zombieguard

ZombieGuard ZIPアーカイブにおける構造的メタデータ回避のための防御型スキャナ。 ZombieGuardは、ZIPのローカルファイルヘッダー、セントラルディレクトリレコード、およびペイロード特性の間の矛盾を検出します。これらの矛盾は、あるパーサーにはアーカイブの内容が空または無害に見える一方で、別のパーサーはペイロードに到達できるようにするために使用される可能性があります。 制限付きZIPパーサーと小型のLightGBMモデルを組み合わせています。アーカイブの内容を抽出したり実行したりすることはありません。 !IMPORTANT...

CVE-2026-92786

A flaw was found in LightGBM. The software does not properly validate data within text models, which can be exploited by an attacker. By crafting a malicious model file, an attacker can trigger an out-of-bounds write during the SHAP prediction process. This vulnerability could lead to arbitrary...

Out-of-bounds Write

Overview Affected versions of this package are vulnerable to Out-of-bounds Write in the parsing process of text models due to insufficient validation of child and split array values. An attacker can achieve arbitrary memory writes by supplying a specially crafted model file with invalid node...

CVE-2026-92786

LightGBM through 4.7.0 fails to validate child and split array values when parsing text models, allowing attackers to write out-of-bounds memory during SHAP prediction. Attackers can craft malicious model files with invalid node references that trigger out-of-bounds writes at attacker-chosen...

CVE-2026-92786 LightGBM through 4.7.0 Out-of-Bounds Write via Crafted Model

LightGBM through 4.7.0 fails to validate child and split array values when parsing text models, allowing attackers to write out-of-bounds memory during SHAP prediction. Attackers can craft malicious model files with invalid node references that trigger out-of-bounds writes at attacker-chosen...

EUVD-2026-81049

LightGBM through 4.7.0 fails to validate child and split array values when parsing text models, allowing attackers to write out-of-bounds memory during SHAP prediction. Attackers can craft malicious model files with invalid node references that trigger out-of-bounds writes at attacker-chosen...

CVE-2026-92786 LightGBM through 4.7.0 Out-of-Bounds Write via Crafted Model

LightGBM through 4.7.0 fails to validate child and split array values when parsing text models, allowing attackers to write out-of-bounds memory during SHAP prediction. Attackers can craft malicious model files with invalid node references that trigger out-of-bounds writes at attacker-chosen...

CVE-2026-92786

LightGBM versions through 4.7.0 are affected by an out-of-bounds write vulnerability triggered during SHAP prediction (feature contribution computation). The root cause is a failure to validate child and split array values when parsing text model files. An attacker can craft a malicious model fil...

CVE-2026-92786 LightGBM through 4.7.0 Out-of-Bounds Write via Crafted Model

LightGBM through 4.7.0 fails to validate child and split array values when parsing text models, allowing attackers to write out-of-bounds memory during SHAP prediction. Attackers can craft malicious model files with invalid node references that trigger out-of-bounds writes at attacker-chosen...

CVE-2026-92786: Out-of-bounds Write

LightGBM through 4.7.0 fails to validate child and split array values when parsing text models, allowing attackers to write out-of-bounds memory during SHAP prediction. Attackers can craft malicious model files with invalid node references that trigger out-of-bounds writes at attacker-chosen...

CLSA-2026-1776904627 TuxCare security update for lightgbm (1 CVE)

TuxCare rebuilt lightgbm to address 1 CVE. Fixed in 3.3.5.post1+tuxcare...

MLFlow unsafe deserialization

Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.23.0 or newer, enabling a maliciously uploaded LightGBM scikit-learn model to run arbitrary code on an end user’s system when interacted with...

PYSEC-2026-1644 MLFlow unsafe deserialization

Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.23.0 or newer, enabling a maliciously uploaded LightGBM scikit-learn model to run arbitrary code on an end user’s system when interacted with...

EUVD-2024-1966

Malicious code in bioql PyPI...

EUVD-2024-40349

Malicious code in bioql PyPI...

Leveraging Machine Learning for Botnet Attack Detection in Edge-Computing Assisted IoT Networks

The increase of IoT devices, driven by advancements in hardware technologies, has led to widespread deployment in large-scale networks that process massive amounts of data daily. However, the reliance on Edge Computing to manage these devices has introduced significant security vulnerabilities, a...

Efficient Malware Detection with Optimized Learning on High-Dimensional Features

Malware detection using machine learning requires feature extraction from binary files, as models cannot process raw binaries directly. A common approach involves using LIEF for raw feature extraction and the EMBER vectorizer to generate 2381-dimensional feature vectors. However, the high...

Security Bulletin: IBM Maximo Application Suite - Predict Component vulnerable to Microsoft LightGBM could allow a remote attacker to execute arbitrary code on the system.

Summary Security Bulletin: IBM Maximo Application Suite - Predict Component vulnerable to Microsoft LightGBM could allow a remote attacker to execute arbitrary code on the system.. This bulletin contains information regarding the vulnerability and its fixture. Vulnerability Details...

MAL-2025-191781 Malicious code in lightgboost (PyPI)

--- -= Per source details. Do not edit below this line.=- Source: kam193 03aea882aa08832e53ccfb267fe4b95c9ea4f24ea51ceeaaa4a85557e67ce15b Packages are designed to collect basic info about the user when importing them, and have no other purpose. While they claim to do so, some packages from the sa...

LightGBM < 4.6.0 RCE

The version of the LightGBM library installed on the remote host is prior to 4.6.0. It is, therefore, affected by a remote code execution vulnerability. Note that Nessus has not tested for this issue but has instead relied only on the application's self-reported version number. %NASLMINLEVEL 8090...