23andMe Yamale before 3.0.8 allows remote attackers to execute arbitrary code via a crafted schema file. The schema parser uses eval as part of its processing, and tries to protect from malicious expressions by limiting the builtins that are passed to the eval. When processing the schema, each line is run through Python's eval function to make the validator available. A well-constructed string within the schema rules can execute system commands; thus, by exploiting the vulnerability, an attacker can run arbitrary code on the image that invokes Yamale.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions most implementations of convolution operators in TensorFlow are affected by a division by 0 vulnerability where an attacker can trigger a denial of service via a crash. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/framework/common_shape_fns.cc#L577) is missing several validations before doing divisions and modulo operations. We have patched the issue in GitHub commit 8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. In affected versions TensorFlow's `saved_model_cli` tool is vulnerable to a code injection as it calls `eval` on user supplied strings. This can be used by attackers to run arbitrary code on the plaform where the CLI tool runs. However, given that the tool is always run manually, the impact of this is not severe. We have patched this by adding a `safe` flag which defaults to `True` and an explicit warning for users. 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.

The d8s-networking package for Python, as distributed on PyPI, included a potential code-execution backdoor inserted by a third party. The backdoor is the democritus-hashes package. The affected version is 0.1.0.

While investigating a bug report on Apache Superset, it was determined that an authenticated user could craft requests via a number of templated text fields in the product that would allow arbitrary access to Python’s `os` package in the web application process in versions < 0.37.1. It was thus possible for an authenticated user to list and access files, environment variables, and process information. Additionally it was possible to set environment variables for the current process, create and update files in folders writable by the web process, and execute arbitrary programs accessible by the web process. All other operations available to the `os` package in Python were also available, even if not explicitly enumerated in this CVE.

Cross Site Scripting (XSS) in Mezzanine v4.3.1 allows remote attackers to execute arbitrary code via the 'Description' field of the component 'admin/blog/blogpost/add/'. This issue is different than CVE-2018-16632.

pretix before 2024.1.1 mishandles file validation.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of SVDF in TFLite is [vulnerable to a null pointer error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/svdf.cc#L300-L313). The [`GetVariableInput` function](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L115-L119) can return a null pointer but `GetTensorData` assumes that the argument is always a valid tensor. Furthermore, because `GetVariableInput` calls [`GetMutableInput`](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L82-L90) which might return `nullptr`, the `tensor->is_variable` expression can also trigger a null pointer exception. We have patched the issue in GitHub commit 5b048e87e4e55990dae6b547add4dae59f4e1c76. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Celery 2.1 and 2.2 before 2.2.8, 2.3 before 2.3.4, and 2.4 before 2.4.4 changes the effective id but not the real id during processing of the --uid and --gid arguments to celerybeat, celeryd_detach, celeryd-multi, and celeryev, which allows local users to gain privileges via vectors involving crafted code that is executed by the worker process.

Privilege Context Switching Error vulnerability in Apache Software Foundation Apache Airflow.This issue affects Apache Airflow: before 2.6.0.



An issue was discovered in Pillow before 8.2.0. For FLI data, FliDecode did not properly check that the block advance was non-zero, potentially leading to an infinite loop on load.

The LDAP backend in OpenStack Identity (Keystone) Grizzly and Havana, when removing a role on a tenant for a user who does not have that role, adds the role to the user, which allows local users to gain privileges.

z3c.form, as used in Plone before 4.2.3 and 4.3 before beta 1, allows remote attackers to obtain the default form field values by leveraging knowledge of the form location and the element id.

before_upstream_connection in AuthPlugin in http/proxy/auth.py in proxy.py before 2.3.1 accepts incorrect Proxy-Authorization header data because of a boolean confusion (and versus or).

Plone CMS before 3 places a base64 encoded form of the username and password in the `__ac` cookie for all user accounts, which makes it easier for remote attackers to obtain access by sniffing the network.

