| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| In Trail of Bits fickling through 0.1.12, a pickle STACK_GLOBAL operand carrying a dotted __qualname__ (for example "Values.read_file") is resolved by pickle's find_class through _getattribute to an arbitrary attribute path rather than to a module-level function. Fickling records only the leading component of the name in its import tracking and renders the operation as a plain import (for instance, 'python -m fickling' displays it as 'from optparse import Values.read_file'), so the trailing attribute reference is never analyzed as a call. The OvertlyBadEvals analysis pass does not flag it, and check_safety() returns LIKELY_SAFE with zero findings. This allows an attacker to reach a class method that performs code execution: optparse.Values.read_file executes exec(open(filename).read(), vars), achieving arbitrary code execution when the crafted pickle is loaded through fickling.load(), which chains check_safety() into pickle.loads() as an explicit security gate. optparse is present in all current CPython 3.x releases (deprecated as of Python 3.13, not removed). This weakness is in the resolution and analysis of dotted attribute-path names, and is distinct from and independently fixable from the module-origin trust weakness tracked as CVE-2026-16760: resolving or flagging dotted attribute-path imports closes this vector while leaving the module-level trust behavior unchanged. This bypass was verified to remain present on the vendor master branch at commit d011709 as of 2026-10-30, after the vendor's October blocklist additions and a new heuristic that flags private stdlib attributes; because the public class method Values.read_file is neither blocklisted nor flagged as a private attribute, it is not addressed by those remediations. |
| The WPSyncSheets For Contact Form 7 – CF7 Google Sheets Connector & Save to Database plugin for WordPress is vulnerable to Remote Code Execution in all versions up to, and including, 1.8.0 via the 'any non-system CF7 field (e.g., your-message)' parameter parameter. This is due to insufficient sanitization of CF7 submission field values before database storage and the absence of an allowed_classes restriction on maybe_unserialize() during admin retrieval. This makes it possible for unauthenticated attackers to execute code on the server. Successful exploitation of the remote code execution gadget chain requires that a Google Sheets access token be configured in the plugin (its primary advertised feature), as this triggers autoloading of the bundled Monolog 2.10.0 library whose classes form the exploitable gadget chain; however, the underlying PHP Object Injection occurs regardless. |
| Deserialization of Untrusted Data vulnerability in Drupal Single Content Sync allows Object Injection. This issue affects Single Content Sync versions: from 0.0.0 to 1.4.19. |
| **UNSUPPORTED WHEN ASSIGNED**
JavaNativeMessageDecoder in the MINA 3.0 codec module calls ObjectInputStream.readObject() on frame bytes with no class filter, so an
application that puts it in front of an untrusted peer is open to gadget-chain RCE.
As the 3.0.0 branch is inactive, we do not plan to release a version that fixes this issue.
Users are recommended to use the latest Apache MINA 2.2.X branch. |
| IBM MQ 9.2.0.0 through 9.2.0.44 LTS, 9.3.0.0 through 9.3.0.42 LTS, 9.4.0.0 through 9.4.0.26 LTS, 9.4.0.0 through 9.4.5.1 CD, and 10.0.0.0 through 10.0.0.5 LTS and CD could allow an authenticated attacker to execute arbitrary code on consumer applications due to insecure deserialization of ObjectMessage payloads. |
| Jenkins 2.587 and earlier, LTS 2.580.1 and earlier does not restrict item types in collections after deserialization, allowing attackers with access to POST config.xml API endpoints to submit crafted `config.xml` files that can lead to, e.g., stored cross-site scripting (XSS) vulnerabilities. |
| Jenkins 2.587 and earlier, LTS 2.580.1 and earlier does not consistently enforce the restriction on deserializing objects of types marked as storing their configuration in independent top-level configuration files as nested values, allowing attackers to bypass the root element check and potentially inject nested objects. |
| Jenkins 2.587 and earlier, LTS 2.580.1 and earlier does not apply its deserialization filter to classes referenced by the `resolves-to` attribute during XStream deserialization. |
| Ultralytics load_dataset_cache_file Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Ultralytics. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.
