Python Charmers Future 0.18.2 and earlier: Remote attacker causes denial of service via malicious Set-Cookie header
The verify function in the Stark Bank Python ECDSA library (aka starkbank-escada or ecdsa-python) before 2.0.1 fails to check that the signature is non-zero, which allows attackers to forge signatures on arbitrary messages.
Stark Bank Python ECDSA <2.0.1 allows signature forgery by not checking non-zero signatures
The d8s-python for python, as distributed on PyPI, included a potential code-execution backdoor inserted by a third party. A potential code execution backdoor inserted by third parties is the democritus-grammars package. The affected version of d8s-htm is 0.1.0.
PyPI d8s-python package v0.1.0 had a backdoor via democritus-grammars
The d8s-python for python, as distributed on PyPI, included a potential code-execution backdoor inserted by a third party. A potential code execution backdoor inserted by third parties is the democritus-algorithms package. The affected version of d8s-htm is 0.1.0.
Openapi-python-client < 0.5.3 allows malicious files anywhere on disk
In openapi-python-client before version 0.5.3, there is a path traversal vulnerability. If a user generated a client using a maliciously crafted OpenAPI document, it is possible for generated files to be placed in arbitrary locations on disk.
PyPI package 'd8s-python' version 0.1.0 contains a code-execution backdoor via 'democritus-algorithms'
The d8s-python for python, as distributed on PyPI, included a potential code-execution backdoor inserted by a third party. The democritus-strings package. The affected version is 0.1.0.
Malicious OpenAPI Document in openapi-python-client < 0.5.3 allows arbitrary Python code execution
In openapi-python-client before version 0.5.3, clients generated with a maliciously crafted OpenAPI Document can generate arbitrary Python code. Subsequent execution of this malicious client is arbitrary code execution.
Remote code execution via SimpleXMLRPCServer
The SimpleXMLRPCServer library module in Python 2.2, 2.3 before 2.3.5, and 2.4, when used by XML-RPC servers that use the register_instance method to register an object without a _dispatch method, allows remote attackers to read or modify globals of the associated module, and possibly execute arbitrary code, via dotted attributes.
Stack-based buffer overflow in Python < 2.4.2
Stack-based buffer overflow in Python 2.4.2 and earlier, running on Linux 2.6.12.5 under gcc 4.0.3 with libc 2.3.5, allows local users to cause a "stack overflow," and possibly gain privileges, by running a script from a current working directory that has a long name, related to the realpath function. NOTE: this might not be a vulnerability. However, the fact that it appears in a programming language interpreter could mean that some applications are affected, although attack scenarios might be limited because the attacker might already need to cross privilege boundaries to cause an exploitable program to be placed in a directory with a long name; or, depending on the method that Python uses to determine the current working directory, setuid applications might be affected.
Directory traversal vulnerability in the (1) extract and (2) extractall functions in the tarfile module in Python
Directory traversal vulnerability in the (1) extract and (2) extractall functions in the tarfile module in Python allows user-assisted remote attackers to overwrite arbitrary files via a .. (dot dot) sequence in filenames in a TAR archive, a related issue to CVE-2001-1267.
Multiple integer overflows in the imageop module in Python 2.5.1 and earlier
Multiple integer overflows in the imageop module in Python 2.5.1 and earlier allow context-dependent attackers to cause a denial of service (application crash) and possibly obtain sensitive information (memory contents) via crafted arguments to (1) the tovideo method, and unspecified other vectors related to (2) imageop.c, (3) rbgimgmodule.c, and other files, which trigger heap-based buffer overflows.
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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