Researchers at TII, in cooperation with University Paderborn and Ruhr University Bochum, have discovered a vulnerability called the Opossum Attack in Transport Layer Security (TLS) impacting protocols like HTTP(S), FTP(S), POP3(S), and SMTP(S). The vulnerability exposes a risk of desynchronization between client and server communications, potentially leading to exploits like session fixation and content confusion. Scans revealed over 2.9 million potentially affected servers, including over 1.4 million IMAP servers and 1.1 million POP3 servers. Why it matters: This discovery highlights the importance of ongoing cybersecurity research in the UAE and internationally to identify and address vulnerabilities in fundamental internet protocols, especially as it led to immediate action by Apache and Cyrus IMAPd.
The paper introduces VENOM, a text-driven framework for generating high-quality unrestricted adversarial examples using diffusion models. VENOM unifies image content generation and adversarial synthesis into a single reverse diffusion process, enhancing both attack success rate and image quality. The framework incorporates an adaptive adversarial guidance strategy with momentum to ensure the generated adversarial examples align with the distribution of natural images.
This paper introduces a novel black-box adversarial attack method, Mixup-Attack, to generate universal adversarial examples for remote sensing data. The method identifies common vulnerabilities in neural networks by attacking features in the shallow layer of a surrogate model. The authors also present UAE-RS, the first dataset of black-box adversarial samples in remote sensing, to benchmark the robustness of deep learning models against adversarial attacks.
The paper introduces ScoreAdv, a novel approach for generating natural adversarial examples (UAEs) using diffusion models. It incorporates an adversarial guidance mechanism and saliency maps to shift the sampling distribution and inject visual information. Experiments on ImageNet and CelebA datasets demonstrate state-of-the-art attack success rates, image quality, and robustness against defenses.