Skip to content

AWS Encryption SDK for Python: Key commitment policy bypass via shared key cache

Moderate severity GitHub Reviewed Published Apr 20, 2026 in aws/aws-encryption-sdk-python • Updated Apr 24, 2026

Package

pip aws-encryption-sdk (pip)

Affected versions

>= 2.0.0, < 3.3.0
>= 4.0.0, < 4.0.4

Patched versions

3.3.1
4.0.5

Description

Summary

AWS Encryption SDK (ESDK) for Python is a client-side encryption library. An issue exists where, under certain circumstances, a specific cryptographic algorithm downgrade in the caching layer might allow an authenticated local threat actor to bypass key commitment policy enforcement via a shared key cache, resulting in ciphertext that can be decrypted to multiple different plaintexts.

Impact

This issue requires all of the following conditions to be true: (1) Two ESDK for Python clients with different commitment policies share a single CachingCryptoMaterialsManager instance within the same process. (2) The client with the weaker commitment policy encrypts first, warming the cache. (3) Both clients use matching encryption contexts. (4) Both clients use the pre-configured default algorithm suite.

These conditions may occur during a migration from ESDK for Python v1 to newer versions, as v1 did not support key commitment.

When the weaker-policy client encrypts first, the cache stores encryption materials that do not enforce key commitment. Subsequent callers — including those configured to require key commitment — are served these cached materials instead of generating new ones that satisfy their policy. This results in encryption without key commitment, meaning the same ciphertext can be validly decrypted to different plaintexts under different keys (the "Invisible Salamanders" issue; see GHSA-wqgp-vphw-hphf). A threat actor who controls ciphertext can cause a recipient to decrypt a message different from what the sender encrypted, breaking message integrity.

Impacted versions

  • From 2.0 to 2.5.1
  • From 3.0 to 3.3.0
  • From 4.0 to 4.0.4

Patches

This issue has been addressed in ESDK for Python versions 3.3.1 and 4.0.5. We recommend upgrading to the latest version and ensuring any forked or derivative code is patched to incorporate the new fixes.

Workarounds

If a customer requires operating multiple instances of the Python ESDK each with differently configured key commitment policies, they must not share a key cache.

References
If there are any questions or comments about this advisory, contact AWS Security through the vulnerability reporting page or directly via email to aws-security@amazon.com. Please do not create a public GitHub issue.

Acknowledgement

Thanks to 1seal.org for collaborating on this issue through the coordinated vulnerability disclosure process.

References

@antonf-amzn antonf-amzn published to aws/aws-encryption-sdk-python Apr 20, 2026
Published by the National Vulnerability Database Apr 20, 2026
Published to the GitHub Advisory Database Apr 24, 2026
Reviewed Apr 24, 2026
Last updated Apr 24, 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 Local
Attack Complexity High
Attack Requirements Present
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity High
Availability None
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:L/AC:H/AT:P/PR:L/UI:N/VC:N/VI:H/VA:N/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.
(1st percentile)

Weaknesses

Selection of Less-Secure Algorithm During Negotiation ('Algorithm Downgrade')

A protocol or its implementation supports interaction between multiple actors and allows those actors to negotiate which algorithm should be used as a protection mechanism such as encryption or authentication, but it does not select the strongest algorithm that is available to both parties. Learn more on MITRE.

CVE ID

CVE-2026-6550

GHSA ID

GHSA-v638-38fc-rhfv

Source code

Loading Checking history
See something to contribute? Suggest improvements for this vulnerability.