The specific flaw exists within the load_dataset_cache_file function. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the current user. Was ZDI-CAN-30124. |
| Ultralytics torch_load Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Ultralytics. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.
The specific flaw exists within the torch_load function. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the current user. Was ZDI-CAN-29652. |
| A JNDI Injection vulnerability has been discovered in Apache CXF's JCA integration module, which can allow for code execution, if an attacker is able to manipulate the JCA deployment descriptor (ra.xml) or runtime activation parameters. Users are recommended to upgrade to versions 4.2.2 or 4.1.7 or 3.6.12, which fixes this issue. |
| A further incomplete fix for a previous advisory CVE-2026-44417 (Untrusted JMS configuration can lead to RCE) for Apache CXF has been identified, which can allow code execution capabilities, if untrusted users are allowed to configure JMS for Apache CXF. Users are recommended to upgrade to versions 4.2.2 or 4.1.7 or 3.6.12, which fixes this issue. |
| MLflow SHAP load_explainer Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of MLflow. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.
The specific flaw exists within the loading of SHAP explainer models. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the current user. Was ZDI-CAN-30301. |
| MLflow PickleEvaluationArtifact Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of MLflow. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.
The specific flaw exists within the parsing of pickle files. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-29513. |
| In JetBrains TeamCity before 2026.1.3, 2025.11.7 unauthenticated remote code execution was possible via the agent polling protocol |
| In Splunk Enterprise versions below 9.2.2, 9.1.5, and 9.0.10 on Windows, an authenticated user could execute a specially crafted query that they could then use to serialize untrusted data. The attacker could use the query to execute arbitrary code. |
| Deserialization of untrusted data in the agent portal of Ivanti EPM before 2022 SU6, or the 2024 September update allows a remote unauthenticated attacker to achieve remote code execution. |
| Kafka UI is an Open-Source Web UI for Apache Kafka Management. Kafka UI API allows users to connect to different Kafka brokers by specifying their network address and port. As a separate feature, it also provides the ability to monitor the performance of Kafka brokers by connecting to their JMX ports. JMX is based on the RMI protocol, so it is inherently susceptible to deserialization attacks. A potential attacker can exploit this feature by connecting Kafka UI backend to its own malicious broker. This vulnerability affects the deployments where one of the following occurs: 1. dynamic.config.enabled property is set in settings. It's not enabled by default, but it's suggested to be enabled in many tutorials for Kafka UI, including its own README.md. OR 2. an attacker has access to the Kafka cluster that is being connected to Kafka UI. In this scenario the attacker can exploit this vulnerability to expand their access and execute code on Kafka UI as well. Instead of setting up a legitimate JMX port, an attacker can create an RMI listener that returns a malicious serialized object for any RMI call. In the worst case it could lead to remote code execution as Kafka UI has the required gadget chains in its classpath. This issue may lead to post-auth remote code execution. This is particularly dangerous as Kafka-UI does not have authentication enabled by default. This issue has been addressed in version 0.7.2. All users are advised to upgrade. There are no known workarounds for this vulnerability. These issues were discovered and reported by the GitHub Security lab and is also tracked as GHSL-2023-230. |
| It was discovered that a previous vulnerability was not completely fixed with SolarWinds Access Rights Manager. While some controls were implemented the researcher was able to bypass these and use a different method to exploit the vulnerability. |
| Stanza is a Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages. From 1.14.0 until 1.15.0, loading an attacker-supplied lemmatizer checkpoint can execute arbitrary code because stanza/models/lemma/trainer.py stores pos_dict as gzip-compressed pickle bytes and Trainer.load passes the decompressed stream to unrestricted pickle.loads. The outer torch.load call uses weights_only=True, but the nested bytes are treated as a primitive and are not inspected by that allowlist. The path is reachable during pipeline construction through a caller-influenced lemma_model_path, before inference begins. This issue is fixed in version 1.15.0. |
