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 purposes(Citation: FireEye OpPoisonedHandover February 2016) and to support other malicious activities, including distraction(Citation: FSISAC FraudNetDoS September 2012), hacktivism, and extortion.(Citation: Symantec DDoS October 2014)

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.(Citation: USNYAG IranianBotnet March 2016)

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.(Citation: ArsTechnica Great Firewall of China)

For attacks attempting to saturate the providing network, see [Network Denial of Service](https://attack.mitre.org/techniques/T1498).


Platforms: Windows
Azure AD
Office 365
SaaS
IaaS
Linux
macOS
Google Workspace
Containers
Tactics:
phase_name: impact

Detection:
Detection of Endpoint DoS can sometimes be achieved before the effect is sufficient to cause significant impact to the availability of the service, but such response time typically requires very aggressive monitoring and responsiveness. Typical network throughput monitoring tools such as netflow, SNMP, and custom scripts can be used to detect sudden increases in circuit utilization.(Citation: Cisco DoSdetectNetflow) Real-time, automated, and qualitative study of the network traffic can identify a sudden surge in one type of protocol can be used to detect an attack as it starts.

In addition to network level detections, endpoint logging and instrumentation can be useful for detection. Attacks targeting web applications may generate logs in the web server, application server, and/or database server that can be used to identify the type of attack, possibly before the impact is felt.

Externally monitor the availability of services that may be targeted by an Endpoint DoS.

References:
source_name: mitre-attack
description: Cisco. (n.d.). Detecting and Analyzing Network Threats With NetFlow. Retrieved April 25, 2019.
source_name: Cisco DoSdetectNetflow
description: FS-ISAC. (2012, September 17). Fraud Alert – Cyber Criminals Targeting Financial Institution Employee Credentials to Conduct Wire Transfer Fraud. Retrieved April 18, 2019.
source_name: FSISAC FraudNetDoS September 2012
description: Goodin, D.. (2015, March 31). Massive denial-of-service attack on GitHub tied to Chinese government. Retrieved April 19, 2019.
source_name: ArsTechnica Great Firewall of China
description: 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.
source_name: FireEye OpPoisonedHandover February 2016
description: Preet Bharara, US Attorney. (2016, March 24). Retrieved April 23, 2019.
source_name: USNYAG IranianBotnet March 2016
description: Wueest, C.. (2014, October 21). The continued rise of DDoS attacks. Retrieved April 24, 2019.
source_name: Symantec DDoS October 2014