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SageMaker Python SDK replaced eval() with safe parser in JumpStart search functionality

High severity GitHub Reviewed Published Mar 5, 2026 in aws/sagemaker-python-sdk

Package

pip sagemaker (pip)

Affected versions

< 3.4.0

Patched versions

3.4.0

Description

Summary

This advisory addresses the use of the search_hub() function within the SageMaker Python SDK's JumpStart search functionality. An actor with the ability to control query parameters passed to the search_hub() function could potentially provide malformed input that causes the eval() function to execute arbitrary commands, access sensitive data, or compromise the execution environment.

A defense-in-depth enhancement has been implemented to replace code evaluation with safe string operations when processing search query parameters. This enhancement removes the use of eval() from the execution path, replacing it with a safe recursive descent parser. The change was released in SageMaker Python SDK version 3.4.0 on January 23, 2026. This advisory is informational to help customers understand their responsibilities regarding input validation and configuration security under the AWS Shared Responsibility Model.

Impact

Customer applications that pass unsanitized or untrusted input directly to the search_hub() function's query parameter could be prone to Remote Code Execution (RCE), potentially allowing attackers to execute arbitrary commands, access sensitive data, or compromise the execution environment. While the SDK was functioning within the requirements of the shared responsibility model—where input sanitization falls on the customer side—additional safeguards have been added to support secure customer implementations and provide defense-in-depth protection.

Impacted versions: All versions of SageMaker Python SDK prior to 3.4.0

Patches

On January 23, 2026, an enhancement was made to SageMaker Python SDK version 3.4.0, which replaces eval() with a safe recursive descent parser that uses string operations for pattern matching with proper operator precedence and exception handling. We recommend upgrading to version 3.4.0 or later, using the following command:

pip install --upgrade sagemaker>=3.4.0

Customers using forked or derivative code should incorporate the fixes from the referenced pull request.

Workarounds

No workarounds are needed, but as always you should ensure that your application is following security best practices:

  • Sanitize and validate input to SDK methods to ensure only expected formats are processed
  • Update to the latest SageMaker Python SDK release on a regular basis
  • Follow AWS security best practices for SDK configuration and usage
  • Ensure proper access controls are in place for environments where the SDK is deployed

References

If you have any questions or comments about this advisory, contact AWS Security via our vulnerability reporting page or email aws-security@amazon.com. Please do not create a public GitHub issue.

Acknowledgement

We thank Dan Aridor (@daridor9) and the security research community for bringing these customer security considerations to our attention through the coordinated disclosure process and for collaborating on this issue through responsible disclosure practices.

References

@mufaddal-rohawala mufaddal-rohawala published to aws/sagemaker-python-sdk Mar 5, 2026
Published to the GitHub Advisory Database Mar 5, 2026
Reviewed Mar 5, 2026

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 Local
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction Active
Vulnerable System Impact Metrics
Confidentiality High
Integrity High
Availability High
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:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

EPSS score

Weaknesses

Incomplete List of Disallowed Inputs

The product implements a protection mechanism that relies on a list of inputs (or properties of inputs) that are not allowed by policy or otherwise require other action to neutralize before additional processing takes place, but the list is incomplete. Learn more on MITRE.

CVE ID

No known CVE

GHSA ID

GHSA-5r2p-pjr8-7fh7

Source code

Credits

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