VAITP Dataset

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CVE
Vulnerability
ODC
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Details
Total vulnerabilities in the dataset (not showing ignored and non-python related vulnerabilties): 1438
771
CVE-2023-29214
XWiki Commons code execution via improper escaping

XWiki Commons are technical libraries common to several other top level XWiki projects. Any user with edit rights can execute arbitrary Groovy, Python or Velocity code in XWiki leading to full access to the XWiki installation. The root cause is improper escaping of the included pages in the IncludedDocuments panel. The problem has been patched on XWiki 14.4.7, and 14.10.

Function
Input Validation and Sanitization
Insecure Parsing or Deserialization
Remote
770
CVE-2023-29212
Code execution via unescaped included pages in XWiki Commons

XWiki Commons are technical libraries common to several other top level XWiki projects. Any user with edit rights can execute arbitrary Groovy, Python or Velocity code in XWiki leading to full access to the XWiki installation. The root cause is improper escaping of the included pages in the included documents edit panel. The problem has been patched on XWiki 14.4.7, and 14.10.

Function
Input Validation and Sanitization
Insecure Parsing or Deserialization
Remote
769
CVE-2022-36040
Rizin 0.4.0 and prior, UNIX-like, PYC file, out-of-bounds write

Rizin is a UNIX-like reverse engineering framework and command-line toolset. Versions 0.4.0 and prior are vulnerable to an out-of-bounds write when getting data from PYC(python) files. A user opening a malicious PYC file could be affected by this vulnerability, allowing an attacker to execute code on the user's machine. Commit number 68948017423a12786704e54227b8b2f918c2fd27 contains a patch.

Function
Memory Corruption
Out-of-Bound Accesses
Local
768
CVE-2021-28957
XSS vulnerability in python-lxml (before 4.6.3) clean module

An XSS vulnerability was discovered in python-lxml's clean module versions before 4.6.3. When disabling the safe_attrs_only and forms arguments, the Cleaner class does not remove the formaction attribute allowing for JS to bypass the sanitizer. A remote attacker could exploit this flaw to run arbitrary JS code on users who interact with incorrectly sanitized HTML. This issue is patched in lxml 4.6.3.

Function
Input Validation and Sanitization
Insecure Parsing or Deserialization
Remote
767
CVE-2016-9950
Path traversal in Apport <= 2.20.4 allows Python file execution

An issue was discovered in Apport before 2.20.4. There is a path traversal issue in the Apport crash file "Package" and "SourcePackage" fields. These fields are used to build a path to the package specific hook files in the /usr/share/apport/package-hooks/ directory. An attacker can exploit this path traversal to execute arbitrary Python files from the local system.

Function
Input Validation and Sanitization
Path Traversal
Local
766
CVE-2008-3294
Vim 5.0-7.1, Python build: Insecure Makefile-conf ownership and permissions allow code execution by local users

src/configure.in in Vim 5.0 through 7.1, when used for a build with Python support, does not ensure that the Makefile-conf temporary file has the intended ownership and permissions, which allows local users to execute arbitrary code by modifying this file during a time window, or by creating it ahead of time with permissions that prevent its modification by configure.

Timing/Serialization
Authentication, Authorization, and Session Management
Privilege Escalation
Local
765
CVE-2018-16858
LibreOffice < 6.0.7 and 6.1.3: Directory Traversal, Execute Arbitrary Macros

It was found that libreoffice before versions 6.0.7 and 6.1.3 was vulnerable to a directory traversal attack which could be used to execute arbitrary macros bundled with a document. An attacker could craft a document, which when opened by LibreOffice, would execute a Python method from a script in any arbitrary file system location, specified relative to the LibreOffice install location.

Function
Input Validation and Sanitization
Path Traversal
Local
764
CVE-2013-1443
Django 1.4.x to 1.6.x auth framework CPU DoS via long password

The authentication framework (django.contrib.auth) in Django 1.4.x before 1.4.8, 1.5.x before 1.5.4, and 1.6.x before 1.6 beta 4 allows remote attackers to cause a denial of service (CPU consumption) via a long password which is then hashed.

Function
Resource Management
Resource Exhaustion
Remote
763
CVE-2020-22083
jsonpickle 1.4.1 RCE in decode

** DISPUTED ** jsonpickle through 1.4.1 allows remote code execution during deserialization of a malicious payload through the decode() function. Note: It has been argued that this is expected and clearly documented behaviour. pickle is known to be capable of causing arbitrary code execution, and must not be used with un-trusted data.

Function
Input Validation and Sanitization
Insecure Parsing or Deserialization
Remote
762
CVE-2019-15790
Apport PID recycling exploit

Apport reads and writes information on a crashed process to /proc/pid with elevated privileges. Apport then determines which user the crashed process belongs to by reading /proc/pid through get_pid_info() in data/apport. An unprivileged user could exploit this to read information about a privileged running process by exploiting PID recycling. This information could then be used to obtain ASLR offsets for a process with an existing memory corruption vulnerability. The initial fix introduced regressions in the Python Apport library due to a missing argument in Report.add_proc_environ in apport/report.py. It also caused an autopkgtest failure when reading /proc/pid and with Python 2 compatibility by reading /proc maps. The initial and subsequent regression fixes are in 2.20.11-0ubuntu16, 2.20.11-0ubuntu8.6, 2.20.9-0ubuntu7.12, 2.20.1-0ubuntu2.22 and 2.14.1-0ubuntu3.29+esm3.

Function
Authentication, Authorization, and Session Management
Privilege Escalation
Local
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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