CVE-2026-12822
Received Received - Intake
Code Injection in Langflow AI up to 1.9.3

Publication date: 2026-06-22

Last updated on: 2026-06-22

Assigner: VulDB

Description
A vulnerability was identified in langflow-ai langflow up to 1.9.3. This affects an unknown function of the component Bundle URL Loader. The manipulation leads to code injection. The attack needs to be performed locally. The vendor was contacted early about this disclosure but did not respond in any way.
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Meta Information
Published
2026-06-22
Last Modified
2026-06-22
Generated
2026-06-22
AI Q&A
2026-06-22
EPSS Evaluated
N/A
NVD
EUVD
Affected Vendors & Products
Showing 1 associated CPE
Vendor Product Version / Range
langflow-ai langflow to 1.9.3 (inc)
Helpful Resources
Exploitability
CWE
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KEV
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CWE ID Description
CWE-94 The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.
CWE-74 The product constructs all or part of a command, data structure, or record using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify how it is parsed or interpreted when it is sent to a downstream component.
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Executive Summary

The vulnerability in langflow-ai langflow up to version 1.9.3 involves a component called Bundle URL Loader. This vulnerability allows an attacker to inject and execute arbitrary code by manipulating bundle URLs that load remote custom components.

Langflow automatically executes Python code from these remote bundles during startup or processing without proper verification or trust boundaries. An attacker who can control or manipulate these bundle URLs or deployment templates can exploit this flaw to run arbitrary code on the Langflow server.

The attack requires local access to the system and can lead to full system compromise if successfully exploited.

Impact Analysis

This vulnerability can lead to remote code execution on the Langflow server, allowing an attacker to run arbitrary Python code with the privileges of the Langflow process.

Successful exploitation can result in full system compromise, including unauthorized access, data theft, modification, or destruction, and potentially further attacks within the network.

Detection Guidance

Detection of this vulnerability involves identifying if Langflow is loading remote bundle URLs that execute Python code without proper validation.

Since the vulnerability arises from automatic execution of Python code from remote bundles during startup or processing, monitoring for unusual or unauthorized Python processes or network connections related to bundle URLs can help detect exploitation attempts.

  • Check running Langflow processes and their startup parameters for references to remote bundle URLs.
  • Use network monitoring tools (e.g., tcpdump, Wireshark) to detect outgoing connections to suspicious or unknown remote bundle URLs.
  • Search Langflow configuration files or deployment templates for remote bundle URL entries.
  • Example commands:
  • 1. To find references to remote bundles in configuration or deployment files: grep -r 'http://' /path/to/langflow/configs
  • 2. To monitor Python processes related to Langflow: ps aux | grep langflow
  • 3. To capture network traffic for suspicious connections: sudo tcpdump -i any host suspicious_bundle_url
Mitigation Strategies

Immediate mitigation steps include disabling the automatic import and execution of remote bundle URLs in Langflow.

Specifically, you should:

  • Disable auto-import of remote components to prevent untrusted code execution.
  • Require explicit trust approval before loading any remote bundles.
  • Enforce signature verification or maintain an allowlist of trusted bundles.
  • Sandbox the loading of components to limit potential damage from malicious code.
  • Disable remote bundle URLs by default in production environments.

These steps help prevent arbitrary code execution and reduce the risk of full system compromise.

Compliance Impact

The provided information does not specify how this vulnerability impacts compliance with common standards and regulations such as GDPR or HIPAA.

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