VAITP Dataset

Dataset Statistics
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CVE
Vulnerability
ODC
Category
Subcategory
Accessibility Scope
Details
Total vulnerabilities in the dataset (not showing ignored and non-python related vulnerabilties): 1890
591
IBM SPSS Statistics 22.0.0.2 and 23.0.0.2 have weak permissions, enabling local users to gain privileges via Python script modification

IBM SPSS Statistics 22.0.0.2 before IF10 and 23.0.0.2 before IF7 uses weak permissions (Everyone: Write) for Python scripts, which allows local users to gain privileges by modifying a script.

Function
Authentication, Authorization, and Session Management
Privilege Escalation
Local
590
Blender versions 2.34, 2.35a, 2.40, and 2.49b: Remote code execution via malicious Python in .blend files' onLoad action of ScriptLink SDNA

Blender 2.34, 2.35a, 2.40, and 2.49b allows remote attackers to execute arbitrary code via a .blend file that contains Python statements in the onLoad action of a ScriptLink SDNA.

Function
Input Validation and Sanitization
Insecure Parsing or Deserialization
Remote
589
Spyce 2.1.3 info disclosure via error message

Spyce - Python Server Pages (PSP) 2.1.3 allows remote attackers to obtain sensitive information via a direct request for spyce/examples/automaton.spy, which reveals the path in an error message.

Checking
Information Leakage
Information Disclosure
Remote
588
SABnzbd 2.3.9 and 3.0.0Alpha2 have a command injection vulnerability, allowing authenticated users to run arbitrary Python commands on the OS

SABnzbd 2.3.9 and 3.0.0Alpha2 has a command injection vulnerability in the web configuration interface that permits an authenticated user to execute arbitrary Python commands on the underlying operating system.

Function
Input Validation and Sanitization
Command Injection
Remote
587
Local users can execute Python code via shell access in vulnerable Junos OS versions before specified releases

Juniper Junos OS 13.2 before 13.2R5, 13.2X51, 13.2X52, and 13.3 before 13.3R3 allow local users to bypass intended restrictions and execute arbitrary Python code via vectors involving shell access.

Function
Input Validation and Sanitization
Command Injection
Local
586
ReportLab (up to v3.5.26) RCE via crafted XML color attribute

ReportLab through 3.5.26 allows remote code execution because of toColor(eval(arg)) in colors.py, as demonstrated by a crafted XML document with '<span color="' followed by arbitrary Python code.

Function
Input Validation and Sanitization
Command Injection
Remote
585
Remote code execution in Mercurial (before 4.1.3) via "hg serve --stdio" with "--debugger" repository name

In Mercurial before 4.1.3, "hg serve --stdio" allows remote authenticated users to launch the Python debugger, and consequently execute arbitrary code, by using --debugger as a repository name.

Function
Input Validation and Sanitization
Command Injection
Remote
584
Impact: Remote application crash

feedparser.py in Universal Feed Parser (aka feedparser or python-feedparser) before 5.0.1 allows remote attackers to cause a denial of service (application crash) via a malformed DOCTYPE declaration.

Function
Input Validation and Sanitization
Insecure Parsing or Deserialization
Remote
583
PyGreSQL 3.8.1 and 4.0 for Python have a security flaw with PQescapeStringConn, allowing remote attacks with multibyte encoding issues

The pygresql module 3.8.1 and 4.0 for Python does not properly support the PQescapeStringConn function, which might allow remote attackers to leverage escaping issues involving multibyte character encodings.

Function
Input Validation and Sanitization
Insecure Parsing or Deserialization
Remote
582
Buffer overflow in Python 2.5 minigzip allows arbitrary code execution via long file argument

Stack-based buffer overflow in the file_compress function in minigzip (Modules/zlib) in Python 2.5 allows context-dependent attackers to execute arbitrary code via a long file argument.

Function
Memory Corruption
Buffer Overflows
Remote
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”

:: Shaping the future through research and ingenuity ::