CVE-2025-10687: Improper Neutralization of Special Elements used in an SQL Command

A vulnerability was found in SourceCodester Responsive E-Learning System 1.0. This affects an unknown part of the file /admin/addteacher.php. The manipulation of the argument Username results in sql injection. It is possible to launch the attack remotely. The exploit has been made public and coul...

CVE-2025-10671: Use of Insufficiently Random Values

A vulnerability has been found in youth-is-as-pale-as-poetry e-learning 1.0. Impacted is the function encryptSecret of the file e-learning-master\exam-api\src\main\java\com\yf\exam\ability\shiro\jwt\JwtUtils.java of the component JWT Token Handler. The manipulation leads to insufficiently random...

PT-2025-38472

Name of the Vulnerable Software and Affected Versions SourceCodester Responsive E-Learning System version 1.0 Description A SQL injection issue exists in SourceCodester Responsive E-Learning System 1.0. The Username parameter in the /admin/add teacher.php file is susceptible to manipulation,...

PT-2025-38404

Name of the Vulnerable Software and Affected Versions youth-is-as-pale-as-poetry e-learning version 1.0 Description A vulnerability exists due to insufficiently random values generated by the encryptSecret function within the JWT Token Handler component. The vulnerable file is...

Hybrid Deep Learning-Federated Learning Powered Intrusion Detection System for IoT/5G Advanced Edge Computing Network

The exponential expansion of IoT and 5G-Advanced applications has enlarged the attack surface for DDoS, malware, and zero-day intrusions. We propose an intrusion detection system that fuses a convolutional neural network CNN, a bidirectional LSTM BiLSTM, and an autoencoder AE bottleneck within a...

E-learning security feature vulnerabilities

e-learning is an exam system for youth-is-as-pale-as-poetry individual developers. A security feature issue vulnerability exists in e-learning version 1.0, which stems from insufficient generation of random values by the encryptSecret function in the JwtUtils.java file in the JWT Token Handler...

CVE-2025-59415

Frappe Learning is a learning system that helps users structure their content. In versions 2.34.1 and below, there is a security vulnerability in Frappe Learning where the system did not adequately sanitize the content uploaded in the profile bio. Malicious SVG files could be used to execute...

CVE-2025-59415

CVE-2025-59415 affects Frappe Learning, versions 2.34.1 and earlier, where profile bio content wasn’t properly sanitized. This allows malicious SVGs to execute scripts in other users’ contexts, per multiple sources. The vulnerability arises from inadequate content sanitization in profile bios. Re...

CVE-2025-59415

Frappe Learning is a learning system that helps users structure their content. In versions 2.34.1 and below, there is a security vulnerability in Frappe Learning where the system did not adequately sanitize the content uploaded in the profile bio. Malicious SVG files could be used to execute...

CVE-2025-59415 Frappe Learning vulnerable to Malicious Content upload via Profile bio field

Frappe Learning is a learning system that helps users structure their content. In versions 2.34.1 and below, there is a security vulnerability in Frappe Learning where the system did not adequately sanitize the content uploaded in the profile bio. Malicious SVG files could be used to execute...

CVE-2025-59415 Frappe Learning vulnerable to Malicious Content upload via Profile bio field

Frappe Learning is a learning system that helps users structure their content. In versions 2.34.1 and below, there is a security vulnerability in Frappe Learning where the system did not adequately sanitize the content uploaded in the profile bio. Malicious SVG files could be used to execute...

CVE-2025-59415 Frappe Learning vulnerable to Malicious Content upload via Profile bio field

Frappe Learning is a learning system that helps users structure their content. In versions 2.34.1 and below, there is a security vulnerability in Frappe Learning where the system did not adequately sanitize the content uploaded in the profile bio. Malicious SVG files could be used to execute...

PT-2025-38279

Name of the Vulnerable Software and Affected Versions: Frappe Learning versions 2.34.1 and below Description: Frappe Learning does not adequately sanitize content uploaded in the profile bio. This allows for the execution of arbitrary scripts in the context of other users through malicious SVG...

CVE-2025-59415: Improper Neutralization of Input During Web Page Generation

Frappe Learning is a learning system that helps users structure their content. In versions 2.34.1 and below, there is a security vulnerability in Frappe Learning where the system did not adequately sanitize the content uploaded in the profile bio. Malicious SVG files could be used to execute...

LLM Jailbreak Detection for (Almost) Free!

Large language models LLMs enhance security through alignment when widely used, but remain susceptible to jailbreak attacks capable of producing inappropriate content. Jailbreak detection methods show promise in mitigating jailbreak attacks through the assistance of other models or multiple model...

Frappe Learning Cross-Site Scripting Vulnerabilities

Frappe Learning is an easy-to-use open source learning management system from Frappe Open Source. A cross-site scripting vulnerability exists in Frappe Learning version 2.34.1 and prior versions, which stems from not adequately cleaning up uploaded content in personal profiles, and could lead to ...

Hierarchical Deep Fusion Framework for Multi-Dimensional Facial Forgery Detection - the 2024 Global Deepfake Image Detection Challenge

The proliferation of sophisticated deepfake technology poses significant challenges to digital security and authenticity. Detecting these forgeries, especially across a wide spectrum of manipulation techniques, requires robust and generalized models. This paper introduces the Hierarchical Deep...

Time-Constrained Intelligent Adversaries for Automation Vulnerability Testing: a Multi-Robot Patrol Case Study

Simulating hostile attacks of physical autonomous systems can be a useful tool to examine their robustness to attack and inform vulnerability-aware design. In this work, we examine this through the lens of multi-robot patrol, by presenting a machine learning-based adversary model that observes...

Anomaly Detection in Industrial Control Systems Based on Cross-Domain Representation Learning

Industrial control systems ICSs are widely used in industry, and their security and stability are very important. Once the ICS is attacked, it may cause serious damage. Therefore, it is very important to detect anomalies in ICSs. ICS can monitor and manage physical devices remotely using...

An Unsupervised Learning Approach for a Reliable Profiling of Cyber Threat Actors Reported Globally Based on Complete Contextual Information of Cyber Attacks

Cyber attacks are rapidly increasing with the advancement of technology and there is no protection for our information. To prevent future cyberattacks it is critical to promptly recognize cyberattacks and establish strong defense mechanisms against them. To respond to cybersecurity threats...