A flaw was found in python. An improperly handled HTTP response in the HTTP client code of python may allow a remote attacker, who controls the HTTP server, to make the client script enter an infinite loop, consuming CPU time. The highest threat from this vulnerability is to system availability.

Twisted is an event-based framework for internet applications, supporting Python 3.6+. Prior to 22.2.0, Twisted SSH client and server implement is able to accept an infinite amount of data for the peer's SSH version identifier. This ends up with a buffer using all the available memory. The attach is a simple as `nc -rv localhost 22 < /dev/zero`. A patch is available in version 22.2.0. There are currently no known workarounds.

b2-sdk-python is a python library to access cloud storage provided by backblaze. Linux and Mac releases of the SDK version 1.14.0 and below contain a key disclosure vulnerability that, in certain conditions, can be exploited by local attackers through a time-of-check-time-of-use (TOCTOU) race condition. SDK users of the SqliteAccountInfo format are vulnerable while users of the InMemoryAccountInfo format are safe. The SqliteAccountInfo saves API keys (and bucket name-to-id mapping) in a local database file ($XDG_CONFIG_HOME/b2/account_info, ~/.b2_account_info or a user-defined path). When first created, the file is world readable and is (typically a few milliseconds) later altered to be private to the user. If the directory containing the file is readable by a local attacker then during the brief period between file creation and permission modification, a local attacker can race to open the file and maintain a handle to it. This allows the local attacker to read the contents after the file after the sensitive information has been saved to it. Consumers of this SDK who rely on it to save data using SqliteAccountInfo class should upgrade to the latest version of the SDK. Those who believe a local user might have opened a handle using this race condition, should remove the affected database files and regenerate all application keys. Users should upgrade to b2-sdk-python 1.14.1 or later.

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.)

A flaw was found in Python, specifically within the urllib.parse module. This module helps break Uniform Resource Locator (URL) strings into components. The issue involves how the urlparse method does not sanitize input and allows characters like '\r' and '\n' in the URL path. This flaw allows an attacker to input a crafted URL, leading to injection attacks. This flaw affects Python versions prior to 3.10.0b1, 3.9.5, 3.8.11, 3.7.11 and 3.6.14.

twisted is an event-driven networking engine written in Python. In affected versions twisted exposes cookies and authorization headers when following cross-origin redirects. This issue is present in the `twited.web.RedirectAgent` and `twisted.web. BrowserLikeRedirectAgent` functions. Users are advised to upgrade. There are no known workarounds.

Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow (MLIR) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered.

Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that assertions in `function.cc` would be falsified and crash the Python interpreter. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ReverseSequence` does not fully validate the value of `batch_dim` and can result in a heap OOB read. There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of `Dim` would access elements before the start of an array. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Authenticated remote code execution in MotionEye <= 0.42.1 and MotioneEyeOS <= 20200606 allows a remote attacker to upload a configuration backup file containing a malicious python pickle file which will execute arbitrary code on the server.

Products.ATContentTypes are the core content types for Plone 2.1 - 4.3. Versions of Plone that are dependent on Products.ATContentTypes prior to version 3.0.6 are vulnerable to reflected cross site scripting and open redirect when an attacker can get a compromised version of the image_view_fullscreen page in a cache, for example in Varnish. The technique is known as cache poisoning. Any later visitor can get redirected when clicking on a link on this page. Usually only anonymous users are affected, but this depends on the user's cache settings. Version 3.0.6 of Products.ATContentTypes has been released with a fix. This version works on Plone 5.2, Python 2 only. As a workaround, make sure the image_view_fullscreen page is not stored in the cache. More information about the vulnerability and cvmitigation measures is available in the GitHub Security Advisory.

IPython (Interactive Python) is a command shell for interactive computing in multiple programming languages, originally developed for the Python programming language. Affected versions are subject to an arbitrary code execution vulnerability achieved by not properly managing cross user temporary files. This vulnerability allows one user to run code as another on the same machine. All users are advised to upgrade.

