Flowise AI CVE-2025-59528 RCE Exploitation: Mitigation Guide

Recent threat intelligence reports indicate that Flowise, a widely adopted open-source platform for building LLM-based applications, is under active exploitation. According to The Hacker News, security researchers at VulnCheck have identified a maximum-severity vulnerability, tracked as CVE-2025-59528, which carries a CVSS score of 10.0. This flaw allows unauthenticated attackers to achieve RCE by exploiting the application’s handling of configuration settings within its low-code environment.

Technical Analysis of CVE-2025-59528

The vulnerability resides in the CustomMCP node, a feature designed to allow users to integrate with Model Context Protocol (MCP) servers. The core issue is a code injection vulnerability where user-supplied input is insufficiently sanitized before being executed in a sensitive context. Specifically, the CVE manifests when the application processes configuration settings for connecting to external MCP servers.

Because Flowise often runs with significant permissions to interact with enterprise data sources, vectoring an exploit through this node provides a gateway for Lateral Movement within the internal network. The research suggests that the exploitation does not require prior authentication if the Flowise instance is exposed directly to the internet, which is a common misconfiguration in rapid AI development deployments.

How to Detect CVE-2025-59528 Exploit in Production Environments

VulnCheck reported that over 12,000 instances of Flowise are currently exposed to the internet. For many of these instances, the management interface is accessible without MFA or network restrictions, significantly increasing the risk. Security teams need to understand how to detect CVE-2025-59528 exploit attempts by monitoring application logs for unusual outbound connections from the Flowise service or unexpected child processes spawned by the Node.js runtime.

Key IoC patterns include:

• Unusual HTTP POST requests to endpoints associated with the CustomMCP node configuration.
• Spikes in outbound traffic to unknown IP addresses, which may indicate a C2 callback.
• Evidence of shell execution or credential access attempts originating from the user account running the Flowise process.

Remediation and Mitigation Strategies

The primary Flowise AI CustomMCP node RCE mitigation strategy is the immediate application of security patches. Users should upgrade to the latest version of Flowise where the vulnerable code has been refactored to prevent arbitrary code injection. Beyond patching, organizations must implement a Zero Trust architecture, ensuring that AI management interfaces are never exposed directly to the public internet.

Implementing an EDR solution on the host server can help detect post-exploitation activity, while a SIEM should be configured to alert on anomalous traffic patterns. It is essential to patch Flowise AI agent builder vulnerability instances across all development, staging, and production environments. Failing to secure these tools could result in a significant Supply Chain Attack surface, as compromised agents may be used to exfiltrate proprietary data or poison AI model outputs.