CVE-2024-58351
Received Received - Intake
Configuration Injection in Flowise Enables RCE and Data Exfiltration

Publication date: 2026-06-20

Last updated on: 2026-06-20

Assigner: VulnCheck

Description
Flowise before 2.1.4 allows configuration to be injected into the Chainflow during execution via the overrideConfig option, supported in both the frontend web integration and the backend Prediction API. Because this feature is enabled by default with no allow-list of permitted variables and relies on vm2 for sandboxing, an attacker can abuse it to achieve remote code execution and sandbox escape, denial of service by crashing the server, server-side request forgery, prompt injection, and server variable and data exfiltration. These issues are self-targeted and do not persist to other users.
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Meta Information
Published
2026-06-20
Last Modified
2026-06-20
Generated
2026-06-20
AI Q&A
2026-06-20
EPSS Evaluated
N/A
NVD
EUVD
Affected Vendors & Products
Showing 1 associated CPE
Vendor Product Version / Range
flowiseai flowise to 2.1.4 (exc)
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.
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Mitigation Strategies

To mitigate this vulnerability in Flowise versions prior to 2.1.4, you should disable the overrideConfig feature by default.

Implement an explicit allow-list of permitted variables to restrict configuration injection.

Remove the use of the vm2 sandbox and replace it with a more secure alternative such as the isolated-vm package.

Executive Summary

The vulnerability in Flowise before version 2.1.4 involves the overrideConfig feature, which allows configuration injection into the Chainflow during execution. This feature is enabled by default and lacks an allow-list of permitted variables. Because Flowise relies on the vm2 sandbox for security, which can be bypassed, an attacker can exploit this to perform remote code execution, escape the sandbox, cause denial of service by crashing the server, perform server-side request forgery, inject prompts, and exfiltrate server variables and data.

This vulnerability affects both the frontend web integration and the backend Prediction API. Although the issues are self-targeted and do not persist to other users, they pose significant risks to the server and business.

Impact Analysis

Exploitation of this vulnerability can lead to several severe impacts including remote code execution on the server, allowing attackers to run arbitrary code.

  • Sandbox escape, bypassing security restrictions intended to isolate code execution.
  • Denial of service by crashing the server, potentially making the service unavailable.
  • Server-side request forgery (SSRF), enabling attackers to make unauthorized requests from the server.
  • Prompt injection and full control over large language model (LLM) prompts.
  • Exfiltration of server variables and data, risking sensitive information leakage.

While these impacts are self-targeted and do not affect other users directly, they expose the server and business to significant security risks.

Compliance Impact

The vulnerability in Flowise before version 2.1.4 allows attackers to perform remote code execution, sandbox escape, denial of service, server-side request forgery, prompt injection, and data exfiltration. These security risks expose the server and business to potential unauthorized access and data breaches.

Although the issues are self-targeted and do not persist to other users, the ability to exfiltrate server variables and data could lead to violations of data protection regulations such as GDPR and HIPAA, which require safeguarding personal and sensitive data against unauthorized access and breaches.

Therefore, organizations using affected versions of Flowise may face compliance challenges if this vulnerability is exploited, as it undermines the confidentiality, integrity, and availability of data required by these standards.

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