Unknown vulnerability in MoinMoin 1.2.2 and earlier allows remote attackers to gain unauthorized access to administrator functions such as (1) revert and (2) delete.

This affects all versions of package html-to-csv. When there is a formula embedded in a HTML page, it gets accepted without any validation and the same would be pushed while converting it into a CSV file. Through this a malicious actor can embed or generate a malicious link or execute commands via CSV files.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/python/keras/saving/model_config.py#L66-L104) uses `yaml.unsafe_load` which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

The PlonePAS product 3.x before 3.9 and 3.2.x before 3.2.2, a product for Plone, does not properly handle the login form, which allows remote authenticated users to acquire the identity of an arbitrary user via unspecified vectors.

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `tf.raw_ops.Switch` operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is `nullptr`, hence we are binding a reference to `nullptr`. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

TensorFlow is an end-to-end open source platform for machine learning. The TFLite code for allocating `TFLiteIntArray`s is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/4ceffae632721e52bf3501b736e4fe9d1221cdfa/tensorflow/lite/c/common.c#L24-L27). An attacker can craft a model such that the `size` multiplier is so large that the return value overflows the `int` datatype and becomes negative. In turn, this results in invalid value being given to `malloc`(https://github.com/tensorflow/tensorflow/blob/4ceffae632721e52bf3501b736e4fe9d1221cdfa/tensorflow/lite/c/common.c#L47-L52). In this case, `ret->size` would dereference an invalid pointer. 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.

MISP MISP-maltego 1.4.4 incorrectly shares a MISP connection across users in a remote-transform use case.

LIEF commit 365a16a was discovered to contain a heap-buffer overflow via the function print_binary at /c/macho_reader.c.

A flaw was discovered in the way Ansible templating was implemented in versions before 2.6.18, 2.7.12 and 2.8.2, causing the possibility of information disclosure through unexpected variable substitution. By taking advantage of unintended variable substitution the content of any variable may be disclosed.

The s3_token middleware in OpenStack keystonemiddleware before 1.6.0 and python-keystoneclient before 1.4.0 disables certification verification when the "insecure" option is set in a paste configuration (paste.ini) file regardless of the value, which allows remote attackers to conduct man-in-the-middle attacks via a crafted certificate, a different vulnerability than CVE-2014-7144.

In Apache Airflow 1.8.2 and earlier, an authenticated user can execute code remotely on the Airflow webserver by creating a special object.

Openstack Compute (Nova) Folsom, 2012.1, and 2011.3 does not limit the number of security group rules, which allows remote authenticated users with certain permissions to cause a denial of service (CPU and hard drive consumption) via a network request that triggers a large number of iptables rules.

The DocumentTemplate package in Zope 2.2 and earlier allows a remote attacker to modify DTMLDocuments or DTMLMethods without authorization.

The isURLInPortal method in the URLTool class in in_portal.py in Plone 2.1 through 4.1, 4.2.x through 4.2.5, and 4.3.x through 4.3.1 treats URLs starting with a space as a relative URL, which allows remote attackers to bypass the allow_external_login_sites filtering property,  redirect users to arbitrary web sites, and conduct phishing attacks via a space before a URL in the "next" parameter to acl_users/credentials_cookie_auth/require_login.

In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in caused by an integer overflow in constructing a new tensor shape. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/0908c2f2397c099338b901b067f6495a5b96760b/tensorflow/core/kernels/sparse_split_op.cc#L66-L70) builds a dense shape without checking that the dimensions would not result in overflow. The `TensorShape` constructor(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when `InitDims`(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status. This is a legacy implementation of the constructor and operations should use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in the presence of overflows. 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.

Multiple cross-site scripting (XSS) vulnerabilities in (1) spamProtect.py, (2) pts.py, and (3) request.py in Plone 2.1 through 4.1, 4.2.x through 4.2.5, and 4.3.x through 4.3.1 allow remote attackers to inject arbitrary web script or HTML via unspecified vectors.

