CVE-2026-63145

Incorrect Authorization CWE-863 in Kibana can lead to integrity compromise of Machine Learning audit and notification records via Accessing Functionality Not Properly Constrained by ACLs CAPEC-1. A vulnerability exists in Kibana's Machine Learning functionality where a Machine Learning management...

CVE-2026-63261 Uncontrolled Resource Consumption in Kibana Leading to Denial of Service

Uncontrolled Resource Consumption CWE-400 in Kibana can lead to denial of service via Excessive Allocation CAPEC-130. A low-privileged authenticated user can send a specially crafted request to a Kibana machine learning feature, causing the server to exhaust available memory and become unavailabl...

CVE-2026-63261

Uncontrolled Resource Consumption CWE-400 in Kibana can lead to denial of service via Excessive Allocation CAPEC-130. A low-privileged authenticated user can send a specially crafted request to a Kibana machine learning feature, causing the server to exhaust available memory and become unavailabl...

CVE-2026-63261 Uncontrolled Resource Consumption in Kibana Leading to Denial of Service

Uncontrolled Resource Consumption CWE-400 in Kibana can lead to denial of service via Excessive Allocation CAPEC-130. A low-privileged authenticated user can send a specially crafted request to a Kibana machine learning feature, causing the server to exhaust available memory and become unavailabl...

CVE-2026-63261

CVE-2026-63261 describes an uncontrolled resource consumption (CWE-400) in Kibana, leading to denial of service via excessive memory allocation. The issue is triggered by a low-privileged authenticated user sending specially crafted requests to the Kibana machine learning feature, which can exhau...

Kibana 8.19.19, 9.3.8, 9.4.4 Security Update (ESA-2026-72)

Uncontrolled Resource Consumption in Kibana Leading to Denial of Service Uncontrolled Resource Consumption CWE-400 in Kibana can lead to denial of service via Excessive Allocation CAPEC-130. A low-privileged authenticated user can send a specially crafted request to a Kibana machine learning...

CVE-2026-63145

Kibana Machine Learning (ML) functionality is affected by an Incorrect Authorization (CWE-863) vulnerability. A management endpoint performs only a coarse privilege check and does not verify that the requesting user has access to the specific ML job or notification resources referenced in the req...

CVE-2026-63145 Incorrect Authorization in Kibana Leading to Machine Learning Audit Log Integrity Compromise

Incorrect Authorization CWE-863 in Kibana can lead to integrity compromise of Machine Learning audit and notification records via Accessing Functionality Not Properly Constrained by ACLs CAPEC-1. A vulnerability exists in Kibana's Machine Learning functionality where a Machine Learning management...

CVE-2026-63145

Incorrect Authorization CWE-863 in Kibana can lead to integrity compromise of Machine Learning audit and notification records via Accessing Functionality Not Properly Constrained by ACLs CAPEC-1. A vulnerability exists in Kibana's Machine Learning functionality where a Machine Learning management...

CVE-2026-63145 Incorrect Authorization in Kibana Leading to Machine Learning Audit Log Integrity Compromise

Incorrect Authorization CWE-863 in Kibana can lead to integrity compromise of Machine Learning audit and notification records via Accessing Functionality Not Properly Constrained by ACLs CAPEC-1. A vulnerability exists in Kibana's Machine Learning functionality where a Machine Learning management...

CVE-2026-63145 Incorrect Authorization in Kibana Leading to Machine Learning Audit Log Integrity Compromise

Incorrect Authorization CWE-863 in Kibana can lead to integrity compromise of Machine Learning audit and notification records via Accessing Functionality Not Properly Constrained by ACLs CAPEC-1. A vulnerability exists in Kibana's Machine Learning functionality where a Machine Learning management...

Kibana 8.19.19, 9.3.8, 9.4.4 Security Update (ESA-2026-69)

Incorrect Authorization in Kibana Leading to Machine Learning Audit Log Integrity Compromise Incorrect Authorization CWE-863 in Kibana can lead to integrity compromise of Machine Learning audit and notification records via Accessing Functionality Not Properly Constrained by ACLs CAPEC-1. A...

PT-2026-63266

Name of the Vulnerable Software and Affected Versions Kibana affected versions not specified Description Uncontrolled Resource Consumption in Kibana can lead to a denial of service through excessive allocation. A low-privileged authenticated user can send a specially crafted request to a machine...

CVE-2026-63261: Uncontrolled Resource Consumption

Uncontrolled Resource Consumption CWE-400 in Kibana can lead to denial of service via Excessive Allocation CAPEC-130. A low-privileged authenticated user can send a specially crafted request to a Kibana machine learning feature, causing the server to exhaust available memory and become unavailabl...

CVE-2026-63145: Incorrect Authorization

Incorrect Authorization CWE-863 in Kibana can lead to integrity compromise of Machine Learning audit and notification records via Accessing Functionality Not Properly Constrained by ACLs CAPEC-1. A vulnerability exists in Kibana's Machine Learning functionality where a Machine Learning management...

PT-2026-63263

Name of the Vulnerable Software and Affected Versions Kibana affected versions not specified Description An incorrect authorization issue exists in the Machine Learning functionality. A management endpoint performs an insufficient authorization check by validating only a coarse privilege level...

Malicious code in @azure-lab-services/ml-ts (npm)

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(A)ISpy: Parasitic Trojans for Machine Learning Infrastructure

Modern machine learning ML pipelines depend heavily on third party libraries for graph compilation and hardware acceleration. While current practices audit data and model artifacts or rely on file integrity checks, the execution environment remains implicitly trusted. This blind spot enables acti...

Towards Quantum Machine Learning for Assessing the Resilience of Post-Quantum Cryptography

The potential capabilities of quantum computers motivated the development of cryptographic protocols suitable for securing communication against adversaries with access to large fault-tolerant quantum computers. However, even though current quantum computers are limited in terms of size and...

JLSEC-2026-748 The ML-KEM ARM64 NEON ciphertext comparison only compares half of the input, breaking the...

The ML-KEM ARM64 NEON ciphertext comparison only compares half of the input, breaking the Fujisaki-Okamoto transform's implicit rejection and weakening IND-CCA2 security on that code path. The constant-time comparison effectively ignored part of the re-encrypted ciphertext, so a decapsulating par...