JLSEC-2025-131 FFmpeg v.n6.1-3-g466799d4f5 allows a heap-based buffer overflow via the `ff_gaussian_blur_8`...

FFmpeg v.n6.1-3-g466799d4f5 allows a heap-based buffer overflow via the ffgaussianblur8 function in libavfilter/edgetemplate.c:116:5 component...

Targeted Pooled Latent-Space Steganalysis Applied to Generative Steganography, with a Fix

Steganographic schemes dedicated to generated images modify the seed vector in the latent space to embed a message, whereas most steganalysis methods attempt to detect the embedding in the image space. This paper proposes to perform steganalysis in the latent space by modeling the statistical...

EUVD-2020-14791

Malware in sbrugna...

EUVD-2020-14798

Malware in sbrugna...

Unity Linux 20.1050e / 20.1060e / 20.1070e Security Update: ffmpeg (UTSA-2025-936106)

The Unity Linux 20 host has a package installed that is affected by a vulnerability as referenced in the UTSA-2025-936106 advisory. A heap-based Buffer Overflow vulnerability exists in gaussianblur at libavfilter/vfedgedetect.c, which might lead to memory corruption and other potential...

Unity Linux 20.1050e / 20.1060e / 20.1070e Security Update: ffmpeg (UTSA-2025-936104)

The Unity Linux 20 host has a package installed that is affected by a vulnerability as referenced in the UTSA-2025-936104 advisory. A heap-based Buffer Overflow vulnerability exists FFmpeg 4.2 at libavfilter/vfedgedetect.c in gaussianblur, which might lead to memory corruption and other potential...

MAL-2025-47213 Malicious code in ts-gaussian (npm)

--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 28976f40d9c1e8c05d8a074ce4984cedef949d2d116e5131b5db71e55cd43695 Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...

Malicious code in ts-gaussian (npm)

--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 28976f40d9c1e8c05d8a074ce4984cedef949d2d116e5131b5db71e55cd43695 Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...

SREC: Encrypted Semantic Super-Resolution Enhanced Communication

Semantic communication SemCom, as a typical paradigm of deep integration between artificial intelligence AI and communication technology, significantly improves communication efficiency and resource utilization efficiency. However, the security issues of SemCom are becoming increasingly prominent...

Linux Distros Unpatched Vulnerability : CVE-2020-22025

The Linux/Unix host has one or more packages installed that are impacted by a vulnerability without a vendor supplied patch available. - A heap-based Buffer Overflow vulnerability exists in gaussianblur at libavfilter/vfedgedetect.c, which might lead to memory corruption and other potential...

Linux Distros Unpatched Vulnerability : CVE-2020-22032

The Linux/Unix host has one or more packages installed that are impacted by a vulnerability without a vendor supplied patch available. - A heap-based Buffer Overflow vulnerability exists FFmpeg 4.2 at libavfilter/vfedgedetect.c in gaussianblur, which might lead to memory corruption and other...

Linux Distros Unpatched Vulnerability : CVE-2023-50009

The Linux/Unix host has one or more packages installed that are impacted by a vulnerability without a vendor supplied patch available. - FFmpeg v.n6.1-3-g466799d4f5 allows a heap-based buffer overflow via the ffgaussianblur8 function in libavfilter/edgetemplate.c:116:5 component. CVE-2023-50009...

VeriPHY: Physical Layer Signal Authentication for Wireless Communication in 5G Environments

Physical layer authentication PLA uses inherent characteristics of the communication medium to provide secure and efficient authentication in wireless networks, bypassing the need for traditional cryptographic methods. With advancements in deep learning, PLA has become a widely adopted technique...

Who'S the Evil Twin? Differential Auditing for Undesired Behavior

Detecting hidden behaviors in neural networks poses a significant challenge due to minimal prior knowledge and potential adversarial obfuscation. We explore this problem by framing detection as an adversarial game between two teams: the red team trains two similar models, one trained solely on...

Sparse Regression Codes for Secret Key Agreement: Achieving Strong Secrecy and Near-Optimal Rates for Gaussian Sources

Secret key agreement from correlated physical layer observations is a cornerstone of information-theoretic security. This paper proposes and rigorously analyzes a complete, constructive protocol for secret key agreement from Gaussian sources using Sparse Regression Codes SPARCs. Our protocol...

FedP3E: Privacy-Preserving Prototype Exchange for Non-IID IoT Malware Detection in Cross-Silo Federated Learning

As IoT ecosystems continue to expand across critical sectors, they have become prominent targets for increasingly sophisticated and large-scale malware attacks. The evolving threat landscape, combined with the sensitive nature of IoT-generated data, demands detection frameworks that are both...

Balancing Privacy and Utility in Correlated Data: a Study of Bayesian Differential Privacy

Privacy risks in differentially private DP systems increase significantly when data is correlated, as standard DP metrics often underestimate the resulting privacy leakage, leaving sensitive information vulnerable. Given the ubiquity of dependencies in real-world databases, this oversight poses a...

Restoring Gaussian Blurred Face Images for Deanonymization Attacks

Gaussian blur is widely used to blur human faces in sensitive photos before the photos are posted on the Internet. However, it is unclear to what extent the blurred faces can be restored and used to re-identify the person, especially under a high-blurring setting. In this paper, we explore this...

Beyond Laplace and Gaussian: Exploring the Generalized Gaussian Mechanism for Private Machine Learning

Differential privacy DP is obtained by randomizing a data analysis algorithm, which necessarily introduces a tradeoff between its utility and privacy. Many DP mechanisms are built upon one of two underlying tools: Laplace and Gaussian additive noise mechanisms. We expand the search space of...

Enclosing Prototypical Variational Autoencoder for Explainable Out-of-Distribution Detection

Understanding the decision-making and trusting the reliability of Deep Machine Learning Models is crucial for adopting such methods to safety-relevant applications. We extend self-explainable Prototypical Variational models with autoencoder-based out-of-distribution OOD detection: A Variational...