OpenStack Identity (Keystone) before 2013.1 allows remote attackers to cause a denial of service (memory consumption and crash) via multiple long requests.

untangle is a python library to convert XML data to python objects. untangle versions 1.2.0 and earlier improperly restricts XML external entity references. By exploiting this vulnerability, a remote unauthenticated attacker may read the contents of local files.

Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that Grappler optimizer would attempt to build a tensor using a reference `dtype`. This would result in a crash due to a `CHECK`-fail in the `Tensor` constructor as reference types are not allowed. 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.

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).

The pip package before 19.2 for Python allows Directory Traversal when a URL is given in an install command, because a Content-Disposition header can have ../ in a filename, as demonstrated by overwriting the /root/.ssh/authorized_keys file. This occurs in _download_http_url in _internal/download.py.

** Reserved ** The pyesasky for python, as distributed on PyPI, included a code-execution backdoor inserted by a third party. The current version, without this backdoor, is 1.2.0-1.4.2.

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `SparseFillEmptyRowsGrad` implementation has incomplete validation of the shapes of its arguments. Although `reverse_index_map_t` and `grad_values_t` are accessed in a similar pattern, only `reverse_index_map_t` is validated to be of proper shape. Hence, malicious users can pass a bad `grad_values_t` to trigger an assertion failure in `vec`, causing denial of service in serving installations. The issue is patched in commit 390611e0d45c5793c7066110af37c8514e6a6c54, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1."

Synopsys hub-rest-api-python (aka blackduck on PyPI) version 0.0.25 - 0.0.52 does not validate SSL certificates in certain cases.

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.

** DISPUTED ** Improper parsing of HTTP requests in Pallets Werkzeug v2.1.0 and below allows attackers to perform HTTP Request Smuggling using a crafted HTTP request with multiple requests included inside the body. NOTE: the vendor's position is that this behavior can only occur in unsupported configurations involving development mode and an HTTP server from outside the Werkzeug project.

Django before 1.4.21, 1.5.x through 1.6.x, 1.7.x before 1.7.9, and 1.8.x before 1.8.3 uses an incorrect regular expression, which allows remote attackers to inject arbitrary headers and conduct HTTP response splitting attacks via a newline character in an (1) email message to the EmailValidator, a (2) URL to the URLValidator, or unspecified vectors to the (3) validate_ipv4_address or (4) validate_slug validator.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can generate undefined behavior via a reference binding to nullptr in `BoostedTreesCalculateBestGainsPerFeature` and similar attack can occur in `BoostedTreesCalculateBestFeatureSplitV2`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/stats_ops.cc) does not validate the input values. We have patched the issue in GitHub commit 9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad and in commit 429f009d2b2c09028647dd4bb7b3f6f414bbaad7. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

The Pallets Project flask version Before 0.12.3 contains a CWE-20: Improper Input Validation vulnerability in flask that can result in Large amount of memory usage possibly leading to denial of service. This attack appear to be exploitable via Attacker provides JSON data in incorrect encoding. This vulnerability appears to have been fixed in 0.12.3. NOTE: this may overlap CVE-2019-1010083.

In Apache Incubator Superset before 0.32, a user can view database names that he has no access to on a dropdown list in SQLLab

Cross-site scripting (XSS) vulnerability in `skins/plone_templates/default_error_message.pt` in Plone before 2.5.3 allows remote attackers to inject arbitrary web script or HTML via the type_name parameter to `Members/ipa/createObject`.

Eval injection in the Math plugin of Limnoria (before 2019.11.09) and Supybot (through 2018-05-09) allows remote unprivileged attackers to disclose information or possibly have unspecified other impact via the calc and icalc IRC commands.

