An adversary injects oversized serialized data payloads into a parser during data processing to produce adverse effects upon the parser such as exhausting system resources and arbitrary code execution.
Extended Description
Applications often need to transform data in and out of serialized data formats, such as XML and YAML, by using a data parser. It may be possible for an adversary to inject data that may have an adverse effect on the parser when it is being processed. By supplying oversized payloads in input vectors that will be processed by the parser, an adversary can cause the parser to consume more resources while processing, causing excessive memory consumption and CPU utilization, and potentially cause execution of arbitrary code. An adversary's goal is to leverage parser failure to their advantage. DoS is most closely associated with web services, SOAP, and Rest, because remote service requesters can post malicious data payloads to the service provider designed to exhaust the service provider's memory, CPU, and/or disk space. This attack exploits the loosely coupled nature of web services, where the service provider has little to no control over the service requester and any messages the service requester sends.
Alternate Terms
Term: XML Denial of Service (XML DoS)
Likelihood Of Attack
Medium
Typical Severity
High
Relationships
This table shows the other attack patterns and high level categories that are related to this attack pattern. These relationships are defined as ChildOf and ParentOf, 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.
Nature
Type
ID
Name
ChildOf
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.
Detailed Attack Pattern - A detailed level attack pattern in CAPEC provides a low level of detail, typically leveraging a specific technique and targeting a specific technology, and expresses a complete execution flow. Detailed attack patterns are more specific than meta attack patterns and standard attack patterns and often require a specific protection mechanism to mitigate actual attacks. A detailed level attack pattern often will leverage a number of different standard level attack patterns chained together to accomplish a goal.
Detailed Attack Pattern - A detailed level attack pattern in CAPEC provides a low level of detail, typically leveraging a specific technique and targeting a specific technology, and expresses a complete execution flow. Detailed attack patterns are more specific than meta attack patterns and standard attack patterns and often require a specific protection mechanism to mitigate actual attacks. A detailed level attack pattern often will leverage a number of different standard level attack patterns chained together to accomplish a goal.
An adversary determines the input data stream that is being processed by an serialized data parser on the victim's side.
Experiment
An adversary crafts input data that may have an adverse effect on the operation of the data parser when the data is parsed on the victim's system.
Prerequisites
An application uses an parser for serialized data to perform transformation on user-controllable data.
An application does not perform sufficient validation to ensure that user-controllable data is safe for a data parser.
Skills Required
[Level: Low]
Denial of service
[Level: High]
Arbitrary code execution
Indicators
Bad data is passed to the serialized data parser (possibly repeatedly), possibly making it crash or execute arbitrary code.
Consequences
This table specifies different individual consequences associated with the attack pattern. The Scope identifies the security property that is violated, while the Impact describes the negative technical impact that arises if an adversary succeeds in their attack. The Likelihood provides information about how likely the specific consequence is expected to be seen relative to the other consequences in the list. For example, there may be high likelihood that a pattern will be used to achieve a certain impact, but a low likelihood that it will be exploited to achieve a different impact.
Scope
Impact
Likelihood
Availability
Resource Consumption
Confidentiality
Read Data
Confidentiality
Integrity
Availability
Execute Unauthorized Commands
Confidentiality
Access Control
Authorization
Gain Privileges
Mitigations
Carefully validate and sanitize all user-controllable serialized data prior to passing it to the parser routine. Ensure that the resultant data is safe to pass to the parser.
Perform validation on canonical data.
Pick a robust implementation of the serialized data parser.
Validate data against a valid schema or DTD prior to parsing.
Related Weaknesses
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.
Allocation of Resources Without Limits or Throttling
Notes
Other
In many cases this type of an attack will result in an XML Denial of Service (XDoS) or similar Denial of Service (DoS) due to an application becoming unstable, freezing, or crashing. However it is possible to cause a crash resulting in arbitrary code execution, leading to a jump from the data plane to the control plane [REF-89].
Other
The main weakness in serialized data related DoS is that the service provider generally must inspect, parse, and validate the data messages to determine routing, workflow, security considerations, and so on. It is exactly these inspection, parsing, and validation routines that DoS targets.
Taxonomy Mappings
CAPEC mappings to ATT&CK techniques leverage an inheritance model to streamline and minimize direct CAPEC/ATT&CK mappings. Inheritance of a mapping is indicated by text stating that the parent CAPEC has relevant ATT&CK mappings. Note that the ATT&CK Enterprise Framework does not use an inheritance model as part of the mapping to CAPEC.
Relevant to the ATT&CK taxonomy mapping (see
parent
)
Description
This table shows the other attack patterns and high level categories that are related to this attack pattern. These relationships are defined as ChildOf and ParentOf, 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.
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