Roundup 1.6 XSS via URI in frontends/roundup.cgi and roundup/cgi/wsgi_handler.py mishandling 404 errors
Roundup 1.6 allows XSS via the URI because frontends/roundup.cgi and roundup/cgi/wsgi_handler.py mishandle 404 errors.
Frappe HTML Injection in desk
Frappe is a full-stack web application framework that uses Python and MariaDB on the server side and an integrated client side library. A malicious Frappe user with desk access could create documents containing HTML payloads allowing HTML Injection. This vulnerability has been patched in version 14.49.0.
CALDERA 2.8.1 Human plugin allows shell command injection via unsanitized "name" parameter
An issue was discovered in CALDERA 2.8.1. When activated, the Human plugin passes the unsanitized name parameter to a python "os.system" function. This allows attackers to use shell metacharacters (e.g., backticks "``" or dollar parenthesis "$()" ) in order to escape the current command and execute arbitrary shell commands.
Unspecified Zope 2.12.x and 2.13.x vulnerability allows remote command execution via OFS/misc_.py and Python modules
Unspecified vulnerability in Zope 2.12.x and 2.13.x, as used in Plone 4.0.x through 4.0.9, 4.1, and 4.2 through 4.2a2, allows remote attackers to execute arbitrary commands via vectors related to the p_ class in OFS/misc_.py and the use of Python modules.
Mako before 0.3.4: XSS via cgi.escape
Mako before 0.3.4 relies on the cgi.escape function in the Python standard library for cross-site scripting (XSS) protection, which makes it easier for remote attackers to conduct XSS attacks via vectors involving single-quote characters and a JavaScript onLoad event handler for a BODY element.
Default root password in Ubuntu VMs: "!
Ubuntu 6.06 LTS, 7.10, 8.04 LTS, and 8.10, when installed as a virtual machine by (1) python-vm-builder or (2) ubuntu-vm-builder in VMBuilder 0.9 in Ubuntu 8.10, have ! (exclamation point) as the default root password, which allows attackers to bypass intended login restrictions.
Spark 2.3.3 Pre-Encryption Data Leakage
Prior to Spark 2.3.3, in certain situations Spark would write user data to local disk unencrypted, even if spark.io.encryption.enabled=true. This includes cached blocks that are fetched to disk (controlled by spark.maxRemoteBlockSizeFetchToMem); in SparkR, using parallelize; in Pyspark, using broadcast and parallelize; and use of python udfs.
Email domain-based registration restrictions bypass in Matrix Sydent < 1.0.2
util/emailutils.py in Matrix Sydent before 1.0.2 mishandles registration restrictions that are based on e-mail domain, if the allowed_local_3pids option is enabled. This occurs because of potentially unwanted behavior in Python, in which an email.utils.parseaddr call on user@bad.example.net@good.example.com returns the user@bad.example.net substring.
Information disclosure in python-oslo-middleware <3.8.1, 3.19.1, 3.23.1
python-oslo-middleware before versions 3.8.1, 3.19.1, 3.23.1 is vulnerable to an information disclosure. Software using the CatchError class could include sensitive values in a traceback's error message. System users could exploit this flaw to obtain sensitive information from OpenStack component error logs (for example, keystone tokens).
TensorFlow tf.function deadlock vulnerability due to mutual recursion
TensorFlow is an open source platform for machine learning. In affected versions the code behind `tf.function` API can be made to deadlock when two `tf.function` decorated Python functions are mutually recursive. This occurs due to using a non-reentrant `Lock` Python object. Loading any model which contains mutually recursive functions is vulnerable. An attacker can cause denial of service by causing users to load such models and calling a recursive `tf.function`, although this is not a frequent scenario. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
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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