CVE-2026-2946

A security vulnerability has been detected in rymcu forest up to 0.0.5. Affected by this issue is the function XssUtils.replaceHtmlCode of the file src/main/java/com/rymcu/forest/util/XssUtils.java of the component Article Content/Comments/Portfolio. The manipulation leads to cross site scripting...

CVE-2026-2946

A security vulnerability has been detected in rymcu forest up to 0.0.5. Affected by this issue is the function XssUtils.replaceHtmlCode of the file src/main/java/com/rymcu/forest/util/XssUtils.java of the component Article Content/Comments/Portfolio. The manipulation leads to cross site scripting...

CVE-2026-2946

CVE-2026-2946 affects rymcu forest up to version 0.0.5. The vulnerability is in the function XssUtils.replaceHtmlCode (src/main/java/com/rymcu/forest/util/XssUtils.java) of the Article Content/Comments/Portfolio component, enabling cross-site scripting. The issue enables remote exploitation and t...

CVE-2026-2946 rymcu forest Article Content/Comments/Portfolio XssUtils.java XssUtils.replaceHtmlCode cross site scripting

A security vulnerability has been detected in rymcu forest up to 0.0.5. Affected by this issue is the function XssUtils.replaceHtmlCode of the file src/main/java/com/rymcu/forest/util/XssUtils.java of the component Article Content/Comments/Portfolio. The manipulation leads to cross site scripting...

CVE-2026-2946

A security vulnerability has been detected in rymcu forest up to 0.0.5. Affected by this issue is the function XssUtils.replaceHtmlCode of the file src/main/java/com/rymcu/forest/util/XssUtils.java of the component Article Content/Comments/Portfolio. The manipulation leads to cross site scripting...

CVE-2026-2946: Improper Neutralization of Input During Web Page Generation

A security vulnerability has been detected in rymcu forest up to 0.0.5. Affected by this issue is the function XssUtils.replaceHtmlCode of the file src/main/java/com/rymcu/forest/util/XssUtils.java of the component Article Content/Comments/Portfolio. The manipulation leads to cross site scripting...

CVE-2026-2947: Improper Neutralization of Input During Web Page Generation

A vulnerability was detected in rymcu forest up to 0.0.5. This affects the function updateUserInfo of the file - src/main/java/com/rymcu/forest/web/api/user/UserInfoController.java of the component User Profile Handler. The manipulation results in cross site scripting. The attack can be executed...

PT-2026-21431

Name of the Vulnerable Software and Affected Versions rymcu forest versions prior to 0.0.6 Description A security issue exists in rymcu forest up to version 0.0.5. The XssUtils.replaceHtmlCode function within the src/main/java/com/rymcu/forest/util/XssUtils.java file, part of the Article...

forest 代码注入漏洞

Forest is a modern knowledge community backend project developed by RYMCU. It is implemented using SpringBoot, Shiro, MyBatis, JWT, and Redis. Versions of Forest 0.0.5 and earlier have a code injection vulnerability. This vulnerability stems from incorrect operations in the updateUserInfo functio...

forest 代码注入漏洞

Forest is a modern knowledge community backend project developed by RYMCU. It is implemented using SpringBoot, Shiro, MyBatis, JWT, and Redis. Versions of Forest 0.0.5 and earlier have a code injection vulnerability. This vulnerability stems from incorrect operations on the XssUtils.replaceHtmlCo...

PT-2026-21450

Name of the Vulnerable Software and Affected Versions rymcu forest versions up to 0.0.5 Description A cross-site scripting issue exists in rymcu forest. The issue is located in the updateUserInfo function within the src/main/java/com/rymcu/forest/web/api/user/UserInfoController.java file of the...

Empirical Evaluation of SMOTE in Android Malware Detection with Machine Learning: Challenges and Performance in CICMalDroid 2020

Malware, malicious software designed to damage computer systems and perpetrate scams, is proliferating at an alarming rate, with thousands of new threats emerging daily. Android devices, prevalent in smartphones, smartwatches, tablets, and IoTs, represent a vast attack surface, making malware...

Malware Detection Based on API Calls: A Reproducibility Study

This study independently reproduces the malware detection methodology presented by Felli cious et al. 7, which employs order-invariant API call frequency analysis using Random Forest classification. We utilized the original public dataset 250,533 training samples, 83,511 test samples and replicat...

Memory-Based Malware Detection under Limited Data Conditions: A Comparative Evaluation of TabPFN and Ensemble Models

Artificial intelligence and machine learning have significantly advanced malware research by enabling automated threat detection and behavior analysis. However, the availability of exploitable data is limited, due to the absence of large datasets with real-world data. Despite the progress of AI i...

V-APF

V-APF 是一款机器学习驱动的自动化 Web 安全检测框架。通过对 Web 页面在“基线请求 vs. 探测请求”间的语义指纹差异进行量化，结合随机森林 Random Forest模型，自动识别 SQLi / XSS 等漏洞并生成报告。...

Decision-Aware Trust Signal Alignment for SOC Alert Triage

Detection systems that utilize machine learning are progressively implemented at Security Operations Centers SOCs to help an analyst to filter through high volumes of security alerts. Practically, such systems tend to reveal probabilistic results or confidence scores which are ill-calibrated and...

Towards Eco Friendly Cybersecurity: Machine Learning Based Anomaly Detection with Carbon and Energy Metrics

The rising energy footprint of artificial intelligence has become a measurable component of US data center emissions, yet cybersecurity research seldom considers its environmental cost. This study introduces an eco aware anomaly detection framework that unifies machine learning based network...

Hybrid Ensemble Method for Detecting Cyber-Attacks in Water Distribution Systems Using the BATADAL Dataset

The cybersecurity of Industrial Control Systems that manage critical infrastructure such as Water Distribution Systems has become increasingly important as digital connectivity expands. BATADAL benchmark data is a good source of testing intrusion detection techniques, but it presents several...

PT-2025-49943

CVE-2025-67569 Missing Authorization vulnerability in scriptsbundle AdForest adforest allows Exploiting Incorrectly Configured Access Control Security Levels.This issue affects AdFo… https://t.co/690H9QRGac...

A Comprehensive Study of Supervised Machine Learning Models for Zero-Day Attack Detection: Analyzing Performance on Imbalanced Data

Among the various types of cyberattacks, identifying zero-day attacks is problematic because they are unknown to security systems as their pattern and characteristics do not match known blacklisted attacks. There are many Machine Learning ML models designed to analyze and detect network attacks,...