What Response Marginals Miss: Adaptive Query Complexity of Functional Backdoor Recovery

Functional backdoor recovery finds any trigger whose attack success rate is at least a given threshold rather than to recover the planted trigger. We study the minimum number of queries required for this task under label feedback which returns the predicted class label. We construct two finite...

JASPER: Special Session on Joint Reliability and Security Assessment of SPlit Computing for Edge Robustness

Split Computing SC enables efficient deployment of Deep Neural Networks DNNs by partitioning inference between edge devices and cloud servers. However, intermediate feature representations are simultaneously exposed to hardware faults and adversarial attacks, which are traditionally evaluated...

Model Poisoning against Federated Model Adaptation with Chain of Bit-Flips

Federated Learning FL allows a set of clients to collectively train a global model without sharing local training data. Giving the responsibility of the training to decentralized actors may lead to poisoning attacks: clients controlled by malicious third party potentially poison the training...

Hybrid ResNet-1D-BiGRU with Multi-Head Attention for Cyberattack Detection in Industrial IoT Environments

This study introduces a hybrid deep learning model for intrusion detection in Industrial IoT IIoT systems, combining ResNet-1D, BiGRU, and Multi-Head Attention MHA for effective spatial-temporal feature extraction and attention-based feature weighting. To address class imbalance, SMOTE was applie...

CVE-2025-13715

Tencent FaceDetection-DSFD resnet Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Tencent FaceDetection-DSFD. User interaction is required to exploit this vulnerability in that...

EUVD-2025-204968

Tencent FaceDetection-DSFD resnet Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Tencent FaceDetection-DSFD. User interaction is required to exploit this vulnerability in that...

CVE-2025-13715

Tencent FaceDetection-DSFD resnet Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Tencent FaceDetection-DSFD. User interaction is required to exploit this vulnerability in that...

CVE-2025-13715 Tencent FaceDetection-DSFD resnet Deserialization of Untrusted Data Remote Code Execution Vulnerability

Tencent FaceDetection-DSFD resnet Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Tencent FaceDetection-DSFD. User interaction is required to exploit this vulnerability in that...

CVE-2025-13715 Tencent FaceDetection-DSFD resnet Deserialization of Untrusted Data Remote Code Execution Vulnerability

Tencent FaceDetection-DSFD resnet Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Tencent FaceDetection-DSFD. User interaction is required to exploit this vulnerability in that...

CVE-2025-13715

The CVE-2025-13715 belongs to Tencent FaceDetection-DSFD (resnet endpoint). The issue is Deserialization of Untrusted Data leading to Remote Code Execution. Exploitation requires user interaction (visiting a malicious page or opening a malicious file). The root cause is improper validation of use...

CVE-2025-13715 Tencent FaceDetection-DSFD resnet Deserialization of Untrusted Data Remote Code Execution Vulnerability

Tencent FaceDetection-DSFD resnet Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Tencent FaceDetection-DSFD. User interaction is required to exploit this vulnerability in that...

PT-2025-52849

Name of the Vulnerable Software and Affected Versions Tencent FaceDetection-DSFD affected versions not specified Description A flaw exists in Tencent FaceDetection-DSFD that allows remote attackers to execute arbitrary code. User interaction is required, such as visiting a malicious page or openi...

Tencent FaceDetection-DSFD resnet Deserialization of Untrusted Data Remote Code Execution Vulnerability

This vulnerability allows remote attackers to execute arbitrary code on affected installations of Tencent FaceDetection-DSFD. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the...

Tencent FaceDetection-DSFD 代码问题漏洞

Tencent FaceDetection-DSFD is a face detection algorithm from Tencent, a Chinese company. Tencent FaceDetection-DSFD suffers from a code issue vulnerability that stems from a lack of validation of user-supplied data at resnet endpoints, which could lead to deserialization of untrusted data and...

CVE-2025-13715: Deserialization of Untrusted Data

Tencent FaceDetection-DSFD resnet Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Tencent FaceDetection-DSFD. User interaction is required to exploit this vulnerability in that...

Activate Me!: Designing Efficient Activation Functions for Privacy-Preserving Machine Learning with Fully Homomorphic Encryption

The growing adoption of machine learning in sensitive areas such as healthcare and defense introduces significant privacy and security challenges. These domains demand robust data protection, as models depend on large volumes of sensitive information for both training and inference. Fully...

CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage

Model compression is crucial for minimizing memory storage and accelerating inference in deep learning DL models, including recent foundation models like large language models LLMs. Users can access different compressed model versions according to their resources and budget. However, while existi...

Spectral Feature Extraction for Robust Network Intrusion Detection Using MFCCs

The rapid expansion of Internet of Things IoT networks has led to a surge in security vulnerabilities, emphasizing the critical need for robust anomaly detection and classification techniques. In this work, we propose a novel approach for identifying anomalies in IoT network traffic by leveraging...

TED-LaST: Towards Robust Backdoor Defense against Adaptive Attacks

Deep Neural Networks DNNs are vulnerable to backdoor attacks, where attackers implant hidden triggers during training to maliciously control model behavior. Topological Evolution Dynamics TED has recently emerged as a powerful tool for detecting backdoor attacks in DNNs. However, TED can be...

Efficient Malicious UAV Detection Using Autoencoder-TSMamba Integration

Malicious Unmanned Aerial Vehicles UAVs present a significant threat to next-generation networks NGNs, posing risks such as unauthorized surveillance, data theft, and the delivery of hazardous materials. This paper proposes an integrated AE-classifier system to detect malicious UAVs. The proposed...