CVE-2026-92190
Quest Foglight for Databases baseRmiServiceExporter Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerabilit
CVSS
9.8
Crítica
EPSS
0.6%
p50
KEV
—
Exploit Today
15
0-100
Publicado: 4 de nov. de 2026 · Última mod.: 4 de nov. de 2026 · CWE-502
0.6%EPSS · 30 dias0.6%
2026-11-042026-11-05
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.
CVECVSSEPSSKEVRExploitTítuloMod.
CVE-2026-1208597.8 ALT—
——0PyMoDAQ 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.9hCVE-2026-1204997.8 ALT—
——0h5io 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.8hCVE-2026-1027397.8 ALT—
——0ESPectre 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-rc1.10hCVE-2026-1186277.8 ALT5.1%
——2MLflow 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-30301.22hCVE-2026-1186237.8 ALT31.4%
——9MLflow 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-29513.22hCVE-2026-1158787.8 ALT48.7%
——15Stanza 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 1.15.0.2d