An adversary, through a previously installed malicious application, performs malicious actions against a third-party Software as a Service (SaaS) application (also known as a cloud based application) by leveraging the persistent and implicit trust placed on a trusted user's session. This attack is executed after a trusted user is authenticated into a cloud service, "piggy-backing" on the authenticated session, and exploiting the fact that the cloud service believes it is only interacting with the trusted user. If successful, the actions embedded in the malicious application will be processed and accepted by the targeted SaaS application and executed at the trusted user's privilege level.
Likelihood Of Attack
The table(s) below shows the other attack patterns and high level categories that are related to this attack pattern. These relationships are defined as ChildOf, ParentOf, MemberOf and give insight to similar items that may exist at higher and lower levels of abstraction. In addition, relationships such as CanFollow, PeerOf, and CanAlsoBe are defined to show similar attack patterns that the user may want to explore.
Meta Attack Pattern - A meta level attack pattern in CAPEC is a decidedly abstract characterization of a specific methodology or technique used in an attack. A meta attack pattern is often void of a specific technology or implementation and is meant to provide an understanding of a high level approach. A meta level attack pattern is a generalization of related group of standard level attack patterns. Meta level attack patterns are particularly useful for architecture and design level threat modeling exercises.
An adversary must be able install a purpose built malicious application onto the trusted user's system and convince the user to execute it while authenticated to the SaaS application.
This attack pattern often requires the technical ability to modify a malicious software package (e.g. Zeus) to spider a targeted site and a way to trick a user into a malicious software download.
To limit one's exposure to this type of attack, tunnel communications through a secure proxy service.
Detection of this type of attack can be done through heuristic analysis of behavioral anomalies (a la credit card fraud detection) which can be used to identify inhuman behavioral patterns. (e.g., spidering)
A Related Weakness relationship associates a weakness with this attack pattern. Each association implies a weakness that must exist for a given attack to be successful. If multiple weaknesses are associated with the attack pattern, then any of the weaknesses (but not necessarily all) may be present for the attack to be successful. Each related weakness is identified by a CWE identifier.
SaaS/Cloud applications are often accessed from unmanaged systems and devices, over untrusted networks that are outside corporate IT control. The likelihood of a cloud service being accessed by a trusted user though an untrusted device is high. Several instances of this style of attack have been found.
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Page Last Updated or Reviewed:
July 31, 2018