Plone through 5.2.4 allows remote authenticated managers to perform disk I/O via crafted keyword arguments to the ReStructuredText transform in a Python script.

Zope is an open-source web application server. In Zope versions prior to 4.6 and 5.2, users can access untrusted modules indirectly through Python modules that are available for direct use. By default, only users with the Manager role can add or edit Zope Page Templates through the web, but sites that allow untrusted users to add/edit Zope Page Templates through the web are at risk from this vulnerability. The problem has been fixed in Zope 5.2 and 4.6. As a workaround, a site administrator can restrict adding/editing Zope Page Templates through the web using the standard Zope user/role permission mechanisms. Untrusted users should not be assigned the Zope Manager role and adding/editing Zope Page Templates through the web should be restricted to trusted users only.

There's a flaw in Python 3's pydoc. A local or adjacent attacker who discovers or is able to convince another local or adjacent user to start a pydoc server could access the server and use it to disclose sensitive information belonging to the other user that they would not normally be able to access. The highest risk of this flaw is to data confidentiality. This flaw affects Python versions before 3.8.9, Python versions before 3.9.3 and Python versions before 3.10.0a7.

The Python "Flask-Security-Too" package is used for adding security features to your Flask application. It is an is an independently maintained version of Flask-Security based on the 3.0.0 version of Flask-Security. All versions of Flask-Security-Too allow redirects after many successful views (e.g. /login) by honoring the ?next query param. There is code in FS to validate that the url specified in the next parameter is either relative OR has the same netloc (network location) as the requesting URL. This check utilizes Pythons urlsplit library. However many browsers are very lenient on the kind of URL they accept and 'fill in the blanks' when presented with a possibly incomplete URL. As a concrete example - setting http://login?next=\\\github.com will pass FS's relative URL check however many browsers will gladly convert this to http://github.com. Thus an attacker could send such a link to an unwitting user, using a legitimate site and have it redirect to whatever site they want. This is considered a low severity due to the fact that if Werkzeug is used (which is very common with Flask applications) as the WSGI layer, it by default ALWAYS ensures that the Location header is absolute - thus making this attack vector mute. It is possible for application writers to modify this default behavior by setting the 'autocorrect_location_header=False`.

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.io.decode_raw` produces incorrect results and crashes the Python interpreter when combining `fixed_length` and wider datatypes. The implementation of the padded version(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc) is buggy due to a confusion about pointer arithmetic rules. First, the code computes(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L61) the width of each output element by dividing the `fixed_length` value to the size of the type argument. The `fixed_length` argument is also used to determine the size needed for the output tensor(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L63-L79). This is followed by reencoding code(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L85-L94). The erroneous code is the last line above: it is moving the `out_data` pointer by `fixed_length * sizeof(T)` bytes whereas it only copied at most `fixed_length` bytes from the input. This results in parts of the input not being decoded into the output. Furthermore, because the pointer advance is far wider than desired, this quickly leads to writing to outside the bounds of the backing data. This OOB write leads to interpreter crash in the reproducer mentioned here, but more severe attacks can be mounted too, given that this gadget allows writing to periodically placed locations in memory. 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 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.

The Flask-Caching extension through 1.10.1 for Flask relies on Pickle for serialization, which may lead to remote code execution or local privilege escalation. If an attacker gains access to cache storage (e.g., filesystem, Memcached, Redis, etc.), they can construct a crafted payload, poison the cache, and execute Python code. NOTE: a third party indicates that exploitation is extremely unlikely unless the machine is already compromised; in other cases, the attacker would be unable to write their payload to the cache and generate the required collision

Pydantic is a data validation and settings management using Python type hinting. In affected versions passing either `'infinity'`, `'inf'` or `float('inf')` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can't upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you'll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.

Synapse is a Matrix reference homeserver written in python (pypi package matrix-synapse). Matrix is an ecosystem for open federated Instant Messaging and VoIP. In Synapse before version 1.33.2 "Push rules" can specify conditions under which they will match, including `event_match`, which matches event content against a pattern including wildcards. Certain patterns can cause very poor performance in the matching engine, leading to a denial-of-service when processing moderate length events. The issue is patched in version 1.33.2. A potential workaround might be to prevent users from making custom push rules, by blocking such requests at a reverse-proxy.

