CVE-2025-5213 projectworlds Responsive E-Learning System delete_file.php sql injection

A vulnerability was found in projectworlds Responsive E-Learning System 1.0. It has been declared as critical. Affected by this vulnerability is an unknown functionality of the file /admin/deletefile.php. The manipulation of the argument ID leads to sql injection. The attack can be launched...

CVE-2025-5213

CVE-2025-5213 affects projectworlds Responsive E-Learning System 1.0. The vulnerability is an SQL injection in an unknown functionality of the file /admin/delete_file.php caused by improper handling of the ID argument. It can be exploited remotely and the exploit has been disclosed publicly. Impa...

Malicious code in ml-preprocessing (npm)

--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 449fa18004b9f5016f86ea6f5c97358b4ca5263d4649325b946379ca51610f63 Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...

Zero-Trust Foundation Models: a New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things

This paper focuses on Zero-Trust Foundation Models ZTFMs, a novel paradigm that embeds zero-trust security principles into the lifecycle of foundation models FMs for Internet of Things IoT systems. By integrating core tenets, such as continuous verification, least privilege access LPA, data...

Projectworlds Responsive E-Learning System Security Vulnerabilities

Projectworlds Responsive E-Learning System is a responsive e-learning system from Projectworlds India. A security vulnerability exists in Projectworlds Responsive E-Learning System version 1.0, which stems from SQL injection due to incorrect manipulation of the parameter ID in the file...

TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks

Verification of the integrity of deep learning inference is crucial for understanding whether a model is being applied correctly. However, such verification typically requires access to model weights and potentially sensitive or private training data. So-called Zero-knowledge Succinct...

MultiPhishGuard: an LLM-Based Multi-Agent System for Phishing Email Detection

Phishing email detection faces critical challenges from evolving adversarial tactics and heterogeneous attack patterns. Traditional detection methods, such as rule-based filters and denylists, often struggle to keep pace with these evolving tactics, leading to false negatives and compromised...

Engineering Trustworthy Machine-Learning Operations with Zero-Knowledge Proofs

As Artificial Intelligence AI systems, particularly those based on machine learning ML, become integral to high-stakes applications, their probabilistic and opaque nature poses significant challenges to traditional verification and validation methods. These challenges are exacerbated in regulated...

Efficient and Stealthy Jailbreak Attacks Via Adversarial Prompt Distillation from LLMs to SLMs

Attacks on large language models LLMs in jailbreaking scenarios raise many security and ethical issues. Current jailbreak attack methods face problems such as low efficiency, high computational cost, and poor cross-model adaptability and versatility, which make it difficult to cope with the rapid...

Language of Network: a Generative Pre-Trained Model for Encrypted Traffic Comprehension

The increasing demand for privacy protection and security considerations leads to a significant rise in the proportion of encrypted network traffic. Since traffic content becomes unrecognizable after encryption, accurate analysis is challenging, making it difficult to classify applications and...

PT-2025-22942 · Unknown · Projectworlds Responsive E-Learning System

Name of the Vulnerable Software and Affected Versions: projectworlds Responsive E-Learning System version 1.0 Description: A critical issue has been identified in the system, affecting an unknown functionality of the file /admin/delete file.php. The manipulation of the ID argument leads to SQL...

Evaluating Query Efficiency and Accuracy of Transfer Learning-Based Model Extraction Attack in Federated Learning

Federated Learning FL is a collaborative learning framework designed to protect client data, yet it remains highly vulnerable to Intellectual Property IP threats. Model extraction ME attacks pose a significant risk to Machine Learning as a Service MLaaS platforms, enabling attackers to replicate...

RADEP: a Resilient Adaptive Defense Framework against Model Extraction Attacks

Machine Learning as a Service MLaaS enables users to leverage powerful machine learning models through cloud-based APIs, offering scalability and ease of deployment. However, these services are vulnerable to model extraction attacks, where adversaries repeatedly query the application programming...

ALRPHFS: Adversarially Learned Risk Patterns with Hierarchical Fast \& Slow Reasoning for Robust Agent Defense

LLM Agents are becoming central to intelligent systems. However, their deployment raises serious safety concerns. Existing defenses largely rely on "Safety Checks", which struggle to capture the complex semantic risks posed by harmful user inputs or unsafe agent behaviors - creating a significant...

Toward Malicious Clients Detection in Federated Learning

Federated learning FL enables multiple clients to collaboratively train a global machine learning model without sharing their raw data. However, the decentralized nature of FL introduces vulnerabilities, particularly to poisoning attacks, where malicious clients manipulate their local models to...

CVE-2025-47942

The Open edX Platform is a learning management platform. Prior to commit 6740e75c0fdc7ba095baf88e9f5e4f3e15cfd8ba, edxapp has no built-in protection against downloading the pythonlib.zip asset from courses, which is a concern since it often contains custom grading code or answers to course...

CVE-2024-49361

ACON is a widely-used library of tools for machine learning that focuses on adaptive correlation optimization. A potential vulnerability has been identified in the input validation process, which could lead to arbitrary code execution if exploited. This issue could allow an attacker to submit...

CVE-2024-48509

Learning with Texts LWT 2.0.3 is vulnerable to SQL Injection. This occurs when the application fails to properly sanitize user inputs, allowing attackers to manipulate SQL queries by injecting malicious SQL statements into URL parameters. By exploiting this vulnerability, an attacker could gain...

CVE-2024-28198

OpenOlat is an open source web-based e-learning platform for teaching, learning, assessment and communication. By manually manipulating http requests when using the draw.io integration it is possible to read arbitrary files as the configured system user and SSRF. The problem is fixed in version...

CVE-2024-21671

The vantage6 technology enables to manage and deploy privacy enhancing technologies like Federated Learning FL and Multi-Party Computation MPC. It is possible to find out usernames from the response time of login requests. This could aid attackers in credential attacks. Version 4.2.0 patches this...