Collaborative research by Microsoft and NVIDIA on real-time immunity

AI-Powered Threats Demand AI-Powered Defense While AI supports growth and innovation, it is also reshaping how organizations address faster, more adaptive security risks. AI-driven security threats, including “vibe-hacking”, are evolving faster than traditional defenses can adapt. Attackers can n...

AutoMalDesc: Large-Scale Script Analysis for Cyber Threat Research

Generating thorough natural language explanations for threat detections remains an open problem in cybersecurity research, despite significant advances in automated malware detection systems. In this work, we present AutoMalDesc, an automated static analysis summarization framework that, followin...

Adaptive Dual-Layer Web Application Firewall (ADL-WAF) Leveraging Machine Learning for Enhanced Anomaly and Threat Detection

Web Application Firewalls are crucial for protecting web applications against a wide range of cyber threats. Traditional Web Application Firewalls often struggle to effectively distinguish between malicious and legitimate traffic, leading to limited efficacy in threat detection. To overcome these...

Scalable Hierarchical AI-Blockchain Framework for Real-Time Anomaly Detection in Large-Scale Autonomous Vehicle Networks

The security of autonomous vehicle networks is facing major challenges, owing to the complexity of sensor integration, real-time performance demands, and distributed communication protocols that expose vast attack surfaces around both individual and network-wide safety. Existing security schemes...

Multi-Agent Collaborative Fuzzing with Continuous Reflection for Smart Contracts Vulnerability Detection

Fuzzing is a widely used technique for detecting vulnerabilities in smart contracts, which generates transaction sequences to explore the execution paths of smart contracts. However, existing fuzzers are falling short in detecting sophisticated vulnerabilities that require specific attack...

BackWeak: Backdooring Knowledge Distillation Simply with Weak Triggers and Fine-Tuning

Knowledge Distillation KD is essential for compressing large models, yet relying on pre-trained "teacher" models downloaded from third-party repositories introduces serious security risks -- most notably backdoor attacks. Existing KD backdoor methods are typically complex and computationally...

Retrofit: Continual Learning with Bounded Forgetting for Security Applications

Modern security analytics are increasingly powered by deep learning models, but their performance often degrades as threat landscapes evolve and data representations shift. While continual learning CL offers a promising paradigm to maintain model effectiveness, many approaches rely on full...

Adaptive Intrusion Detection for Evolving RPL IoT Attacks Using Incremental Learning

The routing protocol for low-power and lossy networks RPL has become the de facto routing standard for resource-constrained IoT systems, but its lightweight design exposes critical vulnerabilities to a wide range of routing-layer attacks such as hello flood, decreased rank, and version number...

VULPO: Context-Aware Vulnerability Detection Via On-Policy LLM Optimization

The widespread reliance on open-source software dramatically increases the risk of vulnerability exploitation, underscoring the need for effective and scalable vulnerability detection VD. Existing VD techniques, whether traditional machine learning-based or LLM-based approaches like prompt...

Data Poisoning Vulnerabilities across Healthcare AI Architectures: A Security Threat Analysis

Healthcare AI systems face major vulnerabilities to data poisoning that current defenses and regulations cannot adequately address. We analyzed eight attack scenarios in four categories: architectural attacks on convolutional neural networks, large language models, and reinforcement learning...

CVE-2025-64705

Frappe Learning is a learning system that helps users structure their content. Starting in version 2.0.0 and prior to version 2.41.0, users were able to access the submissions made by other students The issue has been fixed in version 2.41.0 by ensuring proper roles and redirecting if accessed vi...

CVE-2025-64707

Frappe Learning is a learning system that helps users structure their content. Starting in version 2.0.0 and prior to version 2.41.0, when admins revoked a role from the user, the effect was not immediate because of caching. The issue has been fixed in version 2.41.0 by ensuring the cache is...

How Worrying Are Privacy Attacks against Machine Learning?

In several jurisdictions, the regulatory framework on the release and sharing of personal data is being extended to machine learning ML. The implicit assumption is that disclosing a trained ML model entails a privacy risk for any personal data used in training comparable to directly releasing tho...

CVE-2025-64707

Frappe Learning is a learning system that helps users structure their content. Starting in version 2.0.0 and prior to version 2.41.0, when admins revoked a role from the user, the effect was not immediate because of caching. The issue has been fixed in version 2.41.0 by ensuring the cache is...

CVE-2025-64705

Frappe Learning is a learning system that helps users structure their content. Starting in version 2.0.0 and prior to version 2.41.0, users were able to access the submissions made by other students The issue has been fixed in version 2.41.0 by ensuring proper roles and redirecting if accessed vi...

CVE-2025-64707

Summary : CVE-2025-64707 affects Frappe Learning (LMS). From versions 2.0.0 up to and including 2.41.0, revoking a user’s role could be delayed in effect due to caching, meaning revoked permissions could persist briefly. This behavior has been fixed in version 2.41.0 by ensuring the cache is clea...

CVE-2025-64707 Frappe LMS revoking access did not show immediate effect as roles were cached

Frappe Learning is a learning system that helps users structure their content. Starting in version 2.0.0 and prior to version 2.41.0, when admins revoked a role from the user, the effect was not immediate because of caching. The issue has been fixed in version 2.41.0 by ensuring the cache is...

EUVD-2025-150360

Frappe Learning is a learning system that helps users structure their content. Starting in version 2.0.0 and prior to version 2.41.0, when admins revoked a role from the user, the effect was not immediate because of caching. The issue has been fixed in version 2.41.0 by ensuring the cache is...

CVE-2025-64707 Frappe LMS revoking access did not show immediate effect as roles were cached

Frappe Learning is a learning system that helps users structure their content. Starting in version 2.0.0 and prior to version 2.41.0, when admins revoked a role from the user, the effect was not immediate because of caching. The issue has been fixed in version 2.41.0 by ensuring the cache is...

CVE-2025-64705 Frappe user was able to access the submission of other students

Frappe Learning is a learning system that helps users structure their content. Starting in version 2.0.0 and prior to version 2.41.0, users were able to access the submissions made by other students The issue has been fixed in version 2.41.0 by ensuring proper roles and redirecting if accessed vi...