Endpoint Denial of Service: Application Exhaustion Flood

Adversaries may target resource intensive features of applications to cause a denial of service (DoS), denying availability to those applications. For example, specific features in web applications may be highly resource intensive. Repeated requests to those features may be able to exhaust system resources and deny access to the application or the server itself.[1]

ID: T1499.003
Sub-technique of:  T1499
Tactic: Impact
Platforms: Azure AD, Google Workspace, IaaS, Linux, Office 365, SaaS, Windows, macOS
Impact Type: Availability
Version: 1.2
Created: 20 February 2020
Last Modified: 25 March 2022

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.[2] Filter boundary traffic by blocking source addresses sourcing the attack, blocking ports that are being targeted, or blocking protocols being used for transport.

Detection

ID Data Source Data Component Detects
DS0015 Application Log Application Log Content

Monitor for third-party application logging, messaging, and/or other artifacts that may target resource intensive features of web applications to cause a denial of service (DoS). 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.

DS0029 Network Traffic Network Traffic Content

Monitor and analyze traffic patterns and packet inspection associated to protocol(s), leveraging SSL/TLS inspection for encrypted traffic, that do not follow the expected protocol standards and traffic flows (e.g extraneous packets that do not belong to established flows, gratuitous or anomalous traffic patterns, anomalous syntax, or structure). Consider correlation with process monitoring and command line to detect anomalous processes execution and command line arguments associated to traffic patterns (e.g. monitor anomalies in use of files that do not normally initiate connections for respective protocol(s)).

Network Traffic Flow

Monitor network data for uncommon data flows. Processes utilizing the network that do not normally have network communication or have never been seen before are suspicious.

DS0013 Sensor Health Host Status

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. Monitor for logging, messaging, and other artifacts highlighting the health of host sensors (ex: metrics, errors, and/or exceptions from logging applications)

References