Jubatus 1.0.2 and earlier allows remote code execution via unspecified vectors.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a read from outside of bounds of heap allocated data by sending invalid arguments to `tf.raw_ops.ResourceScatterUpdate`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L919-L923) has an incomplete validation of the relationship between the shapes of `indices` and `updates`: instead of checking that the shape of `indices` is a prefix of the shape of `updates` (so that broadcasting can happen), code only checks that the number of elements in these two tensors are in a divisibility relationship. We have patched the issue in GitHub commit 01cff3f986259d661103412a20745928c727326f. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

The TAR file parser in Avira AntiVir 7.11.1.163, Antiy Labs AVL SDK 2.0.3.7, avast! Antivirus 4.8.1351.0 and 5.0.677.0, AVG Anti-Virus 10.0.0.1190, Bitdefender 7.2, Quick Heal (aka Cat QuickHeal) 11.00, ClamAV 0.96.4, Command Antivirus 5.2.11.5, Emsisoft Anti-Malware 5.1.0.1, eSafe 7.0.17.0, F-Prot Antivirus 4.6.2.117, G Data AntiVirus 21, Ikarus Virus Utilities T3 Command Line Scanner 1.1.97.0, Jiangmin Antivirus 13.0.900, K7 AntiVirus 9.77.3565, Kaspersky Anti-Virus 7.0.0.125, McAfee Anti-Virus Scanning Engine 5.400.0.1158, McAfee Gateway (formerly Webwasher) 2010.1C, Antimalware Engine 1.1.6402.0 in Microsoft Security Essentials 2.0, NOD32 Antivirus 5795, Norman Antivirus 6.06.12, PC Tools AntiVirus 7.0.3.5, Rising Antivirus 22.83.00.03, AVEngine 20101.3.0.103 in Symantec Endpoint Protection 11, Trend Micro AntiVirus 9.120.0.1004, Trend Micro HouseCall 9.120.0.1004, VBA32 3.12.14.2, and VirusBuster 13.6.151.0 allows remote attackers to bypass malware detection via a TAR archive entry with a length field that exceeds the total TAR file size.  NOTE: this may later be SPLIT into multiple CVEs if additional information is published showing that the error occurred independently in different TAR parser implementations.

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.SparseMatMul`. The division by 0 occurs deep in Eigen code because the `b` tensor is empty. 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.

An issue was discovered in py-lmdb 0.97. mdb_node_del does not validate a memmove in the case of an unexpected node->mn_hi, leading to an invalid write operation. NOTE: this outcome occurs when accessing a data.mdb file supplied by an attacker.

The DTML implementation in the Z Object Publishing Environment (Zope) allows remote attackers to conduct unauthorized activities.

## Local file disclosure through LaTeX injection

### Impact
An external audit of the Indico codebase has discovered a vulnerability in Indico's LaTeX sanitization code, which could have malicious users to run unsafe LaTeX commands on the server. Such commands allowed for example to read local files (e.g. `indico.conf`).

As far as we know it is not possible to write files or execute code using this vulnerability.

### Patches
You need to update to [Indico 2.2.3](https://github.com/indico/indico/releases/tag/v2.2.3) as soon as possible.
We also released [Indico 2.1.10](https://github.com/indico/indico/releases/tag/v2.1.10) in case you cannot update to 2.2 for some reason.
See https://docs.getindico.io/en/stable/installation/upgrade/ for instructions on how to update.

### Workarounds
Setting `XELATEX_PATH = None` in `indico.conf` will result in an error when building a PDF, but without being able to run xelatex, the vulnerability cannot be abused.

### For more information
If you have any questions or comments about this advisory:
* Open a thread in [our forum](https://talk.getindico.io/)
* Email us privately at [indico-team@cern.ch](mailto:indico-team@cern.ch)



TensorFlow is an open source platform for machine learning. In affected versions the implementation of `FusedBatchNorm` kernels is vulnerable to a heap OOB access. 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.

Part of the "Hades" wave of the Shai-Hulud supply-chain campaign. On 2026-06-08,
malicious phantom releases of pantheon-agents were published to PyPI using stolen
credentials. The package executes a bundled JavaScript payload (via the Bun
runtime) on import that harvests and exfiltrates credentials and attempts
self-propagation. This entry is a summary; behavior may not be fully
characterized here. See the linked references for detailed analysis and
indicators of compromise.