Eventlet is a concurrent networking library for Python. A websocket peer may exhaust memory on Eventlet side by sending very large websocket frames. Malicious peer may exhaust memory on Eventlet side by sending highly compressed data frame. A patch in version 0.31.0 restricts websocket frame to reasonable limits. As a workaround, restricting memory usage via OS limits would help against overall machine exhaustion, but there is no workaround to protect Eventlet process.

In Django 2.2 before 2.2.22, 3.1 before 3.1.10, and 3.2 before 3.2.2 (with Python 3.9.5+), URLValidator does not prohibit newlines and tabs (unless the URLField form field is used). If an application uses values with newlines in an HTTP response, header injection can occur. Django itself is unaffected because HttpResponse prohibits newlines in HTTP headers.

In Python before 3,9,5, the ipaddress library mishandles leading zero characters in the octets of an IP address string. This (in some situations) allows attackers to bypass access control that is based on IP addresses.

The "origin" parameter passed to some of the endpoints like '/trigger' was vulnerable to XSS exploit. This issue affects Apache Airflow versions <1.10.15 in 1.x series and affects 2.0.0 and 2.0.1 and 2.x series. This is the same as CVE-2020-13944 & CVE-2020-17515 but the implemented fix did not fix the issue completely. Update to Airflow 1.10.15 or 2.0.2. Please also update your Python version to the latest available PATCH releases of the installed MINOR versions, example update to Python 3.6.13 if you are on Python 3.6. (Those contain the fix for CVE-2021-23336 https://nvd.nist.gov/vuln/detail/CVE-2021-23336).

Synapse is a Matrix reference homeserver written in python (pypi package matrix-synapse). Matrix is an ecosystem for open federated Instant Messaging and VoIP. In Synapse before version 1.28.0 Synapse is missing input validation of some parameters on the endpoints used to confirm third-party identifiers could cause excessive use of disk space and memory leading to resource exhaustion. Note that the groups feature is not part of the Matrix specification and the chosen maximum lengths are arbitrary. Not all clients might abide by them. Refer to referenced GitHub security advisory for additional details including workarounds.

Synapse is a Matrix reference homeserver written in python (pypi package matrix-synapse). Matrix is an ecosystem for open federated Instant Messaging and VoIP. In Synapse before version 1.28.0 requests to user provided domains were not restricted to external IP addresses when transitional IPv6 addresses were used. Outbound requests to federation, identity servers, when calculating the key validity for third-party invite events, sending push notifications, and generating URL previews are affected. This could cause Synapse to make requests to internal infrastructure on dual-stack networks. See referenced GitHub security advisory for details and workarounds.

Synapse is a Matrix reference homeserver written in python (pypi package matrix-synapse). Matrix is an ecosystem for open federated Instant Messaging and VoIP. In Synapse before version 1.28.0 Synapse is missing input validation of some parameters on the endpoints used to confirm third-party identifiers could cause excessive use of disk space and memory leading to resource exhaustion. Note that the groups feature is not part of the Matrix specification and the chosen maximum lengths are arbitrary. Not all clients might abide by them. Refer to referenced GitHub security advisory for additional details including workarounds.

models/metadata.py in the pikepdf package 1.3.0 through 2.9.2 for Python allows XXE when parsing XMP metadata entries.

Synapse is a Matrix reference homeserver written in python (pypi package matrix-synapse). Matrix is an ecosystem for open federated Instant Messaging and VoIP. In Synapse before version 1.27.0, the notification emails sent for notifications for missed messages or for an expiring account are subject to HTML injection. In the case of the notification for missed messages, this could allow an attacker to insert forged content into the email. The account expiry feature is not enabled by default and the HTML injection is not controllable by an attacker. This is fixed in version 1.27.0.

Synapse is a Matrix reference homeserver written in python (pypi package matrix-synapse). Matrix is an ecosystem for open federated Instant Messaging and VoIP. In Synapse before version 1.27.0, the password reset endpoint served via Synapse was vulnerable to cross-site scripting (XSS) attacks. The impact depends on the configuration of the domain that Synapse is deployed on, but may allow access to cookies and other browser data, CSRF vulnerabilities, and access to other resources served on the same domain or parent domains. This is fixed in version 1.27.0.

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.