| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| 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 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. |
| PyMoDAQ before 4.4.13, and pymodaq_data, pymodaq_gui, and pymodaq_utils before 5.1.15, 5.2.x before 5.2.14, and 5.3.x before 5.3.10, contain deserialization of untrusted data and eval injection vulnerabilities that allow attackers to execute arbitrary code by supplying crafted files that a user opens. Attackers can store pickled objects in HDF5 string nodes that StringARRAY.array_to_string() passes to pickle.loads() when the node is browsed or read, place Python expressions in HDF5 attributes that JsonConverter.json2object() evaluates, supply a .dock file that load_layout_state() unpickles from the Dashboard Load layout action, or embed Python expressions in XML settings files that elt_to_dict() and set_txt_from_elt() evaluate. |
| h5io before 0.2.6 contains a code injection vulnerability in read_hdf5() that allows attackers to execute arbitrary code by supplying a crafted HDF5 file. Attackers can store Python code in a node titled timezone, which _triage_read() passes to eval() with builtins reachable, name an arbitrary module in class or custom-object nodes that _import_class() imports, or place pickled objects in pd_dataframe or pd_series nodes that pandas deserializes on read. |
| 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. |
| ESPectre is a Wi-Fi motion sensing platform for ESP32. Prior to 3.0.0-rc1, Micro-ESPectre analysis tools, including tools/6_optimize_filter_params.py, tools/1_analyze_raw_data.py, and tools/10_train_ml_model.py, load NPZ datasets with NumPy pickle support enabled through micro-espectre/tools/csi_utils.py and a direct loader. A malicious dataset contributor or pull-request author can place an object-typed array in a .npz file under micro-espectre/data, causing pickle-controlled code to execute as the maintainer or developer when a documented analysis tool accesses the field. This issue is fixed in version 3.0.0-rc1. |
| 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. |
| 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. |
| Quest Foglight for Databases baseRmiServiceExporter Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Quest Foglight for Databases. Authentication is not required to exploit this vulnerability.
The specific flaw exists within the configuration of the baseRmiServiceExporter bean. The issue results from the lack of proper validation of user-supplied data prior to deserializing it. An attacker can leverage this vulnerability to execute code in the context of SYSTEM. Was ZDI-CAN-29170. |
| 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. |
| Apache Causeway faces Java deserialization vulnerabilities that allow remote code execution (RCE) through user-controllable URL parameters. These vulnerabilities affect all applications using Causeway's ViewModel functionality and can be exploited by authenticated attackers to execute arbitrary code with application privileges.
This issue affects all current versions.
Users are recommended to upgrade to version 3.5.0, which fixes the issue. |
| Deserialization of untrusted data in the report-processing code of Puppet, as used by Puppet Server, in the affected releases, allows a client that holds any CA-signed agent certificate to execute arbitrary code on the Puppet Server as its service user by submitting a report containing a crafted rich-data type via PUT request. Where the certificate authority autosigns requests without strong verification, an unauthenticated network attacker can obtain such a certificate. |
| Deserialization of Untrusted Data vulnerability in Apache Camel Camel-Jgroups component.
This issue affects Apache Camel: from 4.0.0 before 4.18.5, from 4.19.0 before 4.22.1.
JGroupsEndpoint.createExchange(Message), which CamelJGroupsReceiver calls for every message the jgroups consumer receives before the exchange is routed, set the exchange body from org.jgroups.Message.getObject(). For an ObjectMessage, which is the message type the Camel jgroups producer sends, JGroups Java-deserializes the payload through an ObjectInputStream on its own receive thread as the message arrives, and getObject() returns the resulting object. No java.io.ObjectInputFilter was applied on that path unless the deployment had set a JVM-wide serialization filter: camel-jgroups installed none, and the JGroups versions shipped with the affected releases apply none of their own, so any serializable class on the application classpath could be instantiated and its deserialization callbacks run. Unless a channel or the channelProperties option is configured, the consumer creates its channel with new JChannel(), the stock JGroups protocol stack, which multicasts over UDP without the AUTH protocol and without encryption, so any host able to reach the cluster's multicast group or bind port can join the cluster and send messages to the consumer without credentials. Such a host could send a crafted serialized object that leads to remote code execution in the Camel process when a usable deserialization gadget chain is present on the classpath, and no non-default option was required on the consumer. Because JGroups materializes the object before Camel's receiver runs, a check performed by Camel can only inspect the deserialized result and cannot stop code that runs during deserialization, so closing the issue also requires a control that applies before the payload is read, as described in the mitigation. Exploitation requires network access to the cluster's multicast group or bind port, which with the default UDP multicast transport means a host on an adjacent network, and a usable gadget chain on the classpath, which is why the severity is assessed as high rather than critical.
Users are recommended to upgrade to version 4.23.0, which fixes the issue. If users are on the 4.22.x releases stream, then they are suggested to upgrade to 4.22.1. If users are on the 4.18.x releases stream, then they are suggested to upgrade to 4.18.5. The 4.14.x releases stream and earlier, and the 4.15.x to 4.17.x and 4.19.x to 4.21.x release lines, reached end of life before this issue was resolved and will not receive a fix, so deployments on those lines must move to a supported release. |
