509 matches found
MAL-2025-17347 Malicious code in com.microsoft.spatialaudio.spatializer.unity (npm)
The package com.microsoft.spatialaudio.spatializer.unity was found to contain malicious code...
Malicious code in com.microsoft.spatialaudio.spatializer.unity (npm)
The package com.microsoft.spatialaudio.spatializer.unity was found to contain malicious code...
Malicious code in com.microsoft.azure.spatial-anchors-sdk.windows (npm)
The package com.microsoft.azure.spatial-anchors-sdk.windows was found to contain malicious code...
Malicious code in com.microsoft.azure.spatial-anchors-sdk.ios (npm)
The package com.microsoft.azure.spatial-anchors-sdk.ios was found to contain malicious code...
MAL-2025-17327 Malicious code in com.microsoft.azure.spatial-anchors-sdk.windows (npm)
The package com.microsoft.azure.spatial-anchors-sdk.windows was found to contain malicious code...
CVE-2025-50690
A Cross-Site Scripting (XSS) vulnerability exists in SpatialReference.org (OSGeo/spatialreference.org) versions prior to 2025-05-17 (commit 2120adfa17ddd535bd0f539e6c4988fa3a2cb491). The flaw is caused by the improper handling of user input within the search query parameter . An unauthenticated a...
HumanSAM: Classifying Human-Centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly
Numerous synthesized videos from generative models, especially human-centric ones that simulate realistic human actions, pose significant threats to human information security and authenticity. While progress has been made in binary forgery video detection, the lack of fine-grained understanding ...
3S-Attack: Spatial, Spectral and Semantic Invisible Backdoor Attack against DNN Models
Backdoor attacks involve either poisoning the training data or directly modifying the model in order to implant a hidden behavior, that causes the model to misclassify inputs when a specific trigger is present. During inference, the model maintains high accuracy on benign samples but misclassifie...
Deep Spatial Neural Net Models with Functional Predictors: Application in Large-Scale Crop Yield Prediction
Accurate prediction of crop yield is critical for supporting food security, agricultural planning, and economic decision-making. However, yield forecasting remains a significant challenge due to the complex and nonlinear relationships between weather variables and crop production, as well as...
EVA-S2PMLP: Secure and Scalable Two-Party MLP via Spatial Transformation
Whitepaper called EVA-S2PMLP: Secure and Scalable Two-Party MLP via Spatial Transformation...
Movable Antennas Meet Low-Altitude Wireless Networks: Fundamentals, Opportunities, and Future Directions
With the rapid development of low-altitude applications, there is an increasing demand for low-altitude wireless networks LAWNs to simultaneously achieve high-rate communication, precise sensing, and reliable control in the low-altitude airspace. In this paper, we first present a typical system...
Linux kernel 安全漏洞
Linux kernel is the kernel used by Linux, the open source operating system of the Linux Foundation in the United States. A security vulnerability exists in the Linux kernel that stems from a corrupted spatial cache and a potential double allocation problem...
GaussMarker: Robust Dual-Domain Watermark for Diffusion Models
As Diffusion Models DM generate increasingly realistic images, related issues such as copyright and misuse have become a growing concern. Watermarking is one of the promising solutions. Existing methods inject the watermark into the single-domain of initial Gaussian noise for generation, which...
TooBadRL: Trigger Optimization to Boost Effectiveness of Backdoor Attacks on Deep Reinforcement Learning
Deep reinforcement learning DRL has achieved remarkable success in a wide range of sequential decision-making domains, including robotics, healthcare, smart grids, and finance. Recent research demonstrates that attackers can efficiently exploit system vulnerabilities during the training phase to...
Safeguarding Multimodal Knowledge Copyright in the RAG-As-A-Service Environment
As Retrieval-Augmented Generation RAG evolves into service-oriented platforms Rag-as-a-Service with shared knowledge bases, protecting the copyright of contributed data becomes essential. Existing watermarking methods in RAG focus solely on textual knowledge, leaving image knowledge unprotected. ...
SAGE: Exploring the Boundaries of Unsafe Concept Domain with Semantic-Augment Erasing
Diffusion models DMs have achieved significant progress in text-to-image generation. However, the inevitable inclusion of sensitive information during pre-training poses safety risks, such as unsafe content generation and copyright infringement. Concept erasing finetunes weights to unlearn...
CSVAR: Enhancing Visual Privacy in Federated Learning Via Adaptive Shuffling against Overfitting
Although federated learning preserves training data within local privacy domains, the aggregated model parameters may still reveal private characteristics. This vulnerability stems from clients' limited training data, which predisposes models to overfitting. Such overfitting enables models to...
The Windows Registry Adventure #8: Practical exploitation of hive memory corruption
Posted by Mateusz Jurczyk, Google Project Zero In the previous blog post, we focused on the general security analysis of the registry and how to effectively approach finding vulnerabilities in it. Here, we will direct our attention to the exploitation of hive-based memory corruption bugs, i.e.,...
