CVE-2025-63687

The CVE-2025-63687 issue affects the rymcu forest project (commit f782e85, 2025-09-04) where the vulnerability exists in AuthorshipAspect.java’s doBefore function. This flaw could allow an authorized attacker to delete arbitrary user posts. Multiple sources (NVD, Red Hat, EUVD/ENISA, CIRCL, CNNVD...

forest 安全漏洞

forest is RYMCU open source a modern knowledge community backend project , using SpringBoot + Shiro + MyBatis + JWT + Redis implementation . A security vulnerability exists in forest version f782e85, which stems from a flaw in the doBefore function in the AuthorshipAspect.java file, which could...

sssd security update

2.9.4-5.0.2.3 - Missing ntohs to service port Orabug: 37389651 - Restore default debug level for ssscache Orabug: 32810448 2.9.4-5.3 - Resolves: RHEL-112455 - p11child currently has an infinite timeout rhel-8.10.z - Resolves: RHEL-120292 - CVE-2025-11561 sssd: SSSD default Kerberos configuration...

LLM-Based Multi-Class Attack Analysis and Mitigation Framework in IoT/IIoT Networks

The Internet of Things has expanded rapidly, transforming communication and operations across industries but also increasing the attack surface and security breaches. Artificial Intelligence plays a key role in securing IoT, enabling attack detection, attack behavior analysis, and mitigation...

Securing IoT Communications Via Anomaly Traffic Detection: Synergy of Genetic Algorithm and Ensemble Method

The rapid growth of the Internet of Things IoT has transformed industries by enabling seamless data exchange among connected devices. However, IoT networks remain vulnerable to security threats such as denial of service DoS attacks, anomalous traffic, and data manipulation due to decentralized...

Attack-Specialized Deep Learning with Ensemble Fusion for Network Anomaly Detection

The growing scale and sophistication of cyberattacks pose critical challenges to network security, particularly in detecting diverse intrusion types within imbalanced datasets. Traditional intrusion detection systems IDS often struggle to maintain high accuracy across both frequent and rare...

GNN-Enhanced Traffic Anomaly Detection for Next-Generation SDN-Enabled Consumer Electronics

Consumer electronics CE connected to the Internet of Things are susceptible to various attacks, including DDoS and web-based threats, which can compromise their functionality and facilitate remote hijacking. These vulnerabilities allow attackers to exploit CE for broader system attacks while...

EUVD-2019-1443

Malware in sbrugna...

EUVD-2008-5750

Malware in sbrugna...

EUVD-2023-56488

Malicious code in bioql PyPI...

Adaptive Deception Framework with Behavioral Analysis for Enhanced Cybersecurity Defense

This paper presents CADL Cognitive-Adaptive Deception Layer, an adaptive deception framework achieving 99.88% detection rate with 0.13% false positive rate on the CICIDS2017 dataset. The framework employs ensemble machine learning Random Forest, XGBoost, Neural Networks combined with behavioral...

go-f3 Vulnerable to Cached Justification Verification Bypass

Description A vulnerability exists in go-f3's justification verification caching mechanism where verification results are cached without properly considering the context of the message. An attacker can bypass justification verification by: 1. First submitting a valid message with a correct...

Dual-Path Phishing Detection: Integrating Transformer-Based NLP with Structural URL Analysis

Phishing emails pose a persistent and increasingly sophisticated threat, undermining email security through deceptive tactics designed to exploit both semantic and structural vulnerabilities. Traditional detection methods, often based on isolated analysis of email content or embedded URLs, fail t...

A Comparative Analysis of Ensemble-Based Machine Learning Approaches with Explainable AI for Multi-Class Intrusion Detection in Drone Networks

The growing integration of drones into civilian, commercial, and defense sectors introduces significant cybersecurity concerns, particularly with the increased risk of network-based intrusions targeting drone communication protocols. Detecting and classifying these intrusions is inherently...

Malicious code in sapphire-forest-lht755-project (npm)

The package sapphire-forest-lht755-project was found to contain malicious code...

Malicious code in star-forest-wro395-project (npm)

The package star-forest-wro395-project was found to contain malicious code...

MAL-2025-46139 Malicious code in star-forest-wro395-project (npm)

The package star-forest-wro395-project was found to contain malicious code...

MAL-2025-45956 Malicious code in sapphire-forest-lht755-project (npm)

The package sapphire-forest-lht755-project was found to contain malicious code...

Hybrid Cryptographic Monitoring System for Side-Channel Attack Detection on PYNQ SoCs

AES-128 encryption is theoretically secure but vulnerable in practical deployments due to timing and fault injection attacks on embedded systems. This work presents a lightweight dual-detection framework combining statistical thresholding and machine learning ML for real-time anomaly detection. B...

Machine Learning-Based AES Key Recovery Via Side-Channel Analysis on the ASCAD Dataset

Cryptographic algorithms like AES and RSA are widely used and they are mathematically robust and almost unbreakable but its implementation on physical devices often leak information through side channels, such as electromagnetic EM emissions, potentially compromising said theoretically secure...