| Name |
Oversized Serialized Data Payloads |
|
| Likelyhood of attack |
Typical severity |
| Medium |
High |
|
| Summary |
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. |
| 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. |
| Execution Flow |
| Step |
Phase |
Description |
Techniques |
| 1 |
Explore |
An adversary determines the input data stream that is being processed by an serialized data parser on the victim's side. |
|
| 2 |
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. |
|
|
| Solutions | 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 |
|
CWE ID
|
Description
|
| CWE-19 |
Data Processing Errors |
| CWE-20 |
Improper Input Validation |
| CWE-112 |
Missing XML Validation |
| CWE-674 |
Uncontrolled Recursion |
| CWE-770 |
Allocation of Resources Without Limits or Throttling |
|
| Related CAPECS |
|
CAPEC ID
|
Description
|
| CAPEC-130 |
An adversary causes the target to allocate excessive resources to servicing the attackers' request, thereby reducing the resources available for legitimate services and degrading or denying services. Usually, this attack focuses on memory allocation, but any finite resource on the target could be the attacked, including bandwidth, processing cycles, or other resources. This attack does not attempt to force this allocation through a large number of requests (that would be Resource Depletion through Flooding) but instead uses one or a small number of requests that are carefully formatted to force the target to allocate excessive resources to service this request(s). Often this attack takes advantage of a bug in the target to cause the target to allocate resources vastly beyond what would be needed for a normal request. |
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