EUVD-2023-59784

Malicious code in bioql PyPI...

EUVD-2024-17291

Malicious code in bioql PyPI...

EUVD-2021-3136

Malicious code in bioql PyPI...

Defending against Stegomalware in Deep Neural Networks with Permutation Symmetry

Deep neural networks are being utilized in a growing number of applications, both in production systems and for personal use. Network checkpoints are as a consequence often shared and distributed on various platforms to ease the development process. This work considers the threat of neural networ...

Automated Cyber Defense with Generalizable Graph-Based Reinforcement Learning Agents

Deep reinforcement learning RL is emerging as a viable strategy for automated cyber defense ACD. The traditional RL approach represents networks as a list of computers in various states of safety or threat. Unfortunately, these models are forced to overfit to specific network topologies, renderin...

LLMs in Cybersecurity: Friend or Foe in the Human Decision Loop?

Large Language Models LLMs are transforming human decision-making by acting as cognitive collaborators. Yet, this promise comes with a paradox: while LLMs can improve accuracy, they may also erode independent reasoning, promote over-reliance and homogenize decisions. In this paper, we investigate...

Asymmetry Vulnerability and Physical Attacks on Online Map Construction for Autonomous Driving

High-definition maps provide precise environmental information essential for prediction and planning in autonomous driving systems. Due to the high cost of labeling and maintenance, recent research has turned to online HD map construction using onboard sensor data, offering wider coverage and mor...

GOP Cries Censorship Over Spam Filters That Work

The chairman of the Federal Trade Commission FTC last week sent a letter to Google's CEO demanding to know why Gmail was blocking messages from Republican senders while allegedly failing to block similar missives supporting Democrats. The letter followed media reports accusing Gmail of...

Trust Me, I Know This Function: Hijacking LLM Static Analysis Using Bias

Large Language Models LLMs are increasingly trusted to perform automated code review and static analysis at scale, supporting tasks such as vulnerability detection, summarization, and refactoring. In this paper, we identify and exploit a critical vulnerability in LLM-based code analysis: an...

Routing and Wavelength Assignment with Minimal Attack Radius for QKD Networks

Quantum Key Distribution QKD can distribute keys with guaranteed security but remains susceptible to key exchange interruption due to physical-layer threats, such as high-power jamming attacks. To address this challenge, we first introduce a novel metric, namely Maximum Number of Affected Request...

The vulnerability of the reference_count function and the biasPadEnable() function in the Linux operating system’s kernel allows a hacker to increase their privileges within the system.

The vulnerability of the referencecount biasPadEnable function in the Linux operating system is related to competitive access to resources a state of competition. Exploiting this vulnerability can allow a hacker to enhance their privileges within the system...

Restricted Boltzmann Machine As a Probabilistic Enigma

We theoretically propose a symmetric encryption scheme based on Restricted Boltzmann Machines that functions as a probabilistic Enigma device, encoding information in the marginal distributions of visible states while utilizing bias permutations as cryptographic keys. Theoretical analysis reveals...

TELSAFE: Security Gap Quantitative Risk Assessment Framework

Gaps between established security standards and their practical implementation have the potential to introduce vulnerabilities, possibly exposing them to security risks. To effectively address and mitigate these security and compliance challenges, security risk management strategies are essential...

Hiding Prompt Injections in Academic Papers

Academic papers were found to contain hidden instructions to LLMs: It discovered such prompts in 17 articles, whose lead authors are affiliated with 14 institutions including Japan's Waseda University, South Korea's KAIST, China's Peking University and the National University of Singapore, as wel...

The Psychology of Exposure: Why Security Teams Ignore What’s Right in Front of Them

Running short on time but still want to stay in the know? Well, we’ve got you covered! We’ve condensed all the key takeaways into a handy audio summary. Our AI-driven podcasts are fit for on the go. Your security team sees everything and notices nothing. Drowning in alerts, CVEs, dashboards, risk...

The Psychology of Exposure: Why Security Teams Ignore What’s Right in Front of Them

Running short on time but still want to stay in the know? Well, we’ve got you covered! We’ve condensed all the key takeaways into a handy audio summary. Our AI-driven podcasts are fit for on the go. Your security team sees everything and notices nothing. Drowning in alerts, CVEs, dashboards, risk...

Organizational Adaptation to Generative AI in Cybersecurity: a Systematic Review

Cybersecurity organizations are adapting to GenAI integration through modified frameworks and hybrid operational processes, with success influenced by existing security maturity, regulatory requirements, and investments in human capital and infrastructure. This qualitative research employs...

CVE-2025-38010

In the Linux kernel, the following vulnerability has been resolved: phy: tegra: xusb: Use a bitmask for UTMI pad power state tracking The current implementation uses biaspadenable as a reference count to manage the shared bias pad for all UTMI PHYs. However, during system suspension with connecte...

CVE-2025-38010

CVE-2025-38010 – Linux kernel patch replaces a single reference counter for UTMI pad power with a per-pad bitmask (utmi_pad_enabled) to track all four USB2 UTMI PHY pads. The root cause was an unbalanced reference count when suspending with connected USB devices, due to power-downs not validating...

Bias Variation Compensation in Perimeter-Gated SPAD TRNGs

Random number generators that utilize arrays of entropy source elements suffer from bias variation BV. Despite the availability of efficient debiasing algorithms, optimized implementations of hardware friendly options depend on the bit bias in the raw bit streams and cannot accommodate a wide BV...