Fickling fails to block the 'pty' module, misclassifying unsafe pickles.
Fickling is a Python pickling decompiler and static analyzer. Versions prior to 0.1.6 had a bypass caused by `pty` missing from the block list of unsafe module imports. This led to unsafe pickles based on `pty.spawn()` being incorrectly flagged as `LIKELY_SAFE`, and was fixed in version 0.1.6. This impacted any user or system that used Fickling to vet pickle files for security issues.
Fickling security check bypass allows for arbitrary code execution.
Fickling is a Python pickling decompiler and static analyzer. Versions prior to 0.1.6 are missing `marshal` and `types` from the block list of unsafe module imports. Fickling started blocking both modules to address this issue. This allows an attacker to craft a malicious pickle file that can bypass fickling since it misses detections for `types.FunctionType` and `marshal.loads`. A user who deserializes such a file, believing it to be safe, would inadvertently execute arbitrary code on their system. This impacts any user or system that uses Fickling to vet pickle files for security issues. The issue was fixed in version 0.1.6.
Unsafe deserialization in torch_musa's compare_tool allows for RCE.
MooreThreads torch_musa through all versions contains an unsafe deserialization vulnerability in torch_musa.utils.compare_tool. The compare_for_single_op() and nan_inf_track_for_single_op() functions use pickle.load() on user-controlled file paths without validation, allowing arbitrary code execution. An attacker can craft a malicious pickle file that executes arbitrary Python code when loaded, enabling remote code execution with the privileges of the victim process.
Inefficient parsing of HTTP headers in Tornado allows for a Denial of Service.
Tornado is a Python web framework and asynchronous networking library. Versions 6.5.2 and below use an inefficient algorithm when parsing parameters for HTTP header values, potentially causing a DoS. The _parseparam function in httputil.py is used to parse specific HTTP header values, such as those in multipart/form-data and repeatedly calls string.count() within a nested loop while processing quoted semicolons. If an attacker sends a request with a large number of maliciously crafted parameters in a Content-Disposition header, the server's CPU usage increases quadratically (O(nยฒ)) during parsing. Due to Tornado's single event loop architecture, a single malicious request can cause the entire server to become unresponsive for an extended period. This issue is fixed in version 6.5.3.
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(nยฒ) 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.
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.
The supreme art of war is to subdue the enemy without fighting.
Sun Tzu – “The Art of War”
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