CVE-2026-41265: Flowise Airtable Agent RCE Vulnerability

CVE-2026-41265 Overview

CVE-2026-41265 is a critical command injection vulnerability in Flowise, a popular drag-and-drop user interface for building customized large language model (LLM) flows. The vulnerability exists in the run method of the Airtable_Agents class and stems from improper sandboxing when evaluating LLM-generated Python scripts. An unauthenticated attacker can leverage prompt injection techniques to convince the LLM to respond with a malicious Python script, resulting in arbitrary command execution on the Flowise server.

Critical Impact

Unauthenticated attackers can achieve remote code execution on Flowise servers through prompt injection, potentially leading to complete server compromise, data exfiltration, and lateral movement within the network.

Affected Products

• Flowise versions prior to 3.1.0
• Deployments utilizing the Airtable Agent node in chatflows
• Any Flowise instance exposed to untrusted user prompts

Discovery Timeline

• April 23, 2026 - CVE-2026-41265 published to NVD
• April 23, 2026 - Last updated in NVD database

Technical Details for CVE-2026-41265

Vulnerability Analysis

This vulnerability represents a critical command injection flaw (CWE-77) that combines two dangerous attack vectors: prompt injection against an LLM and inadequate code execution sandboxing. The Flowise platform allows users to create custom LLM workflows, and the Airtable Agent node specifically enables interaction with Airtable databases through natural language queries.

The fundamental issue is that when the Airtable Agent processes user prompts, it may generate Python code to fulfill the request. This generated code is then executed on the server without proper sandboxing or validation. An attacker can craft malicious prompts designed to manipulate the LLM into generating Python code containing arbitrary system commands.

The attack is particularly dangerous because it requires no authentication—any user who can send prompts to a chatflow utilizing the Airtable Agent node can potentially exploit this vulnerability. The network-accessible nature of Flowise deployments means that internet-facing instances are at significant risk.

Root Cause

The root cause of CVE-2026-41265 lies in the run method of the Airtable_Agents class, which fails to implement proper sandboxing when executing LLM-generated Python scripts. The code evaluation mechanism trusts the output from the LLM without validating that the generated code is safe to execute. This creates a code injection pathway where attacker-controlled input (the prompt) can influence code that runs with the privileges of the Flowise server process.

The absence of input sanitization, code validation, or execution isolation means that any Python code the LLM can be convinced to generate will be executed directly on the host system.

Attack Vector

The attack leverages prompt injection—a technique where malicious instructions are embedded within user prompts to manipulate LLM behavior. The attacker sends carefully crafted prompts to a chatflow that uses the Airtable Agent node. These prompts are designed to override the LLM's intended behavior and trick it into generating Python code containing malicious commands.

The attack flow proceeds as follows: the attacker submits a prompt containing instructions that bypass the LLM's normal constraints. The LLM, interpreting these instructions, generates Python code that includes system commands chosen by the attacker. The Flowise Airtable_Agents class then executes this code without validation, running the attacker's commands with server-level privileges.

This vulnerability is exploitable over the network without authentication, making it accessible to any attacker who can reach the Flowise chatflow endpoint. Successful exploitation can result in complete server compromise, including the ability to read sensitive data, install backdoors, pivot to other systems, or disrupt operations.

Detection Methods for CVE-2026-41265

Indicators of Compromise

• Unusual Python process spawning from the Flowise application process
• System command execution originating from the Flowise server that doesn't match normal operational patterns
• Suspicious network connections initiated by the Flowise process to external addresses
• Unexpected file system modifications in Flowise installation directories or system paths
• Log entries showing atypical chatflow prompts containing code-like syntax or system command references

Detection Strategies

• Monitor application logs for prompts containing suspicious patterns such as import os, subprocess, eval, or exec references
• Implement network monitoring to detect anomalous outbound connections from Flowise server processes
• Deploy endpoint detection and response (EDR) solutions to identify unexpected child processes spawned by the Flowise application
• Analyze chatflow input logs for prompt injection patterns attempting to manipulate LLM behavior

Monitoring Recommendations

• Enable verbose logging for Flowise chatflow interactions and retain logs for forensic analysis
• Configure alerts for any shell command execution or Python subprocess creation originating from the Flowise application
• Implement egress filtering to restrict outbound network access from the Flowise server to only necessary destinations
• Regularly review Flowise server access logs for unusual request patterns or high-volume prompt submissions

How to Mitigate CVE-2026-41265

Immediate Actions Required

• Upgrade all Flowise installations to version 3.1.0 or later immediately
• If immediate upgrade is not possible, disable or remove any chatflows utilizing the Airtable Agent node
• Restrict network access to Flowise instances using firewall rules or VPN requirements
• Implement authentication requirements for all chatflow endpoints if not already in place
• Review server logs for evidence of exploitation attempts

Patch Information

The vulnerability is fixed in Flowise version 3.1.0. Users should upgrade to this version or later to remediate the vulnerability. The fix implements proper sandboxing for LLM-generated code execution in the Airtable Agent. Detailed information about the vulnerability and the fix can be found in the GitHub Security Advisory.

Workarounds

• Remove or disable the Airtable Agent node from all production chatflows until patching is complete
• Place Flowise instances behind a reverse proxy with request filtering to block suspicious prompt patterns
• Implement network segmentation to isolate Flowise servers from critical infrastructure
• Deploy web application firewall (WAF) rules to detect and block potential prompt injection attempts
• Restrict Flowise access to trusted internal users only through authentication and IP allowlisting

# Example: Restrict Flowise access via iptables (adjust as needed)
# Only allow access from trusted internal network
iptables -A INPUT -p tcp --dport 3000 -s 10.0.0.0/8 -j ACCEPT
iptables -A INPUT -p tcp --dport 3000 -j DROP