CVE-2022-35918 Streamlit vulnerability – If you work in the machine learning industry, you should consider it.
(1st Aug, 2022)

Preface: On 2017, Facebook’s artificial intelligence robots shut down after they start talking to each other in their own language. Maybe no one remembers!

Background: If you are a data scientist. You know the details of the algorithms, which libraries to use, and perform diagnostics. For the machine learning setup, perhaps you will use a opensource software technology. One of the way is creating an ML app using Flask, a commonly used web framework in Python.
Furthermore, you have another choices. Streamlit is a framework that is used by different machine learning engineers and data scientists to build UIs and powerful machine learning apps from a trained model.

  1. How to install streamlit?
    pip install streamlit
  2. Build the streamlit app
  • Create a new Python file named
  • Add our pickled model into a created folder.
  1. Import required packages.
  2. Unplick the model.
  3. Building your prediction logic.
  4. You will use material UI for styles and icons for your app
  5. Adding an image.

Vulnerability details: Users hosting Streamlit app(s) that use custom components are vulnerable to a directory traversal attack that could leak data from their web server file-system such as: server logs, world readable files, and potentially other sensitive information.
An attacker can craft a malicious URL with file paths and the streamlit server would process that URL and return the contents of that file.

Solution: Vendor strongly recommend users upgrade to v1.11.1 as soon as possible. Please refer to the link for details –

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