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Litestar allows unbounded resource consumption (DoS vulnerability)

High severity GitHub Reviewed Published Nov 20, 2024 in litestar-org/litestar • Updated Nov 20, 2024

Package

pip litestar (pip)

Affected versions

<= 2.12.1

Patched versions

None

Description

Summary

Litestar offers multiple methods to return a parsed representation of the request body, as well as extractors that rely on those parsers to map request content to structured data types. Multiple of those parsers do not have size limits when reading the request body into memory, which allows an attacker to cause excessive memory consumption on the server by sending large requests.

Details

The Request methods to parse json, msgpack or form-data all read the entire request stream into memory via await self.body() without a prior size check or size limit. There may be other places (e.g. extractors) where this can happen.

For most formats, a configurable size limit would be sufficient to mitigate this issue. The total request size can also be limited by a proxy (e.g. nginx) in front of the actual application as a workaround. However, for applications that actually want to accept large file uploads via multipart/form-data, a simple size limit would not be practical. The multipart parser currently used by Litestar expects a single byte string as input and does not support incremental parsing via Request.stream(). Applications could bypass the Litestar parser and use a streaming parser to read from Request.stream() instead, but that would not work with extractors and other features of the framework. Switching the parser for a different implementation is currently not possible via public APIs.

PoC

Start an applications that accesses Request.json(), Request.msgpack() or Request.form() or uses an extractor that relies on those parsers internally, and send a large request with a matching content type. The actual content of the request does not matter. For example: curl -F "foo=</dev/random" http://127.0.0.1:8000/) for multipart/form-data. Server memory consumption will increase very quickly until memory (and swap) are exhausted.

Impact

This is a denial of service (DoS) vulnerability affecting all Litestar applications that process json, msgpack or form-data submission requests.

References

@provinzkraut provinzkraut published to litestar-org/litestar Nov 20, 2024
Published by the National Vulnerability Database Nov 20, 2024
Published to the GitHub Advisory Database Nov 20, 2024
Reviewed Nov 20, 2024
Last updated Nov 20, 2024

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements Present
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability Low

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:L

Weaknesses

CVE ID

CVE-2024-52581

GHSA ID

GHSA-gjcc-jvgw-wvwj

Source code

Credits

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