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joserfc: Compact JWS size guard allocates attacker-controlled segments before rejection

Moderate severity GitHub Reviewed Published Oct 6, 2026 in authlib/joserfc • Updated Oct 30, 2026

Package

pip joserfc (pip)

Affected versions

< 1.7.6

Patched versions

1.7.6

Description

Summary

joserfc 1.7.4 defines compact-JWS header, payload, and signature limits, but
calls value.split(b".") before validating them. Python bytes.split() copies
the attacker-controlled segments, so the current guard allocates roughly one
complete payload before rejecting it.

Reproduction

.venv-research/bin/python 06-practical-testing/preauth-memory-profile.py

The input is resident before a fork-isolated verifier runs, and every signature
is invalid.

Input Peak RSS delta Amplification Result
1 MiB 1.11 MiB 1.11× size rejected
4 MiB 4.04 MiB 1.01× size rejected
8 MiB 8.04 MiB 1.01× size rejected
16 MiB 16.04 MiB 1.00× size rejected
32 MiB 31.74 MiB 0.99× size rejected
64 MiB 63.80 MiB 1.00× size rejected

The unconstrained profile is the primary evidence: joserfc allocates an
additional attacker-sized object before producing its intended
ExceededSizeError. A separate baseline-plus-headroom stress test raises
MemoryError when that copy cannot fit, but this report does not characterize
an absolute RLIMIT_AS value as a realistic worker memory budget.

Security Argument

The issue is not that joserfc can prevent the transport layer from receiving a
large header. The issue is narrower: once bytes reach deserialize_compact(),
the library's existing size guard cannot fulfill its allocation-limiting purpose
because attacker-controlled segment copies are created first.

This differs from
GHSA-frfh-8v73-gjg4,
which concerned embedding already-loaded oversized segments in exception and log
messages. Here, the current implementation itself creates an additional
payload-sized allocation before its fixed size exception.

Recommended Fix

Check len(value) against a maximum compact-serialization size before
split(). If per-segment diagnostics are needed, locate delimiters with bounded
find() operations or memory views, validate offsets and lengths, and only then
materialize acceptable segments.

References

@lepture lepture published to authlib/joserfc Oct 6, 2026
Published by the National Vulnerability Database Oct 29, 2026
Published to the GitHub Advisory Database Oct 30, 2026
Reviewed Oct 30, 2026
Last updated Oct 30, 2026

Severity

Moderate

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 None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability Low
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

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:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(9th percentile)

Weaknesses

Uncontrolled Resource Consumption

The product does not properly control the allocation and maintenance of a limited resource. Learn more on MITRE.

CVE ID

CVE-2026-119284

GHSA ID

GHSA-9pg5-8c7x-5hfx

Source code

Credits

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