TensorFlow is an end-to-end open source platform for machine learning. Specifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap<T>` (i.e., `std::vector<absl::flat_hash_map<int64,T>>`(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure. If the `shape` tensor has more than one element, `num_batches` is the first value in `shape`. Ensuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3.

OpenStack keystonemiddleware (formerly python-keystoneclient) 0.x before 0.11.0 and 1.x before 1.2.0 disables certification verification when the "insecure" option is set in a paste configuration (paste.ini) file regardless of the value, which allows remote attackers to conduct man-in-the-middle attacks via a crafted certificate.

An incomplete fix was found for the fix of the flaw CVE-2020-1733 ansible: insecure temporary directory when running become_user from become directive. The provided fix is insufficient to prevent the race condition on systems using ACLs and FUSE filesystems. Ansible Engine 2.7.18, 2.8.12, and 2.9.9 as well as previous versions are affected and Ansible Tower 3.4.5, 3.5.6 and 3.6.4 as well as previous versions are affected.

cache.py in Suds 0.4, when tempdir is set to None, allows local users to redirect SOAP queries and possibly have other unspecified impact via a symlink attack on a cache file with a predictable name in /tmp/suds/.

Ansible "User" module leaks any data which is passed on as a parameter to ssh-keygen. This could lean in undesirable situations such as passphrases credentials passed as a parameter for the ssh-keygen executable. Showing those credentials in clear text form for every user which have access just to the process list.

`bin/compile-messages.py` in Django 0.95 does not quote argument strings before invoking the msgfmt program through the os.system function, which allows attackers to execute arbitrary commands via shell metacharacters in a (1) .po or (2) .mo file.

In RPyC before 6.0.0, when a server exposes a method that calls the attribute named __array__ for a client-provided netref (e.g., np.array(client_netref)), a remote attacker can craft a class that results in remote code execution.

TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for the `Cudnn*` operations in TensorFlow can be tricked into accessing invalid memory, via a heap buffer overflow. This occurs because the ranks of the `input`, `input_h` and `input_c` parameters are not validated, but code assumes they have certain values. 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.

The default configuration for salt-ssh in Salt (aka SaltStack) 0.17.0 does not validate the SSH host key of requests, which allows remote attackers to have unspecified impact via a man-in-the-middle (MITM) attack.

(1) core/tests/test_memmap.py, (2) core/tests/test_multiarray.py, (3) f2py/f2py2e.py, and (4) lib/tests/test_io.py in NumPy before 1.8.1 allow local users to write to arbitrary files via a symlink attack on a temporary file.

openssh_key_parser is an open source Python package providing utilities to parse and pack OpenSSH private and public key files. In versions prior to 0.0.6 if a field of a key is shorter than it is declared to be, the parser raises an error with a message containing the raw field value. An attacker able to modify the declared length of a key's sensitive field can thus expose the raw value of that field. Users are advised to upgrade to version 0.0.6, which no longer includes the raw field value in the error message. There are no known workarounds for this issue.

TensorFlow is an end-to-end open source platform for machine learning. It is possible to trigger a null pointer dereference in TensorFlow by passing an invalid input to `tf.raw_ops.CompressElement`. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/data/compression_utils.cc#L34) was accessing the size of a buffer obtained from the return of a separate function call before validating that said buffer is valid. We have patched the issue in GitHub commit 5dc7f6981fdaf74c8c5be41f393df705841fb7c5. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Apache Libcloud before 0.11.1 uses an incorrect regular expression during verification of whether the server hostname matches a domain name in the subject's Common Name (CN) or subjectAltName field of the X.509 certificate, which allows man-in-the-middle attackers to spoof SSL servers via a crafted certificate.

Pillow before 3.3.2 allows context-dependent attackers to execute arbitrary code by using the "crafted image file" approach, related to an "Insecure Sign Extension" issue affecting the ImagingNew in Storage.c component.

