CVE-2026-45082

May 26, 2026, 8:24 p.m.

7.6
High

Description

Karakeep is a elf-hostable bookmark-everything app. A Server-Side Request Forgery (SSRF) protection bypass vulnerability was identified in versions prior to 0.32.0 affecting redirect-following processing components. Although the application implements protections intended to prevent requests toward internal/private network destinations, these protections could be bypassed through crafted HTTP redirect chains. By leveraging attacker-controlled redirects, an authenticated user could cause vulnerable application components to initiate requests toward internally reachable Docker network services accessible from the application environment. The issue affected multiple processing paths, including crawler-related functionality and video download processing flows. Version 0.32.0 contains a patch.

Product(s) Impacted

Vendor Product Versions
Karakeep
  • Karakeep
  • <0.32.0

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 karakeep karakeep <0.32.0 / / / / / / /

CVSS Score

7.6 / 10

CVSS Data - 3.1

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Privileges Required: LOW
  • Scope: UNCHANGED
  • Confidentiality Impact: HIGH
  • Integrity Impact: LOW
  • Availability Impact: LOW
  • CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:L

    View Vector String

Timeline

Published: May 26, 2026, 3:16 p.m.
Last Modified: May 26, 2026, 8:24 p.m.

Status : Deferred

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

More info

*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.