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.

pipenv is a Python development workflow tool. Starting with version 2018.10.9 and prior to version 2022.1.8, a flaw in pipenv's parsing of requirements files allows an attacker to insert a specially crafted string inside a comment anywhere within a requirements.txt file, which will cause victims who use pipenv to install the requirements file to download dependencies from a package index server controlled by the attacker. By embedding malicious code in packages served from their malicious index server, the attacker can trigger arbitrary remote code execution (RCE) on the victims' systems. If an attacker is able to hide a malicious `--index-url` option in a requirements file that a victim installs with pipenv, the attacker can embed arbitrary malicious code in packages served from their malicious index server that will be executed on the victim's host during installation (remote code execution/RCE). When pip installs from a source distribution, any code in the setup.py is executed by the install process. This issue is patched in version 2022.1.8. The GitHub Security Advisory contains more information about this vulnerability.

The dnslib package through 0.9.16 for Python does not verify that the ID value in a DNS reply matches an ID value in a query.

PIL.ImageMath.eval in Pillow before 9.0.0 allows evaluation of arbitrary expressions, such as ones that use the Python exec method. A lambda expression could also be used.

NLTK (Natural Language Toolkit) is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. Versions prior to 3.6.5 are vulnerable to regular expression denial of service (ReDoS) attacks. The vulnerability is present in PunktSentenceTokenizer, sent_tokenize and word_tokenize. Any users of this class, or these two functions, are vulnerable to the ReDoS attack. In short, a specifically crafted long input to any of these vulnerable functions will cause them to take a significant amount of execution time. If your program relies on any of the vulnerable functions for tokenizing unpredictable user input, then we would strongly recommend upgrading to a version of NLTK without the vulnerability. For users unable to upgrade the execution time can be bounded by limiting the maximum length of an input to any of the vulnerable functions. Our recommendation is to implement such a limit.

A Buffer Overflow vulnerability exists in NumPy 1.9.x in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulneraility; In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user

vault-cli is a configurable command-line interface tool (and python library) to interact with Hashicorp Vault. In versions before 3.0.0 vault-cli features the ability for rendering templated values. When a secret starts with the prefix `!template!`, vault-cli interprets the rest of the contents of the secret as a Jinja2 template. Jinja2 is a powerful templating engine and is not designed to safely render arbitrary templates. An attacker controlling a jinja2 template rendered on a machine can trigger arbitrary code, making this a Remote Code Execution (RCE) risk. If the content of the vault can be completely trusted, then this is not a problem. Otherwise, if your threat model includes cases where an attacker can manipulate a secret value read from the vault using vault-cli, then this vulnerability may impact you. In 3.0.0, the code related to interpreting vault templated secrets has been removed entirely. Users are advised to upgrade as soon as possible. For users unable to upgrade a workaround does exist. Using the environment variable `VAULT_CLI_RENDER=false` or the flag `--no-render` (placed between `vault-cli` and the subcommand, e.g. `vault-cli --no-render get-all`) or adding `render: false` to the vault-cli configuration yaml file disables rendering and removes the vulnerability. Using the python library, you can use: `vault_cli.get_client(render=False)` when creating your client to get a client that will not render templated secrets and thus operates securely.

Rapid7 Insight Agent, versions 3.0.1 to 3.1.2.34, suffer from a local privilege escalation due to an uncontrolled DLL search path. Specifically, when Insight Agent versions 3.0.1 to 3.1.2.34 start, the Python interpreter attempts to load python3.dll at "C:\DLLs\python3.dll," which normally is writable by locally authenticated users. Because of this, a malicious local user could use Insight Agent's startup conditions to elevate to SYSTEM privileges. This issue was fixed in Rapid7 Insight Agent 3.1.2.35. This vulnerability is a regression of CVE-2019-5629.