CVE-2026-4503

7.5

IBM · Langflow Desktop

IBM Langflow Desktop 1.0.0 through 1.8.4 contains an authorization bypass vulnerability that allows unauthenticated users to access other users' images via an insecure object reference.

Executive summary

A critical authorization flaw in IBM Langflow Desktop versions 1.0.0 through 1.8.4 allows unauthenticated attackers to access unauthorized image data, potentially leading to significant information disclosure.

Vulnerability

This vulnerability, identified as CWE-639, arises from an insecure direct object reference where user-controlled keys are not properly validated. An unauthenticated attacker can manipulate these keys to retrieve private images belonging to other users.

Business impact

The ability for unauthenticated parties to access sensitive user data poses a severe risk to data confidentiality and regulatory compliance. With a CVSS score of 7.5, this high-severity vulnerability could lead to the unauthorized exposure of proprietary or personal imagery stored within the application, resulting in potential reputational damage and loss of user trust.

Remediation

Immediate Action: Upgrade to IBM Langflow Desktop version 1.9.0 or newer immediately by utilizing the in-application update mechanism or downloading the latest installer from the official Langflow website.

Proactive Monitoring: Review application access logs for unusual patterns, such as sequential or high-frequency requests for image resources that do not correspond to standard user activity.

Compensating Controls: Deploy a Web Application Firewall to monitor and block abnormal HTTP requests containing suspicious object identifiers or unexpected parameter values.

Exploitation status

Public Exploit Available: No.

Analyst recommendation

Given the ease of exploitation and the potential for unauthorized data access, administrators must prioritize this update. Applying the patch to version 1.9.0 is the only effective way to remediate the underlying authorization logic failure and secure the application against potential data exposure incidents.

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