How the CVE Works:
The vulnerability (CVE-2025-XXXX) in ZenML version 0.66.0 arises from improper handling of multipart request boundaries. Attackers can exploit this flaw by sending specially crafted multipart requests with malformed boundary strings. When arbitrary characters are appended to the boundary, the server fails to process the request correctly, entering an infinite loop. This causes excessive CPU and memory consumption, leading to a Denial of Service (DoS) condition. The affected endpoints, such as `/api/v1/login` and /api/v1/device_authorization, become unresponsive, rendering the service unavailable to legitimate users. The issue stems from insufficient validation of multipart boundary strings in the request processing logic.
DailyCVE Form:
Platform: ZenML
Version: 0.66.0
Vulnerability: Unauthenticated DoS
Severity: High
Date: Mar 20, 2025
What Undercode Say:
Exploitation:
- Craft a malicious HTTP request with a malformed multipart boundary.
- Use tools like `curl` or Python’s `requests` library to send the payload:
curl -X POST http://<target>/api/v1/login -F "file=@malicious_payload"
- Append arbitrary characters to the boundary, e.g.,
boundary=-WebKitFormBoundaryXYZ123!@.
Protection:
1. Update ZenML to the latest patched version.
- Implement input validation for multipart boundaries in the server-side code.
- Use a Web Application Firewall (WAF) to filter malformed requests.
- Monitor server logs for unusual activity, such as repeated multipart requests.
Code Snippet for Mitigation:
from flask import Flask, request, abort
app = Flask(<strong>name</strong>)
@app.route('/api/v1/login', methods=[bash])
def login():
if 'multipart/form-data' not in request.headers.get('Content-Type', ''):
abort(400, 'Invalid Content-Type')
boundary = request.headers.get('Content-Type').split('boundary=')[bash]
if not boundary.isalnum(): Ensure boundary contains only alphanumeric characters
abort(400, 'Invalid boundary')
Process request
return 'Login successful', 200
Analytics:
- Impact: High, as it affects service availability.
- Exploit Complexity: Low, requiring minimal technical knowledge.
- Attack Vector: Network-based, unauthenticated.
- Affected Systems: ZenML servers running version 0.66.0.
Commands for Detection:
1. Check server logs for repeated multipart requests:
grep -i "multipart" /var/log/zenml/access.log
2. Monitor CPU and memory usage:
top -b -n 1 | grep zenml
References:
References:
Reported By: https://github.com/advisories/GHSA-6gmf-2369-c76c
Extra Source Hub:
Undercode
