CAPEC-231 Oversized Serialized Data Payloads

CAPEC ID: 231

CAPEC-231 Metadata

Likelihood of Attack

Medium

Typical Severity

High

Overview

Summary

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.

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.

Potential Solutions / 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 (CWE)

CWE ID Description
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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