CVE-2026-72629 Authorization Bypass Through User-Controlled Key in Kibana Leading to Cross-Space Access to Machine Learning Trained Models

Authorization Bypass Through User-Controlled Key CWE-639 in Kibana can lead to unauthorized cross-space access via Accessing Functionality Not Properly Constrained by ACLs CAPEC-1. The result is disclosure of inference output from a trained model in a different space that the user is not authoriz...

CVE-2026-72629

Authorization Bypass Through User-Controlled Key CWE-639 in Kibana can lead to unauthorized cross-space access via Accessing Functionality Not Properly Constrained by ACLs CAPEC-1. The result is disclosure of inference output from a trained model in a different space that the user is not authoriz...

CVE-2026-72642 Use of Out-of-range Pointer Offset in the Elasticsearch Machine Learning Native Inference Process

The native inference process that Elasticsearch uses to evaluate uploaded machine learning models accepts a model operation that computes a memory address from an offset supplied inside the model, without validating that the offset stays within the bounds of the underlying storage. A user with th...

CVE-2026-72642

The native inference process that Elasticsearch uses to evaluate uploaded machine learning models accepts a model operation that computes a memory address from an offset supplied inside the model, without validating that the offset stays within the bounds of the underlying storage. A user with th...

CVE-2026-72642

The CVE notes a flaw in Elasticsearch’s native ML inference where a model operation computes a memory address from an offset without bounds checking, enabling heap corruption that can crash the inference process and potentially allow arbitrary code execution within that process. Affected configur...

CVE-2026-72642 Use of Out-of-range Pointer Offset in the Elasticsearch Machine Learning Native Inference Process

The native inference process that Elasticsearch uses to evaluate uploaded machine learning models accepts a model operation that computes a memory address from an offset supplied inside the model, without validating that the offset stays within the bounds of the underlying storage. A user with th...

EUVD-2026-58287

The native inference process that Elasticsearch uses to evaluate uploaded machine learning models accepts a model operation that computes a memory address from an offset supplied inside the model, without validating that the offset stays within the bounds of the underlying storage. A user with th...

CVE-2026-72671 Missing Authorization in Kibana Leading to Unauthorized Modification of Machine Learning Trained Model Space Assignments

A Kibana Machine Learning capability that removes a saved object from the current space accepts machine learning trained models as a target, but it verifies only the privileges that apply to anomaly detection jobs and data frame analytics jobs. A user whose role grants create anomaly detection jo...

CVE-2026-72671 Missing Authorization in Kibana Leading to Unauthorized Modification of Machine Learning Trained Model Space Assignments

A Kibana Machine Learning capability that removes a saved object from the current space accepts machine learning trained models as a target, but it verifies only the privileges that apply to anomaly detection jobs and data frame analytics jobs. A user whose role grants create anomaly detection jo...

CVE-2026-72671 Missing Authorization in Kibana Leading to Unauthorized Modification of Machine Learning Trained Model Space Assignments

A Kibana Machine Learning capability that removes a saved object from the current space accepts machine learning trained models as a target, but it verifies only the privileges that apply to anomaly detection jobs and data frame analytics jobs. A user whose role grants create anomaly detection jo...

CVE-2026-72671

CVE-2026-72671 describes a missing authorization in Kibana’s Machine Learning feature that can allow an authenticated user with certain ML privileges to remove a trained model from a space without the trained-model privilege. The vulnerability affects Kibana ML capabilities that remove saved obje...

EUVD-2026-58258

A Kibana Machine Learning capability that removes a saved object from the current space accepts machine learning trained models as a target, but it verifies only the privileges that apply to anomaly detection jobs and data frame analytics jobs. A user whose role grants create anomaly detection jo...

Kibana 8.19.20 and 9.4.5 Security Update (ESA-2026-88)

Missing Authorization in Kibana Leading to Unauthorized Modification of Machine Learning Trained Model Space Assignments A Kibana Machine Learning capability that removes a saved object from the current space accepts machine learning trained models as a target, but it verifies only the privileges...

K000162902: Node.js vulnerability CVE-2026-21715

Security Advisory Description A flaw in Node.js Permission Model filesystem enforcement leaves fs.realpathSync.native without the required read permission checks, while all comparable filesystem functions correctly enforce them. As a result, code running under --permission with restricted...

PT-2026-71759

Name of the Vulnerable Software and Affected Versions Elasticsearch affected versions not specified Description The native inference process used to evaluate uploaded machine learning models fails to validate that a memory address offset supplied within the model remains within the bounds of the...

PT-2026-71751

Name of the Vulnerable Software and Affected Versions Kibana affected versions not specified Description An authorization bypass occurs due to a user-controlled key, allowing unauthorized cross-space access because functionality is not properly constrained by Access Control Lists ACLs. This issue...

PT-2026-71781

Name of the Vulnerable Software and Affected Versions Kibana affected versions not specified Description A Kibana Machine Learning capability that removes a saved object from the current space incorrectly verifies privileges when targeting machine learning trained models. It only checks for...

Concept Drift Detection and Adaptive Retraining of Malware Classification Models

Concept drift refers to changes over time in the statistical properties of data, as compared to the data that was used to train a learning model. Machine learning models for malware detection or classification are particularly susceptible to performance degradation caused by concept drift, as...

CVE-2026-72671: Missing Authorization

A Kibana Machine Learning capability that removes a saved object from the current space accepts machine learning trained models as a target, but it verifies only the privileges that apply to anomaly detection jobs and data frame analytics jobs. A user whose role grants create anomaly detection jo...

CVE-2026-72629: Authorization Bypass Through User-Controlled Key

Authorization Bypass Through User-Controlled Key CWE-639 in Kibana can lead to unauthorized cross-space access via Accessing Functionality Not Properly Constrained by ACLs CAPEC-1. The result is disclosure of inference output from a trained model in a different space that the user is not authoriz...