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CVE-2023-6572

Sensitive information exposure in gradio-app/gradio GitHub repository prior to main branch

  • CVSS 8.1
  • CWE-77 Improper Neutralization of Special Elements used in a Command ('Command Injection')
  • Information Leakage
  • Remote

Exposure of Sensitive Information to an Unauthorized Actor in GitHub repository gradio-app/gradio prior to main.

CVSS base score
8.1
Published
2023-12-14
OWASP
A07 Identification and Authentication Failures
Orthogonal defect classification
Function
Code defect classification
Extraneous Functionality
Category
Information Leakage
Subcategory
Insecure Handling of Sensitive Data
Accessibility scope
Remote
Impact
Information Disclosure
Fixed by upgrading
Yes

Solution

Update Gradio to version 2023-11-06 or later

Vulnerable code sample

from flask import Flask, jsonify

app = Flask(__name__)

@app.route('/sensitive-data', methods=['GET'])
def get_sensitive_data():
    sensitive_data = {"secret": "This is sensitive information"}
    return jsonify(sensitive_data)

if __name__ == '__main__':
    app.run()

Patched code sample

import os
from flask import Flask, request, jsonify

app = Flask(__name__)

ACCESS_TOKEN = os.getenv("ACCESS_TOKEN")

@app.route('/sensitive-data', methods=['GET'])
def get_sensitive_data():
    token = request.headers.get('Authorization')

    if token != f"Bearer {ACCESS_TOKEN}":
        return jsonify({"error": "Unauthorized access"}), 403

    sensitive_data = {"secret": "This is sensitive information"}
    return jsonify(sensitive_data)

if __name__ == '__main__':
    app.run()

Cite this entry

@misc{vaitp:cve20236572,
  title        = {{Sensitive information exposure in gradio-app/gradio GitHub repository prior to main branch}},
  author       = {Bogaerts, Fr\'ed\'eric and Ivaki, Naghmeh and Fonseca, Jos\'e},
  year         = {2023},
  note         = {VAITP Python Vulnerability Dataset, entry CVE-2023-6572},
  howpublished = {\url{https://netpack.pt/vaitp/vulnerability/CVE-2023-6572/}}
}
Introducing the "VAITP dataset": a specialized repository of Python vulnerabilities and patches, meticulously compiled for the use of the security research community. As Python's prominence grows, understanding and addressing potential security vulnerabilities become crucial. Crafted by and for the cybersecurity community, this dataset offers a valuable resource for researchers, analysts, and developers to analyze and mitigate the security risks associated with Python. Through the comprehensive exploration of vulnerabilities and corresponding patches, the VAITP dataset fosters a safer and more resilient Python ecosystem, encouraging collaborative advancements in programming security.

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