The default LDAP ACIs in FreeIPA 3.0 before 3.1.2 do not restrict access to the (1) ipaNTTrustAuthIncoming and (2) ipaNTTrustAuthOutgoing attributes, which allow remote attackers to obtain the Cross-Realm Kerberos Trust key via unspecified vectors.

The i_create_images_and_backing (aka create_images_and_backing) method in libvirt driver in OpenStack Compute (Nova) Grizzly, Havana, and Icehouse, when using KVM live block migration, does not properly create all expected files, which allows attackers to obtain snapshot root disk contents of other users via ephemeral storage.

In the affected versions, the AWS Encryption CLI operated in "discovery mode" even when "strict mode" was specified. Although decryption only succeeded if the user had permission to decrypt with at least one of the CMKs, decryption could be successful using a CMK that was not included in the user-defined set when the CLI was operating in "strict mode."

Affected users should upgrade to Encryption CLI v1.8.x or v2.1.x as soon as possible.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.ExperimentalDatasetToTFRecord` and `tf.raw_ops.DatasetToTFRecord` can trigger heap buffer overflow and segmentation fault. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc#L93-L102) assumes that all records in the dataset are of string type. However, there is no check for that, and the example given above uses numeric types. We have patched the issue in GitHub commit e0b6e58c328059829c3eb968136f17aa72b6c876. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

sendto.py in Plone 2.1 through 4.1, 4.2.x through 4.2.5, and 4.3.x through 4.3.1 allows remote authenticated users to spoof emails via unspecified vectors.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

A flaw was found in the Ansible Engine when the fetch module is used. An attacker could intercept the module, inject a new path, and then choose a new destination path on the controller node. All versions in 2.7.x, 2.8.x and 2.9.x branches are believed to be vulnerable.

The TempURL middleware in OpenStack Object Storage (Swift) 1.4.6 through 1.8.0, 1.9.0 through 1.10.0, and 1.11.0 allows remote attackers to obtain secret URLs by leveraging an object name and a timing side-channel attack.

TensorFlow is an end-to-end open source platform for machine learning. The validation in `tf.raw_ops.QuantizeAndDequantizeV2` allows invalid values for `axis` argument:. The validation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L74-L77) uses `||` to mix two different conditions. If `axis_ < -1` the condition in `OP_REQUIRES` will still be true, but this value of `axis_` results in heap underflow. This allows attackers to read/write to other data on the heap. 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.

