Tornado DoS from repeated HTTP headers blocking the server's event loop.
Tornado is a Python web framework and asynchronous networking library. In versions 6.5.2 and below, a single maliciously crafted HTTP request can block the server's event loop for an extended period, caused by the HTTPHeaders.add method. The function accumulates values using string concatenation when the same header name is repeated, causing a Denial of Service (DoS). Due to Python string immutability, each concatenation copies the entire string, resulting in O(n²) time complexity. The severity can vary from high if max_header_size has been increased from its default, to low if it has its default value of 64KB. This issue is fixed in version 6.5.3.
Tornado: Unescaped reason phrase leads to header injection and XSS.
Tornado is a Python web framework and asynchronous networking library. In versions 6.5.2 and below, the supplied reason phrase is used unescaped in HTTP headers (where it could be used for header injection) or in HTML in the default error page (where it could be used for XSS) and can be exploited by passing untrusted or malicious data into the reason argument. Used by both RequestHandler.set_status and tornado.web.HTTPError, the argument is designed to allow applications to pass custom "reason" phrases (the "Not Found" in HTTP/1.1 404 Not Found) to the HTTP status line (mainly for non-standard status codes). This issue is fixed in version 6.5.3.
mad-proxy <= 0.3 traffic interception bypass exposes sensitive traffic.
mad-proxy is a Python-based HTTP/HTTPS proxy server for detection and blocking of malicious web activity using custom security policies. Versions 0.3 and below allow attackers to bypass HTTP/HTTPS traffic interception rules, potentially exposing sensitive traffic. This issue does not have a fix at the time of publication.
NiceGUI <= 3.3.1 has a directory traversal vulnerability in add_media_files.
NiceGUI is a Python-based UI framework. Versions 3.3.1 and below are vulnerable to directory traversal through the App.add_media_files() function, which allows a remote attacker to read arbitrary files on the server filesystem. This issue is fixed in version 3.4.0.
Authenticated RCE in SOAR server via a malicious custom integration package.
A vulnerability exists in the SecOps SOAR server. The custom integrations feature allowed an authenticated user with an "IDE role" to achieve Remote Code Execution (RCE) in the server. The flaw stemmed from weak validation of uploaded Python package code. An attacker could upload a package containing a malicious setup.py file, which would execute on the server during the installation process, leading to potential server compromise. No customer action is required. All customers have been automatically upgraded to the fixed version: 6.3.64 or higher.
XSS in NiceGUI's ui.interactive_image via unsanitized SVG rendering.
NiceGUI is a Python-based UI framework. Versions 3.3.1 and below are subject to a XSS vulnerability through the ui.interactive_image component of NiceGUI. The component renders SVG content using Vue's v-html directive without any sanitization. This allows attackers to inject malicious HTML or JavaScript via the SVG <foreignObject> tag whenever the image component is rendered or updated. This is particularly dangerous for dashboards or multi-user applications displaying user-generated content or annotations. This issue is fixed in version 3.4.0.
Reflected XSS in NiceGUI's CSS functions allows arbitrary JS execution.
NiceGUI is a Python-based UI framework. Versions 3.3.1 and below are vulnerable to Reflected XSS through its ui.add_css, ui.add_scss, and ui.add_sass functions. The functions lack proper sanitization or encoding for the JavaScript context they generate. An attacker can break out of the intended <style> or <script> tags by injecting closing tags (e.g., </style> or </script>), allowing for the execution of arbitrary JavaScript. This issue is fixed in version 3.4.0.
Unauthenticated disclosure of sensitive info in ReQuest F3 Server debug log.
ReQuest Serious Play F3 Media Server versions 7.0.3.4968 (Pro), 7.0.2.4954, 6.5.2.4954, 6.4.2.4681, 6.3.2.4203, and 2.0.1.823 allows unauthenticated attackers to disclose the webserver's Python debug log file containing system information, credentials, paths, processes and command arguments running on the device. Attackers can access sensitive information by visiting the message_log page.
urllib3 vulnerable to a decompression bomb DoS via its streaming API.
urllib3 is a user-friendly HTTP client library for Python. Starting in version 1.0 and prior to 2.6.0, the Streaming API improperly handles highly compressed data. urllib3's streaming API is designed for the efficient handling of large HTTP responses by reading the content in chunks, rather than loading the entire response body into memory at once. When streaming a compressed response, urllib3 can perform decoding or decompression based on the HTTP Content-Encoding header (e.g., gzip, deflate, br, or zstd). The library must read compressed data from the network and decompress it until the requested chunk size is met. Any resulting decompressed data that exceeds the requested amount is held in an internal buffer for the next read operation. The decompression logic could cause urllib3 to fully decode a small amount of highly compressed data in a single operation. This can result in excessive resource consumption (high CPU usage and massive memory allocation for the decompressed data.
Denial of Service in urllib3 due to an unbounded decompression chain.
urllib3 is a user-friendly HTTP client library for Python. Starting in version 1.24 and prior to 2.6.0, the number of links in the decompression chain was unbounded allowing a malicious server to insert a virtually unlimited number of compression steps leading to high CPU usage and massive memory allocation for the decompressed data. This vulnerability is fixed in 2.6.0.
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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Sun Tzu – “The Art of War”
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