Type confusion in TensorFlow, leads to null pointer dereference, fixed in TensorFlow 2.5.0 with backports
TensorFlow is an end-to-end open source platform for machine learning. Calling TF operations with tensors of non-numeric types when the operations expect numeric tensors result in null pointer dereferences. The conversion from Python array to C++ array(https://github.com/tensorflow/tensorflow/blob/ff70c47a396ef1e3cb73c90513da4f5cb71bebba/tensorflow/python/lib/core/ndarray_tensor.cc#L113-L169) is vulnerable to a type confusion. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
TensorFlow < 2.2.1 and 2.3.1: Uninitialized memory corruption in dlpack.to_dlpack due to Python object mishandling
In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of `dlpack.to_dlpack` can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users from passing in a Python object instead of a tensor. The uninitialized memory address is due to a `reinterpret_cast` Since the `PyObject` is a Python object, not a TensorFlow Tensor, the cast to `EagerTensor` fails. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1.
Cobbler before 3.3.1 allows Python module imports via "#from MODULE import" in templar.py, posing a security risk
An issue was discovered in Cobbler before 3.3.1. In the templar.py file, the function check_for_invalid_imports can allow Cheetah code to import Python modules via the "#from MODULE import" substring. (Only lines beginning with #import are blocked.)
Cloudflare-scrape 1.6.6 to 1.7.1 allows malicious sites to execute Python code on user's scrapers
An issue was discovered in cloudflare-scrape 1.6.6 through 1.7.1. A malicious website owner could craft a page that executes arbitrary Python code against any cfscrape user who scrapes that website. This is fixed in 1.8.0.
Python-gnupg 0.3.5 and 0.3.6 allow unspecified impact via option injection in positional arguments
python-gnupg 0.3.5 and 0.3.6 allows context-dependent attackers to have an unspecified impact via vectors related to "option injection through positional arguments." NOTE: this vulnerability exists because of an incomplete fix for CVE-2013-7323.
OpenStack Swift < 1.7.0: Remote code execution via crafted pickle metadata in memcached
OpenStack Object Storage (swift) before 1.7.0 uses the loads function in the pickle Python module unsafely when storing and loading metadata in memcached, which allows remote attackers to execute arbitrary code via a crafted pickle object.
Remote code execution in Plone 2.5.0 - 2.5.4 and 3.0.0 - 3.0.2 via pickled objects in network data
Plone 2.5 through 2.5.4 and 3.0 through 3.0.2 allows remote attackers to execute arbitrary Python code via network data containing pickled objects for the (1) statusmessages or (2) linkintegrity module, which the module unpickles and executes.
Karrigell < 2.1.8 has remote code execution via eval injection in manipulated script arguments
Eval injection vulnerability in Karrigell before 2.1.8 allows remote attackers to execute arbitrary Python code via modified arguments to a Karrigell services (.ks) script, which can reference functions from libraries that are used by that script.
Local privilege escalation in Intel Python < 2022.1 due to uncontrolled search path element
Uncontrolled search path element in the Intel(R) Distribution for Python programming language before version 2022.1 for Intel(R) oneAPI Toolkits may allow an authenticated user to potentially enable escalation of privilege via local access.
Calibre 3.18: Remote code execution via crafted .pickle file
gui2/viewer/bookmarkmanager.py in Calibre 3.18 calls cPickle.load on imported bookmark data, which allows remote attackers to execute arbitrary code via a crafted .pickle file, as demonstrated by Python code that contains an os.system call.
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 ::