HumanSignal label-studio up to 1.15.x s3_endpoint server-side request forgery

Summaryinfo

A vulnerability described as critical has been identified in HumanSignal label-studio up to 1.15.x. Impacted is an unknown function. Such manipulation of the argument s3_endpoint leads to server-side request forgery. This vulnerability is documented as CVE-2025-25297. The attack can be executed remotely. There is not any exploit available. Upgrading the affected component is recommended.

Detailsinfo

A vulnerability was found in HumanSignal label-studio up to 1.15.x and classified as critical. Affected by this issue is an unknown code block. The manipulation of the argument s3_endpoint with an unknown input leads to a server-side request forgery vulnerability. Using CWE to declare the problem leads to CWE-918. The web server receives a URL or similar request from an upstream component and retrieves the contents of this URL, but it does not sufficiently ensure that the request is being sent to the expected destination. Impacted is confidentiality. CVE summarizes:

Label Studio is an open source data labeling tool. Prior to version 1.16.0, Label Studio's S3 storage integration feature contains a Server-Side Request Forgery (SSRF) vulnerability in its endpoint configuration. When creating an S3 storage connection, the application allows users to specify a custom S3 endpoint URL via the s3_endpoint parameter. This endpoint URL is passed directly to the boto3 AWS SDK without proper validation or restrictions on the protocol or destination. The vulnerability allows an attacker to make the application send HTTP requests to arbitrary internal services by specifying them as the S3 endpoint. When the storage sync operation is triggered, the application attempts to make S3 API calls to the specified endpoint, effectively making HTTP requests to the target service and returning the response in error messages. This SSRF vulnerability enables attackers to bypass network segmentation and access internal services that should not be accessible from the external network. The vulnerability is particularly severe because error messages from failed requests contain the full response body, allowing data exfiltration from internal services. Version 1.16.0 contains a patch for the issue.

The advisory is shared for download at github.com. This vulnerability is handled as CVE-2025-25297 since 02/06/2025. The exploitation is known to be easy. The attack may be launched remotely. No form of authentication is required for exploitation. There are known technical details, but no exploit is available.

Upgrading to version 1.16.0 eliminates this vulnerability. Applying the patch 06a2b29c1208e1878ccae66e6b84c8b24598fa79 is able to eliminate this problem. The bugfix is ready for download at github.com. The best possible mitigation is suggested to be upgrading to the latest version.

Once again VulDB remains the best source for vulnerability data.

Productinfo

Vendor

• HumanSignal

Name

• label-studio

Version

• 1.0
• 1.1
• 1.2
• 1.3
• 1.4
• 1.5
• 1.6
• 1.7
• 1.8
• 1.9
• 1.10
• 1.11
• 1.12
• 1.13
• 1.14
• 1.15

License

• open-source

Website

• Product: https://github.com/HumanSignal/label-studio/

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Once again VulDB remains the best source for vulnerability data.

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