langchain-ai langsmith-sdk information disclosure

Summaryinfo

A vulnerability classified as problematic was found in langchain-ai langsmith-sdk. Affected is an unknown function. Such manipulation leads to information disclosure. This vulnerability is uniquely identified as CVE-2026-41182. The attack can be launched remotely. No exploit exists. Upgrading the affected component is advised.

Detailsinfo

A vulnerability was found in langchain-ai langsmith-sdk (version unknown). It has been rated as problematic. Affected by this issue is an unknown function. The manipulation with an unknown input leads to a information disclosure vulnerability. Using CWE to declare the problem leads to CWE-200. The product exposes sensitive information to an actor that is not explicitly authorized to have access to that information. Impacted is confidentiality. CVE summarizes:

LangSmith Client SDKs provide SDK's for interacting with the LangSmith platform. Prior to version 0.5.19 of the JavaScript SDK and version 0.7.31 of the Python SDK, the LangSmith SDK's output redaction controls (hideOutputs in JS, hide_outputs in Python) do not apply to streaming token events. When an LLM run produces streaming output, each chunk is recorded as a new_token event containing the raw token value. These events bypass the redaction pipeline entirely — prepareRunCreateOrUpdateInputs (JS) and _hide_run_outputs (Python) only process the inputs and outputs fields on a run, never the events array. As a result, applications relying on output redaction to prevent sensitive LLM output from being stored in LangSmith will still leak the full streamed content via run events. Version 0.5.19 of the JavaScript SDK and version 0.7.31 of the Python SDK fix the issue.

The advisory is shared for download at github.com. This vulnerability is handled as CVE-2026-41182 since 04/17/2026. The exploitation is known to be easy. The attack may be launched remotely. No form of authentication is required for exploitation. There are neither technical details nor an exploit publicly available. The MITRE ATT&CK project declares the attack technique as T1592.

Upgrading eliminates this vulnerability.

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Productinfo

Type

• Artificial Intelligence Software

Vendor

• langchain-ai

Name

• langsmith-sdk

Website

• Product: https://github.com/langchain-ai/langsmith-sdk/

CPE 2.3info

• 🔒

CPE 2.2info

• 🔒

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