CVE ID↕	Published↕	CVSS↓
PYSEC-2021-119	Aug 9, 2021	N/A
PYSEC-2021-588	Aug 12, 2021	N/A
PYSEC-2021-637	Nov 5, 2021	N/A
PYSEC-2022-43044	Oct 11, 2022	N/A
PYSEC-2020-222	Sep 17, 2020	N/A
PYSEC-2021-343	Aug 27, 2021	N/A
GHSA-672r-97r7-vx2q	Feb 26, 2024	N/A
PYSEC-2021-792	Aug 12, 2021	N/A
PYSEC-2011-17	Dec 5, 2011	N/A
PYSEC-2023-59	May 8, 2023	N/A
PYSEC-2021-92	Jun 2, 2021	N/A
GHSA-f889-wfwm-6p7m	May 17, 2022	N/A
PYSEC-2014-33	Sep 30, 2014	N/A
PYSEC-2021-46	Jan 11, 2021	N/A
PYSEC-2026-734	Jul 2, 2026	N/A
PYSEC-2026-680	Jul 2, 2026	N/A
PYSEC-2021-866	Nov 26, 2021	N/A
PYSEC-2021-300	Aug 12, 2021	N/A
PYSEC-2009-17	Apr 23, 2009	N/A
PYSEC-2020-113	Sep 25, 2020	N/A
PYSEC-2021-533	May 14, 2021	N/A
PYSEC-2020-66	May 15, 2020	N/A
PYSEC-2022-276	Sep 13, 2022	N/A
PYSEC-2019-2	Jul 30, 2019	N/A
PYSEC-2015-30	Apr 17, 2015	N/A
PYSEC-2019-147	Jan 23, 2019	N/A
GHSA-hq3f-9gf7-73r8	May 17, 2022	N/A
PYSEC-2026-760	Jul 2, 2026	N/A
PYSEC-2014-64	Jan 21, 2014	N/A
PYSEC-2020-336	Dec 10, 2020	N/A
PYSEC-2021-221	May 14, 2021	N/A
PYSEC-2014-54	Mar 11, 2014	N/A
PYSEC-2026-651	Jul 2, 2026	N/A
PYSEC-2022-244	Jul 26, 2022	N/A
PYSEC-2022-97	Feb 4, 2022	N/A
PYSEC-2021-4	May 2, 2021	N/A
PYSEC-2020-192	Sep 4, 2020	N/A
PYSEC-2022-220	Jun 24, 2022	N/A
PYSEC-2020-117	Sep 25, 2020	N/A
PYSEC-2020-26	Nov 6, 2020	N/A
PYSEC-2021-13	May 13, 2021	N/A
PYSEC-2022-203	May 25, 2022	N/A
PYSEC-2015-10	Jul 14, 2015	N/A
PYSEC-2021-575	Aug 12, 2021	N/A
PYSEC-2018-66	Aug 20, 2018	N/A
PYSEC-2019-173	Dec 16, 2019	N/A
PYSEC-2026-896	Jul 6, 2026	N/A
PYSEC-2019-32	Nov 16, 2019	N/A
PYSEC-2012-36	Jun 7, 2012	N/A
PYSEC-2018-114	Mar 9, 2018	N/A
PYSEC-2021-766	Aug 12, 2021	N/A
PYSEC-2012-25	Mar 21, 2012	N/A
PYSEC-2021-485	May 14, 2021	N/A
PYSEC-2019-238	Sep 11, 2019	N/A
PYSEC-2026-762	Jul 2, 2026	N/A
GHSA-67cx-rhhq-mfhq	Oct 11, 2019	N/A
PYSEC-2021-632	Nov 5, 2021	N/A
PYSEC-2021-242	May 14, 2021	N/A
PYSEC-2026-607	Jul 1, 2026	N/A
PYSEC-2021-158	May 14, 2021	N/A
PYSEC-2014-71	Oct 2, 2014	N/A
PYSEC-2020-208	May 15, 2020	N/A
PYSEC-2013-33	Sep 23, 2013	N/A
PYSEC-2018-44	Oct 23, 2018	N/A
PYSEC-2026-630	Jul 2, 2026	N/A
PYSEC-2024-44	Mar 12, 2024	N/A
PYSEC-2021-630	Nov 5, 2021	N/A
PYSEC-2013-26	Nov 5, 2013	N/A
PYSEC-2018-34	Jan 8, 2018	N/A
PYSEC-2022-233	Jul 6, 2022	N/A
PYSEC-2021-259	Aug 12, 2021	N/A
PYSEC-2012-12	Nov 4, 2012	N/A
PYSEC-2016-9	Nov 4, 2016	N/A
PYSEC-2014-100	May 29, 2014	N/A
PYSEC-2014-111	Feb 6, 2014	N/A
GHSA-2xwp-m7mq-7q3r	Oct 28, 2020	N/A
PYSEC-2021-563	Aug 12, 2021	N/A
PYSEC-2014-56	Mar 11, 2014	N/A
PYSEC-2021-603	Aug 13, 2021	N/A
PYSEC-2020-7	Mar 16, 2020	N/A
PYSEC-2014-116	Jan 23, 2014	N/A
PYSEC-2021-736	May 14, 2021	N/A

Know every vulnerability
before it knows you.

pypi CVE Vulnerabilities — DevGuard Vulnerability Database

Know every vulnerabilitybefore it knows you.

pypi CVE Vulnerabilities — DevGuard Vulnerability Database

Know every vulnerability
before it knows you.