macOS |
Version | 1.1 |
Created | 18 April 2019 |
Last Modified | 30 March 2023 |
Procedure Examples
ID | Name | Description |
---|---|---|
S0052 | OnionDuke | OnionDuke has the capability to use a Denial of Service module.8 |
G0034 | Sandworm Team | Sandworm Team temporarily disrupted service to Georgian government, non-government, and private sector websites after compromising a Georgian web hosting provider in 2019.11 |
S0412 | ZxShell | ZxShell has a feature to perform SYN flood attack on a host.109 |
Mitigations
ID | Mitigation | Description |
---|---|---|
M1037 | Filter Network Traffic | Leverage services provided by Content Delivery Networks (CDN) or providers specializing in DoS mitigations to filter traffic upstream from services.7 Filter boundary traffic by blocking source addresses sourcing the attack, blocking ports that are being targeted, or blocking protocols being used for transport. To defend against SYN floods, enable SYN Cookies. |
Detection
ID | Data Source | Data Component |
---|---|---|
DS0015 | Application Log | Application Log Content |
DS0029 | Network Traffic | Network Traffic Content |
DS0013 | Sensor Health | Host Status |
References
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Cisco. (n.d.). Detecting and Analyzing Network Threats With NetFlow. Retrieved April 25, 2019. ↩
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FS-ISAC. (2012, September 17). Fraud Alert – Cyber Criminals Targeting Financial Institution Employee Credentials to Conduct Wire Transfer Fraud. Retrieved April 18, 2019. ↩
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Goodin, D.. (2015, March 31). Massive denial-of-service attack on GitHub tied to Chinese government. Retrieved April 19, 2019. ↩
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Ned Moran, Mike Scott, Mike Oppenheim of FireEye. (2014, November 3). Operation Poisoned Handover: Unveiling Ties Between APT Activity in Hong Kong’s Pro-Democracy Movement. Retrieved April 18, 2019. ↩
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Preet Bharara, US Attorney. (2016, March 24). Retrieved April 23, 2019. ↩
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Wueest, C.. (2014, October 21). The continued rise of DDoS attacks. Retrieved April 24, 2019. ↩
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Meintanis, S., Revuelto, V., Socha, K.. (2017, March 10). DDoS Overview and Response Guide. Retrieved April 24, 2019. ↩
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Faou, M., Tartare, M., Dupuy, T. (2019, October). OPERATION GHOST. Retrieved September 23, 2020. ↩
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Allievi, A., et al. (2014, October 28). Threat Spotlight: Group 72, Opening the ZxShell. Retrieved September 24, 2019. ↩
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Fraser, N., et al. (2019, August 7). Double DragonAPT41, a dual espionage and cyber crime operation APT41. Retrieved September 23, 2019. ↩
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Scott W. Brady. (2020, October 15). United States vs. Yuriy Sergeyevich Andrienko et al.. Retrieved November 25, 2020. ↩