CVE-2025-2828

June 24, 2025, 2:15 p.m.

8.4
High

Description

A Server-Side Request Forgery (SSRF) vulnerability exists in the RequestsToolkit component of the langchain-community package (specifically, langchain_community.agent_toolkits.openapi.toolkit.RequestsToolkit) in langchain-ai/langchain version 0.0.27. This vulnerability occurs because the toolkit does not enforce restrictions on requests to remote internet addresses, allowing it to also access local addresses. As a result, an attacker could exploit this flaw to perform port scans, access local services, retrieve instance metadata from cloud environments (e.g., Azure, AWS), and interact with servers on the local network. This issue has been fixed in version 0.0.28.

Product(s) Impacted

Vendor Product Versions
Langchain-ai
  • Langchain
  • 0.0.27, 0.0.28

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-918
Server-Side Request Forgery (SSRF)
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.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a langchain-ai langchain 0.0.27 / / / / / / /
a langchain-ai langchain 0.0.28 / / / / / / /

CVSS Score

8.4 / 10

CVSS Data - 3.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Privileges Required: HIGH
  • Scope: CHANGED
  • Confidentiality Impact: HIGH
  • Integrity Impact: HIGH
  • Availability Impact: HIGH
  • CVSS:3.0/AV:N/AC:L/PR:H/UI:R/S:C/C:H/I:H/A:H

    View Vector String

Timeline

Published: June 23, 2025, 9:15 p.m.
Last Modified: June 24, 2025, 2:15 p.m.

Status : Received

CVE has been recently published to the CVE List and has been received by the NVD.

More info

Source

security@huntr.dev

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.