VAITP

In affected versions of TensorFlow the tf.raw_ops.ImmutableConst operation returns a constant tensor created from a memory mapped file which is assumed immutable. However, if the type of the tensor is not an integral type, the operation crashes the Python interpreter as it tries to write to the memory area. If the file is too small, TensorFlow properly returns an error as the memory area has fewer bytes than what is needed for the tensor it creates. However, as soon as there are enough bytes, the above snippet causes a segmentation fault. This is because the allocator used to return the buffer data is not marked as returning an opaque handle since the needed virtual method is not overridden. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.

Sentry is an error tracking and performance monitoring platform. In versions of the sentry python library prior to 22.11.0 an attacker with a known valid invite link could manipulate a cookie to allow the same invite link to be reused on multiple accounts when joining an organization. As a result an attacker with a valid invite link can create multiple users and join an organization they may not have been originally invited to. This issue was patched in version 22.11.0. Sentry SaaS customers do not need to take action. Self-hosted Sentry installs on systems which can not upgrade can disable the invite functionality until they are ready to deploy the patched version by editing their `sentry.conf.py` file (usually located at `~/.sentry/`).

xwiki-platform-icon-ui is vulnerable to Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection'). Any user with view rights on commonly accessible documents including the icon picker macro can execute arbitrary Groovy, Python or Velocity code in XWiki due to improper neutralization of the macro parameters of the icon picker macro. The problem has been patched in XWiki 13.10.7, 14.5 and 14.4.2. Workarounds: The [patch](https://github.com/xwiki/xwiki-platform/commit/47eb8a5fba550f477944eb6da8ca91b87eaf1d01) can be manually applied by editing `IconThemesCode.IconPickerMacro` in the object editor. The whole document can also be replaced by the current version by importing the document from the XAR archive of a fixed version as the only changes to the document have been security fixes and small formatting changes.

Waitress is a Web Server Gateway Interface server for Python 2 and 3. Waitress versions 2.1.0 and 2.1.1 may terminate early due to a thread closing a socket while the main thread is about to call select(). This will lead to the main thread raising an exception that is not handled and then causing the entire application to be killed. This issue has been fixed in Waitress 2.1.2 by no longer allowing the WSGI thread to close the socket. Instead, that is always delegated to the main thread. There is no work-around for this issue. However, users using waitress behind a reverse proxy server are less likely to have issues if the reverse proxy always reads the full response.

Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. Running Auto-GPT version prior to 0.4.3 by cloning the git repo and executing `docker compose run auto-gpt` in the repo root uses a different docker-compose.yml file from the one suggested in the official docker set up instructions. The docker-compose.yml file located in the repo root mounts itself into the docker container without write protection. This means that if malicious custom python code is executed via the `execute_python_file` and `execute_python_code` commands, it can overwrite the docker-compose.yml file and abuse it to gain control of the host system the next time Auto-GPT is started. The issue has been patched in version 0.4.3.

Fides is an open-source privacy engineering platform for managing the fulfillment of data privacy requests in a runtime environment, and the enforcement of privacy regulations in code. The Fides webserver API allows custom integrations to be uploaded as a ZIP file. This ZIP file must contain YAML files, but Fides can be configured to also accept the inclusion of custom Python code in it. The custom code is executed in a restricted, sandboxed environment, but the sandbox can be bypassed to execute any arbitrary code. The vulnerability allows the execution of arbitrary code on the target system within the context of the webserver python process owner on the webserver container, which by default is `root`, and leverage that access to attack underlying infrastructure and integrated systems. This vulnerability affects Fides versions `2.11.0` through `2.19.0`. Exploitation is limited to API clients with the `CONNECTOR_TEMPLATE_REGISTER` authorization scope. In the Fides Admin UI this scope is restricted to highly privileged users, specifically root users and users with the owner role. Exploitation is only possible if the security configuration parameter `allow_custom_connector_functions` is enabled by the user deploying the Fides webserver container, either in `fides.toml` or by setting the env var `FIDES__SECURITY__ALLOW_CUSTOM_CONNECTOR_FUNCTIONS=True`. By default this configuration parameter is disabled. The vulnerability has been patched in Fides version `2.19.0`. Users are advised to upgrade to this version or later to secure their systems against this threat. Users unable to upgrade should ensure that `allow_custom_connector_functions` in `fides.toml` and the `FIDES__SECURITY__ALLOW_CUSTOM_CONNECTOR_FUNCTIONS` are both either unset or explicit set to `False`.

SQLFluff is a SQL linter. Prior to version 2.1.2, in environments where untrusted users have access to the config files, there is a potential security vulnerability where those users could use the `library_path` config value to allow arbitrary python code to be executed via macros. For many users who use SQLFluff in the context of an environment where all users already have fairly escalated privileges, this may not be an issue - however in larger user bases, or where SQLFluff is bundled into another tool where developers still wish to give users access to supply their on rule configuration, this may be an issue. The 2.1.2 release offers the ability for the `library_path` argument to be overwritten on the command line by using the `--library-path` option. This overrides any values provided in the config files and effectively prevents this route of attack for users which have access to the config file, but not to the scripts which call the SQLFluff CLI directly. A similar option is provided for the Python API, where users also have a greater ability to further customise or override configuration as necessary. Unless `library_path` is explicitly required, SQLFluff maintainers recommend using the option `--library-path none` when invoking SQLFluff which will disable the `library-path` option entirely regardless of the options set in the configuration file or via inline config directives. As a workaround, limiting access to - or otherwise validating configuration files before they are ingested by SQLFluff will provides a similar effect and does not require upgrade.

XWiki Commons are technical libraries common to several other top level XWiki projects. Any user with view rights on commonly accessible documents including the legacy notification activity macro can execute arbitrary Groovy, Python or Velocity code in XWiki leading to full access to the XWiki installation. The root cause is improper escaping of the macro parameters of the legacy notification activity macro. This macro is installed by default in XWiki. The vulnerability can be exploited via every wiki page that is editable including the user's profile, but also with just view rights using the HTMLConverter that is part of the CKEditor integration which is bundled with XWiki. The vulnerability has been patched in XWiki 13.10.11, 14.4.7 and 14.10.

Pure Storage FlashArray products running Purity//FA 6.2.0 - 6.2.3, 6.1.0 - 6.1.12, 6.0.0 - 6.0.8, 5.3.0 - 5.3.17, 5.2.x and prior Purity//FA releases, and Pure Storage FlashBlade products running Purity//FB 3.3.0, 3.2.0 - 3.2.4, 3.1.0 - 3.1.12, 3.0.x and prior Purity//FB releases are vulnerable to a privilege escalation via the manipulation of Python environment variables which can be exploited by a logged-in user to escape a restricted shell to an unrestricted shell with root privileges. No other Pure Storage products or services are affected. Remediation is available from Pure Storage via a self-serve “opt-in” patch, manual patch application or a software upgrade to an unaffected version of Purity software.

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.