Multi-Agent Honeypot-Based Request-Response Context Dataset for Improved SQL Injection Detection Performance

SQL injection remains a major threat to web applications, as existing defenses often fail against obfuscation and evolving attacks because of neglecting the request-response context. This paper presents a context-enriched SQL injection detection framework, focusing on constructing a high-quality...

How the Graph Construction Technique Shapes Performance in IoT Botnet Detection

The increasing incidence of IoT-based botnet attacks has driven interest in advanced learning models for detection. Recent efforts have focused on leveraging attention mechanisms to model long-range feature dependencies and Graph Neural Networks GNNs to capture relationships between data instance...

Quantifying Catastrophic Forgetting in IoT Intrusion Detection Systems

Distribution shifts in attack patterns within RPL-based IoT networks pose a critical threat to the reliability and security of large-scale connected systems. Intrusion Detection Systems IDS trained on static datasets often fail to generalize to unseen threats and suffer from catastrophic forgetti...

BIT-SUPERSET-2026-23982 Apache Superset: Improper Authorization in Dataset Creation Allows Access Control Bypass

An Improper Authorization vulnerability exists in Apache Superset that allows a low-privileged user to bypass data access controls. When creating a dataset, Superset enforces permission checks to prevent users from querying unauthorized data. However, an authenticated attacker with permissions to...

CVE-2026-23982

An Improper Authorization vulnerability exists in Apache Superset that allows a low-privileged user to bypass data access controls. When creating a dataset, Superset enforces permission checks to prevent users from querying unauthorized data. However, an authenticated attacker with permissions to...

GHSA-3M2G-V7JF-7FXC Apache Superset Improper Authorization allows low-privileged users to bypass access controls

An Improper Authorization vulnerability exists in Apache Superset that allows a low-privileged user to bypass data access controls. When creating a dataset, Superset enforces permission checks to prevent users from querying unauthorized data. However, an authenticated attacker with permissions to...

Apache Superset Improper Authorization allows low-privileged users to bypass access controls

An Improper Authorization vulnerability exists in Apache Superset that allows a low-privileged user to bypass data access controls. When creating a dataset, Superset enforces permission checks to prevent users from querying unauthorized data. However, an authenticated attacker with permissions to...

Incorrect Authorization

Overview apache-superset is a modern, enterprise-ready business intelligence web application. Affected versions of this package are vulnerable to Incorrect Authorization during the dataset creation process. An attacker can gain unauthorized access to restricted data by overwriting the SQL query o...

CVE-2026-23982

An Improper Authorization vulnerability exists in Apache Superset that allows a low-privileged user to bypass data access controls. When creating a dataset, Superset enforces permission checks to prevent users from querying unauthorized data. However, an authenticated attacker with permissions to...

CVE-2026-23982

CVE-2026-23982 describes an Improper Authorization in Apache Superset where a low-privilege user can bypass data access controls during dataset creation by overwriting the SQL query of an existing dataset. Affected: Apache Superset

CVE-2026-23982 Apache Superset: Improper Authorization in Dataset Creation Allows Access Control Bypass

An Improper Authorization vulnerability exists in Apache Superset that allows a low-privileged user to bypass data access controls. When creating a dataset, Superset enforces permission checks to prevent users from querying unauthorized data. However, an authenticated attacker with permissions to...

CVE-2026-23982 Apache Superset: Improper Authorization in Dataset Creation Allows Access Control Bypass

An Improper Authorization vulnerability exists in Apache Superset that allows a low-privileged user to bypass data access controls. When creating a dataset, Superset enforces permission checks to prevent users from querying unauthorized data. However, an authenticated attacker with permissions to...

EUVD-2026-8476

An Improper Authorization vulnerability exists in Apache Superset that allows a low-privileged user to bypass data access controls. When creating a dataset, Superset enforces permission checks to prevent users from querying unauthorized data. However, an authenticated attacker with permissions to...

CVE-2026-23982 Apache Superset: Improper Authorization in Dataset Creation Allows Access Control Bypass

An Improper Authorization vulnerability exists in Apache Superset that allows a low-privileged user to bypass data access controls. When creating a dataset, Superset enforces permission checks to prevent users from querying unauthorized data. However, an authenticated attacker with permissions to...

PT-2026-21680

Name of the Vulnerable Software and Affected Versions Apache Superset versions prior to 6.0.0 Description An improper authorization issue exists in Apache Superset that allows a low-privileged user to bypass data access controls. Specifically, an authenticated attacker with permissions to write...

SafePickle: Robust and Generic ML Detection of Malicious Pickle-Based ML Models

Model repositories such as Hugging Face increasingly distribute machine learning artifacts serialized with Python's pickle format, exposing users to remote code execution RCE risks during model loading. Recent defenses, such as PickleBall, rely on per-library policy synthesis that requires comple...

Evaluating the Reliability of Digital Forensic Evidence Discovered by Large Language Model: A Case Study

The growing reliance on AI-identified digital evidence raises significant concerns about its reliability, particularly as large language models LLMs are increasingly integrated into forensic investigations. This paper proposes a structured framework that automates forensic artifact extraction,...

GHSA-QV8J-HGPC-VRQ8 Google Cloud Vertex AI SDK affected by Stored Cross-Site Scripting (XSS)

Stored Cross-Site Scripting XSS in the genai/evalsvisualization component of Google Cloud Vertex AI SDK google-cloud-aiplatform versions from 1.98.0 up to but not including 1.131.0 allows an unauthenticated remote attacker to execute arbitrary JavaScript in a victim's Jupyter or Colab environment...

CVE-2026-2472

Stored Cross-Site Scripting XSS in the genai/evalsvisualization component of Google Cloud Vertex AI SDK google-cloud-aiplatform versions from 1.98.0 up to but not including 1.131.0 allows an unauthenticated remote attacker to execute arbitrary JavaScript in a victim's Jupyter or Colab environment...

CVE-2026-2472

CVE-2026-2472 concerns Google Cloud Vertex AI SDK (google-cloud-aiplatform). The vulnerability resides in the _genai/_evals_visualization component and affects versions from 1.98.0 up to, but not including, 1.131.0. It enables a stored XSS where an unauthenticated remote attacker can inject scrip...