CVE-2022-24770 in gradio
Summary
by MITRE • 03/18/2022
`gradio` is an open source framework for building interactive machine learning models and demos. Prior to version 2.8.11, `gradio` suffers from Improper Neutralization of Formula Elements in a CSV File. The `gradio` library has a flagging functionality which saves input/output data into a CSV file on the developer's computer. This can allow a user to save arbitrary text into the CSV file, such as commands. If a program like MS Excel opens such a file, then it automatically runs these commands, which could lead to arbitrary commands running on the user's computer. The problem has been patched as of `2.8.11`, which escapes the saved csv with single quotes. As a workaround, avoid opening csv files generated by `gradio` with Excel or similar spreadsheet programs.
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Analysis
by VulDB Data Team • 03/20/2022
The vulnerability identified as CVE-2022-24770 affects the gradio framework, an open-source tool designed for creating interactive machine learning models and demonstrations. This security flaw resides in the flagging functionality of gradio, which serves as a mechanism for developers to collect and store input/output data from user interactions. The vulnerability specifically manifests in how the framework handles CSV file generation when saving flagged data, creating a potential vector for command injection attacks. The issue impacts versions prior to 2.8.11, making it a significant concern for users who have not updated their installations.
The technical root cause of this vulnerability stems from improper neutralization of formula elements within CSV files. When gradio's flagging feature saves data to CSV format, it fails to properly escape or sanitize special characters that could be interpreted as spreadsheet commands. This flaw aligns with CWE-15, which addresses improper neutralization of special elements used in resource identifiers. The vulnerability occurs because the framework does not adequately process or escape characters that might trigger automatic execution within spreadsheet applications, particularly Microsoft Excel. When users open the generated CSV files with such programs, the spreadsheet software automatically interprets certain text patterns as formulas, leading to unintended command execution on the user's system.
The operational impact of this vulnerability extends beyond simple data manipulation, presenting a serious security risk to developers and end-users who rely on gradio for machine learning demonstrations. Attackers could craft malicious input data containing spreadsheet formulas that execute arbitrary commands when the CSV file is opened in Excel or similar applications. This creates a vector for privilege escalation and potential system compromise, as the commands would execute with the privileges of the user who opens the file. The vulnerability particularly affects environments where developers frequently use gradio's flagging feature and where the generated CSV files might be shared or opened by multiple users. The risk is compounded by the fact that spreadsheet applications automatically process these formulas without user intervention, making the attack largely invisible to the end user.
The fix implemented in gradio version 2.8.11 addresses this vulnerability by introducing proper CSV escaping mechanisms that wrap saved content in single quotes, preventing the interpretation of special characters as spreadsheet commands. This solution directly mitigates the command injection risk by ensuring that any potentially malicious content is treated as literal text rather than executable formulas. Security practitioners should ensure all gradio installations are updated to version 2.8.11 or later to protect against this vulnerability. Organizations using gradio should also implement additional safeguards such as restricting access to flagged data files and educating users about the risks of opening unknown CSV files in spreadsheet applications. The workaround of avoiding Excel or similar programs when opening gradio-generated CSV files remains a valid temporary measure until full patch adoption occurs. This vulnerability demonstrates the importance of proper input sanitization in file generation processes and highlights how seemingly benign features can create significant security risks when not properly secured against formula injection attacks.