CVE-2025-64408
Apache Causeway faces Java deserialization vulnerabilities that allow remote code execution (RCE) through user-controllable URL parameters.
CVSS
6.3
Medium
EPSS
11.6%
p96
KEV
—
Exploit Today
29
0-100
Published: Nov 19, 2025 · Last modified: Oct 18, 2026 · CWE-502
10.8%EPSS · 30 days11.6%
2026-10-072026-11-03
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.
CVECVSSEPSSKEVRExploitTitleMod.
CVE-2026-921909.8 CRI—
——0Quest 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-29170.6hCVE-2026-1186277.8 HIG—
——0MLflow 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-30301.12hCVE-2026-1186237.8 HIG—
——0MLflow 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-29513.12hCVE-2026-1158787.8 HIG—
——0Stanza 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 1.15.0.1dCVE-2026-115731——
——0Deserialization 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.1dCVE-2026-1208337.8 HIG3.7%
——1labbench before 0.46.1 contains a deserialization of untrusted data vulnerability in read() and read_relational() that passes any file with a .p or .pickle extension to pandas.read_pickle based on the extension alone. Attackers who supply a crafted data file or relational data archive can execute arbitrary code when a user loads it with these functions.2d