Vulnerabilities

With the aim of informing, warning and helping professionals with the latest security vulnerabilities in technology systems, we have made a database available for users interested in this information, which is in Spanish and includes all of the latest documented and recognised vulnerabilities.

This repository, with over 75,000 registers, is based on the information from the NVD (National Vulnerability Database) – by virtue of a partnership agreement – through which INCIBE translates the included information into Spanish.

On occasions this list will show vulnerabilities that have still not been translated, as they are added while the INCIBE team is still carrying out the translation process. The CVE (Common Vulnerabilities and Exposures) Standard for Information Security Vulnerability Names is used with the aim to support the exchange of information between different tools and databases.

All vulnerabilities collected are linked to different information sources, as well as available patches or solutions provided by manufacturers and developers. It is possible to carry out advanced searches, as there is the option to select different criteria to narrow down the results, some examples being vulnerability types, manufacturers and impact levels, among others.

Through RSS feeds or Newsletters we can be informed daily about the latest vulnerabilities added to the repository. Below there is a list, updated daily, where you can discover the latest vulnerabilities.

CVE-2026-31223

Publication date:

12/05/2026

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&#39;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&#39;s system when the file is loaded via the vulnerable method.

Severity CVSS v4.0: Pending analysis

Last modification:

13/05/2026

CVE-2026-31222

Publication date:

12/05/2026

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&#39;s system when the file is loaded via the vulnerable method.

Severity CVSS v4.0: Pending analysis

Last modification:

13/05/2026

CVE-2026-34187

Publication date:

12/05/2026

Improper Neutralization of Special Elements used in an SQL Command vulnerability allows SQL Injection via graph container parameter. This issue affects Pandora FMS: from 777 through 800

Severity CVSS v4.0: HIGH

Last modification:

14/05/2026

CVE-2026-31225

Publication date:

12/05/2026

The superduper project thru v0.10.0 contains a critical remote code execution vulnerability in its query parsing component. The _parse_op_part() function in query.py uses the unsafe eval() function to dynamically evaluate user-supplied query operands without proper sanitization or restriction. Although the function attempts to limit the execution context by providing a restricted global namespace, it does not block access to dangerous built-in functions. A remote attacker can exploit this by submitting a specially crafted query string containing Python code that imports modules (e.g., os) and executes arbitrary system commands, leading to complete compromise of the server.

Severity CVSS v4.0: Pending analysis

Last modification:

13/05/2026

CVE-2026-31226

Publication date:

12/05/2026

The TinyZero project thru commit 6652a63c57fa7e5ccde3fc9c598c7176ff15b839 (2025-58-24) contains a critical command injection vulnerability (CWE-78) in its HDFS file operation utilities. The vulnerability arises from the unsafe construction and execution of shell commands via os.system() without proper input sanitization or escaping. User-controlled input (such as file paths) is directly interpolated into shell command strings using f-strings within the _copy() function. An attacker can inject arbitrary OS commands by supplying a specially crafted path parameter through the Hydra configuration framework. This leads to remote code execution with the privileges of the user running the TinyZero training process.

Severity CVSS v4.0: Pending analysis

Last modification:

13/05/2026

CVE-2026-31228

Publication date:

12/05/2026

The Adversarial Robustness Toolbox (ART) thru 1.20.1 contains a remote code execution vulnerability in its Kubeflow component. The robustness evaluation function for PyTorch models uses the unsafe eval() function to dynamically evaluate user-supplied strings for the LossFn and Optimizer parameters without any sanitization or security restrictions. An attacker can exploit this by providing a specially crafted string that contains arbitrary Python code, which will be executed when eval() is called, leading to complete compromise of the system running the ART evaluation.

Severity CVSS v4.0: Pending analysis

Last modification:

13/05/2026

CVE-2026-31224

Publication date:

12/05/2026

The snorkel library thru v0.10.0 contains an insecure deserialization vulnerability (CWE-502) in the MultitaskClassifier.load() method of the MultitaskClassifier class. The method loads model weight 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&#39;s system when the file is loaded via the vulnerable method.

Severity CVSS v4.0: Pending analysis

Last modification:

13/05/2026

CVE-2026-31218

Publication date:

12/05/2026

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&#39;s system.

Severity CVSS v4.0: Pending analysis

Last modification:

13/05/2026

CVE-2026-31219

Publication date:

12/05/2026

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&#39;s system.

Severity CVSS v4.0: Pending analysis

Last modification:

13/05/2026

CVE-2026-31220

Publication date:

12/05/2026

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.

Severity CVSS v4.0: Pending analysis

Last modification:

13/05/2026

CVE-2026-30810

Publication date:

12/05/2026

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

Severity CVSS v4.0: HIGH

Last modification:

13/05/2026

CVE-2026-31214

Publication date:

12/05/2026

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.

Severity CVSS v4.0: Pending analysis

Last modification:

13/05/2026

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