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NVIDIA Megatron-LM for all platforms contains a vulnerability in a python component where an attacker may cause a code injection issue by providing a malicious file. A successful exploit of this vulnerability may lead to Code Execution, Escalation of Privileges, Information Disclosure and Data Tampering.
NVIDIA Megatron-LM for all platforms contains a vulnerability in a python component where an attacker may cause a code injection issue by providing a malicious file. A successful exploit of this vulnerability may lead to Code Execution, Escalation of Privileges, Information Disclosure and Data Tampering.
APTRS (Automated Penetration Testing Reporting System) is a python and Django-based automated reporting tool designed for penetration testers and security organizations. In 1.0, there is a vulnerability in the web application's handling of user-supplied input that is incorporated into a Jinja2 template. Specifically, when user input is improperly sanitized or validated, an attacker can inject Jinja2 syntax into the template, causing the server to execute arbitrary code. For example, an attacker might be able to inject expressions like {{ config }}, {{ self.class.mro[1].subclasses() }}, or more dangerous payloads that trigger execution of arbitrary python code. The vulnerability can be reproduced by submitting crafted input to all the template fields handled by ckeditor, that are passed directly to a Jinja2 template. If the input is rendered without sufficient sanitization, it results in the execution of malicious Jinja2 code on the server.
Jinja is an extensible templating engine. Prior to 3.1.5, An oversight in how the Jinja sandboxed environment detects calls to str.format allows an attacker that controls the content of a template to execute arbitrary python code. To exploit the vulnerability, an attacker needs to control the content of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates. Jinja's sandbox does catch calls to str.format and ensures they don't escape the sandbox. However, it's possible to store a reference to a malicious string's format method, then pass that to a filter that calls it. No such filters are built-in to Jinja, but could be present through custom filters in an application. After the fix, such indirect calls are also handled by the sandbox. This vulnerability is fixed in 3.1.5.
Qualys discovered that needrestart, before version 3.8, allows local attackers to execute arbitrary code as root by winning a race condition and tricking needrestart into running their own, fake python interpreter (instead of the system's real python interpreter). The initial security fix (6ce6136) introduced a regression which was subsequently resolved (42af5d3).
Qualys discovered that needrestart, before version 3.8, allows local attackers to execute arbitrary code as root by tricking needrestart into running the python interpreter with an attacker-controlled pythonPATH environment variable.
A vulnerability has been found in the Cpython `venv` module and CLI where path names provided when creating a virtual environment were not quoted properly, allowing the creator to inject commands into virtual environment "activation" scripts (ie "source venv/bin/activate"). This means that attacker-controlled virtual environments are able to run commands when the virtual environment is activated. Virtual environments which are not created by an attacker or which aren't activated before being used (ie "./venv/bin/python") are not affected.
An arbitrary code execution vulnerability exists in versions 0.2.9 up to 0.5.10 of the Guardrails AI Guardrails framework because of the way it validates XML files. If a victim user loads a maliciously crafted XML file containing python code, the code will be passed to an eval function, causing it to execute on the user's machine.
Robotmk before 2.0.1 allows a local user to escalate privileges (e.g., to SYSTEM) if automated python environment setup is enabled, because the "shared holotree usage" feature allows any user to edit any python environment.
Deserialization of untrusted data can occur in versions 0.6 or newer of the skops python library, enabling a maliciously crafted model to run arbitrary code on an end user's system when loaded.
sagemaker-python-sdk is a library for training and deploying machine learning models on Amazon SageMaker. In affected versions the capture_dependencies function in `sagemaker.serve.save_retrive.version_1_0_0.save.utils` module allows for potentially unsafe Operating System (OS) Command Injection if inappropriate command is passed as the “requirements_path” parameter. This consequently may allow an unprivileged third party to cause remote code execution, denial of service, affecting both confidentiality and integrity. This issue has been addressed in version 2.214.3. Users are advised to upgrade. Users unable to upgrade should not override the “requirements_path” parameter of capture_dependencies function in `sagemaker.serve.save_retrive.version_1_0_0.save.utils`, and instead use the default value.
sagemaker-python-sdk is a library for training and deploying machine learning models on Amazon SageMaker. The sagemaker.base_deserializers.NumpyDeserializer module before v2.218.0 allows potentially unsafe deserialization when untrusted data is passed as pickled object arrays. This consequently may allow an unprivileged third party to cause remote code execution, denial of service, affecting both confidentiality and integrity. Users are advised to upgrade to version 2.218.0. Users unable to upgrade should not pass pickled numpy object arrays which originated from an untrusted source, or that could have been tampered with. Only pass pickled numpy object arrays from trusted sources.
An issue was found in the Cpython `tempfile.TemporaryDirectory` class affecting versions 3.12.1, 3.11.7, 3.10.13, 3.9.18, and 3.8.18 and prior. The tempfile.TemporaryDirectory class would dereference symlinks during cleanup of permissions-related errors. This means users which can run privileged programs are potentially able to modify permissions of files referenced by symlinks in some circumstances.
python 3.9.x before 3.9.16 and 3.10.x before 3.10.9 on Linux allows local privilege escalation in a non-default configuration. The python multiprocessing library, when used with the forkserver start method on Linux, allows pickles to be deserialized from any user in the same machine local network namespace, which in many system configurations means any user on the same machine. Pickles can execute arbitrary code. Thus, this allows for local user privilege escalation to the user that any forkserver process is running as. Setting multiprocessing.util.abstract_sockets_supported to False is a workaround. The forkserver start method for multiprocessing is not the default start method. This issue is Linux specific because only Linux supports abstract namespace sockets. Cpython before 3.9 does not make use of Linux abstract namespace sockets by default. Support for users manually specifying an abstract namespace socket was added as a bugfix in 3.7.8 and 3.8.3, but users would need to make specific uncommon API calls in order to do that in Cpython before 3.9.
needrestart 0.8 through 3.5 before 3.6 is prone to local privilege escalation. Regexes to detect the Perl, python, and Ruby interpreters are not anchored, allowing a local user to escalate privileges when needrestart tries to detect if interpreters are using old source files.
360 Total Security 9.0.0.1202 before 2017-07-07 allows Privilege Escalation via a Trojan horse Shcore.dll file in any directory in the PATH, as demonstrated by the C:\python27 directory.
Palo Alto Networks Panorama VM Appliance with PAN-OS before 6.0.1 might allow remote attackers to execute arbitrary python code via a crafted firmware image file.
An issue was discovered in Apport before 2.20.4. There is a path traversal issue in the Apport crash file "Package" and "SourcePackage" fields. These fields are used to build a path to the package specific hook files in the /usr/share/apport/package-hooks/ directory. An attacker can exploit this path traversal to execute arbitrary python files from the local system.
An issue was discovered in Apport before 2.20.4. In apport/ui.py, Apport reads the CrashDB field and it then evaluates the field as python code if it begins with a "{". This allows remote attackers to execute arbitrary python code.
IBM SPSS Statistics 22.0.0.2 before IF10 and 23.0.0.2 before IF7 uses weak permissions (Everyone: Write) for python scripts, which allows local users to gain privileges by modifying a script.