Video Signature: In-Generation Watermarking for Latent Video Diffusion Models

The rapid development of Artificial Intelligence Generated Content AIGC has led to significant progress in video generation but also raises serious concerns about intellectual property protection and reliable content tracing. Watermarking is a widely adopted solution to this issue, but existing...

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection

Money laundering is a financial crime that poses a serious threat to financial integrity and social security. The growing number of transactions makes it necessary to use automatic tools that help law enforcement agencies detect such criminal activity. In this work, we present Amatriciana, a nove...

Aurora: Are Android Malware Classifiers Reliable under Distribution Shift?

The performance figures of modern drift-adaptive malware classifiers appear promising, but does this translate to genuine operational reliability? The standard evaluation paradigm primarily focuses on baseline performance metrics, neglecting confidence-error alignment and operational stability...

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.,...

DP-RTFL: Differentially Private Resilient Temporal Federated Learning for Trustworthy AI in Regulated Industries

Federated Learning FL has emerged as a critical paradigm for enabling privacy-preserving machine learning, particularly in regulated sectors such as finance and healthcare. However, standard FL strategies often encounter significant operational challenges related to fault tolerance, system...

LAMDA: a Longitudinal Android Malware Benchmark for Concept Drift Analysis

Machine learning ML-based malware detection systems often fail to account for the dynamic nature of real-world training and test data distributions. In practice, these distributions evolve due to frequent changes in the Android ecosystem, adversarial development of new malware families, and the...

D4+: Emergent Adversarial Driving Maneuvers with Approximate Functional Optimization

Intelligent mechanisms implemented in autonomous vehicles, such as proactive driving assist and collision alerts, reduce traffic accidents. However, verifying their correct functionality is difficult due to complex interactions with the environment. This problem is exacerbated in adversarial...

FABLE: a Localized, Targeted Adversarial Attack on Weather Forecasting Models

Deep learning-based weather forecasting models have recently demonstrated significant performance improvements over gold-standard physics-based simulation tools. However, these models are vulnerable to adversarial attacks, which raises concerns about their trustworthiness. In this paper, we first...

Detecting Sybil Addresses in Blockchain Airdrops: a Subgraph-Based Feature Propagation and Fusion Approach

Sybil attacks pose a significant security threat to blockchain ecosystems, particularly in token airdrop events. This paper proposes a novel sybil address identification method based on subgraph feature extraction lightGBM. The method first constructs a two-layer deep transaction subgraph for eac...

VIDSTAMP: a Temporally-Aware Watermark for Ownership and Integrity in Video Diffusion Models

The rapid rise of video diffusion models has enabled the generation of highly realistic and temporally coherent videos, raising critical concerns about content authenticity, provenance, and misuse. Existing watermarking approaches, whether passive, post-hoc, or adapted from image-based techniques...

Security Bulletin: IBM Spectrum Protect Plus vulnerability discloses sensitive information due to unencrypted data in transit (CVE-2020-4497)

Summary IBM Spectrum Protect Plus does not encrypt data transfer between vSnap servers and application agents. This could allow an attacker to view senstive information in transit. Vulnerability Details CVEID:CVE-2020-4497 DESCRIPTION: IBM Spectrum Protect Plus discloses sensitive information due...

PyTorch LossCTC.cpp torch.nn.functional.ctc_loss denial of service

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Contrastive Learning for Continuous Touch-Based Authentication

Smart mobile devices have become indispensable in modern daily life, where sensitive information is frequently processed, stored, and transmitted-posing critical demands for robust security controls. Given that touchscreens are the primary medium for human-device interaction, continuous user...

CSI2Dig: Recovering Digit Content from Smartphone Loudspeakers Using Channel State Information

Eavesdropping on sounds emitted by mobile device loudspeakers can capture sensitive digital information, such as SMS verification codes, credit card numbers, and withdrawal passwords, which poses significant security risks. Existing schemes either require expensive specialized equipment, rely on...

CVE-2025-30204 vulnerabilities

Vulnerabilities for packages: opentofu, cortex, sqlexporter, pulumi, openfga, weaviate, xeol, splunk-otel-collector, terragrunt, kine, flux, kargo, rclone, buildkitd, gitness, minio-operator, external-dns, restic, grafana-agent-operator, kyverno-policy-reporter-ui, atlantis, sftpgo-plugin-kms,...

WordPress plugin AHAthat Plugin SQL注入漏洞

WordPress and WordPress plugin are both products of the WordPress Foundation.WordPress is a set of blogging platforms developed using the PHP language. The platform supports setting up personal blog sites on servers with PHP and MySQL.WordPress plugin is an application plugin. A SQL injection...

SUSE CVE-2025-1243

The Temporal api-go library prior to version 1.44.1 did not send update response information to Data Converter when the proxy package within the api-go module was used in a gRPC proxy prior to transmission. This resulted in information contained within the update response field not having Data...

GO-2025-3462 Unencrypted transmission in Temporal api-go library in go.temporal.io/api

Unencrypted transmission in Temporal api-go library in go.temporal.io/api...

Improper Data Encryption

Temporal api-go is vulnerable to Improper Data Encryption. The vulnerability is due to missing Data Converter transformations due to the update response information not being processed by the Data Converter when using a gRPC proxy with the api-go module, leading to unencrypted data exposure...

GHSA-Q9W6-CWJ4-GF4P Unencrypted transmission in Temporal api-go library

The Temporal api-go library prior to version 1.44.1 did not send update response information to Data Converter when the proxy package within the api-go module was used in a gRPC proxy prior to transmission. This resulted in information contained within the update response field not having Data...