The snorkel library thru v0.10.0 contains a critical insecure deserialization vulnerability (CWE-502) in the BaseLabeler.load() method of the BaseLabeler class. The method loads serialized labeler models using the unsafe pickle.load() function on user-supplied file paths without any validation or security controls. Python's pickle module is inherently dangerous for deserializing untrusted data, as it can execute arbitrary code during the deserialization process. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the victim's system when the file is loaded via the vulnerable method.

The snorkel library thru v0.10.0 contains an insecure deserialization vulnerability (CWE-502) in the Trainer.load() method of the Trainer class. The method loads model checkpoint files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the Pickle module. A remote attacker can exploit this by providing a maliciously crafted model file, leading to arbitrary code execution on the victim's system when the file is loaded via the vulnerable method.

PyTorch-Lightning versions 2.6.0 and earlier contain an insecure deserialization vulnerability (CWE-502) in the checkpoint loading mechanism. The LightningModule.load_from_checkpoint() method, which is commonly used to load saved model states, internally calls torch.load() without setting the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the Pickle module. A remote attacker can exploit this by providing a maliciously crafted checkpoint file, leading to arbitrary code execution on the victim's system when the file is loaded.

PySyft (Syft Datasite/Server) versions 0.9.5 and earlier are vulnerable to remote code execution due to insufficient validation and sandboxing of user-submitted code. The system allows low-privileged users to submit Python functions (via @sy.syft_function()) for remote execution on the server. While a code approval mechanism exists, the submitted code undergoes no security checks for dangerous operations (e.g., file access, command execution). Once approved, the code is executed within the server process using exec() and eval() functions without proper isolation. A remote attacker can leverage this to execute arbitrary Python code on the server, leading to complete compromise of the server environment.

The _load_model() function in the neural_magic_training.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f (2024-07-21) is vulnerable to insecure deserialization (CWE-502). When a user provides a single model file path (e.g., .pt or .pth) via the --model command-line argument, the function loads the file using torch.load() without enabling the weights_only=True security parameter. This allows the deserialization of arbitrary Python objects through the Pickle module. A remote attacker can exploit this by providing a maliciously crafted model file, leading to arbitrary code execution during deserialization on the victim's system.

The _load_model() function in the neural_magic_training.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f (2024-07-21) is vulnerable to insecure deserialization (CWE-502). When loading a model state dictionary from a state_dict.pt file via torch.load(), the function does not enable the weights_only=True security parameter. This allows the deserialization of arbitrary Python objects through the Pickle module. A remote attacker can exploit this by providing a maliciously crafted state_dict.pt file within a directory specified via the --model argument, leading to arbitrary code execution during the deserialization process on the victim's system.

The _load_model() function in the neural_magic_training.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f (2024-07-21) allows arbitrary code execution. When a user supplies a directory path via the --model command-line argument, the function reads a module.py file from that directory and executes its contents directly using Python's exec() function. This design does not validate or sanitize the file's content, allowing an attacker who controls the input directory to execute arbitrary Python code in the context of the process running the script.

The nexent v1.7.5.2 backend service contains an unauthorized arbitrary storage file deletion vulnerability in its file management API. The DELETE /storage/{object_name:path} endpoint lacks authentication, authorization, and input validation mechanisms. Unauthenticated remote attackers can send crafted requests with a user-controlled object_name path parameter to delete arbitrary files from the underlying MinIO storage system. Successful exploitation leads to data loss and denial of service.

The nexent v1.7.5.2 backend service contains an unauthorized arbitrary file deletion vulnerability in its ElasticSearch service interface. The DELETE /{index_name}/documents endpoint lacks proper authentication and authorization controls and does not validate the user-supplied path_or_url parameter. This allows unauthenticated remote attackers to send crafted requests that trigger the deletion of arbitrary documents from ElasticSearch indices and corresponding files from the MinIO storage system. Successful exploitation leads to data destruction and denial of service.

The torch-checkpoint-shrink.py script in the ml-engineering project in commit 0099885db36a8f06556efe1faf552518852cb1e0 (2025-20-27) contains an insecure deserialization vulnerability (CWE-502). The script uses torch.load() to process PyTorch checkpoint files (.pt) without enabling the security-restrictive weights_only=True parameter. This oversight allows the deserialization of arbitrary Python objects via the pickle module. A remote attacker can exploit this by providing a maliciously crafted checkpoint file, leading to arbitrary code execution in the context of the user running the script.

Server-Side Request Forgery vulnerability allows Privilege Escalation via API Checker extension. This issue affects Pandora FMS: from 777 through 800

Session Fixation vulnerability allows Session Hijacking via crafted session ID. This issue affects Pandora FMS: from 777 through 800

Cross-Site Request Forgery vulnerability allows an attacker to perform unauthorized actions via crafted web page. This issue affects Pandora FMS: from 777 through 800

Insecure Default Initialization of Resource vulnerability allows Authentication Bypass via API access. This issue affects Pandora FMS: from 777 through 800

An insecure direct object reference in MK-Auth 23.01K4.9 allows attackers to access and send support calls for other users via manipulation of the chamado parameter through a crafted GET request.

An arbitrary file upload vulnerability in MK-Auth 23.01K4.9 allows attackers to execute arbitrary code via uploading a crafted PHP file.

Sandbox escape in the Profile Backup component. This vulnerability was fixed in Firefox 150.0.3.

LWP::UserAgent versions before 6.83 for Perl leak Authorization and Proxy-Authorization headers on cross-origin redirects. On a 3xx response, the redirect handler strips only Host and Cookie before issuing the follow-up request. Caller-supplied Authorization and Proxy-Authorization headers are sent unchanged to the redirect target, including across scheme, host, or port changes. A redirect to an attacker controlled host therefore discloses the caller's credentials to that host.

SQL injection in the web console of Ivanti Endpoint Manager before version 2024 SU6 allows a remote authenticated attacker to achieve remote code execution.

Incorrect permissions assignment in the agent of Ivanti Endpoint Manager before version 2024 SU6 allows a local authenticated attacker to escalate their privileges.

An exposed dangerous method on the Core Server of Ivanti Endpoint Manager before version 2024 SU6 allows a remote authenticated attacker to leak access credentials.

OS command injection in Ivanti Virtual Traffic Manager before version 22.9r4 allows a remote authenticated attacker with admin privileges to achieve remote code execution.

External control of a file name in Ivanti Xtraction before version 2026.2 allows a remote authenticated attacker to read sensitive files and write arbitrary HTML files to a web directory, leading to information disclosure and possible client-side attacks.

A race condition in Ivanti Secure Access Client before 22.8R6 allows a locally authenticated user to escalate privileges to SYSTEM

An incorrect permission assignment for critical resource of Ivanti Secure Access Client   before 22.8R6 allows a local authenticated user to read or modify sensitive log data via write access to a shared memory section.