SUSE-SU-2025:02527-1 Security update for polkit

This update for polkit fixes the following issues: - CVE-2025-7519: Fixed a XML policy file with a large number of nested elements that may lead to out-of-bounds write. bsc1246472...

Ruby REXML < 3.3.6 DoS vulnerability

The version of the REXML Ruby library installed on the remote host is prior to 3.3.6. It is, therefore, affected by a DoS vulnerability. The vulnerability lies when it parses an XML that has many deep elements that have same local name attributes. If you need to parse untrusted XMLs with tree...

AZL-65379 CVE-2025-7519 affecting package polkit for versions less than 0.119-4

A flaw was found in polkit. When processing an XML policy with 32 or more nested elements in depth, an out-of-bounds write can be triggered. This issue can lead to a crash or other unexpected behavior, and arbitrary code execution is not discarded. To exploit this flaw, a high-privilege account i...

Phishing Detection in the Gen-AI Era: Quantized LLMs Vs Classical Models

Phishing attacks are becoming increasingly sophisticated, underscoring the need for detection systems that strike a balance between high accuracy and computational efficiency. This paper presents a comparative evaluation of traditional Machine Learning ML, Deep Learning DL, and quantized...

PYSEC-2025-251

The JSONReader in run-llama/llamaindex versions 0.12.28 is vulnerable to a stack overflow due to uncontrolled recursive JSON parsing. This vulnerability allows attackers to trigger a Denial of Service DoS by submitting deeply nested JSON structures, leading to a RecursionError and crashing...

Beyond Training-Time Poisoning: Component-Level and Post-Training Backdoors in Deep Reinforcement Learning

Deep Reinforcement Learning DRL systems are increasingly used in safety-critical applications, yet their security remains severely underexplored. This work investigates backdoor attacks, which implant hidden triggers that cause malicious actions only when specific inputs appear in the observation...

README: Robust Error-Aware Digital Signature Framework Via Deep Watermarking Model

Deep learning-based watermarking has emerged as a promising solution for robust image authentication and protection. However, existing models are limited by low embedding capacity and vulnerability to bit-level errors, making them unsuitable for cryptographic applications such as digital...

Adaptive Malware Detection Using Sequential Feature Selection: a Dueling Double Deep Q-Network (D3QN) Framework for Intelligent Classification

Traditional malware detection methods exhibit computational inefficiency due to exhaustive feature extraction requirements, creating accuracy-efficiency trade-offs that limit real-time deployment. We formulate malware classification as a Markov Decision Process with episodic feature acquisition a...

CVE-2025-52999

jackson-core contains core low-level incremental "streaming" parser and generator abstractions used by Jackson Data Processor. In versions prior to 2.15.0, if a user parses an input file and it has deeply nested data, Jackson could end up throwing a StackoverflowError if the depth is particularly...

Universal and Efficient Detection of Adversarial Data through Nonuniform Impact on Network Layers

Deep Neural Networks DNNs are notoriously vulnerable to adversarial input designs with limited noise budgets. While numerous successful attacks with subtle modifications to original input have been proposed, defense techniques against these attacks are relatively understudied. Existing defense...

Autonomous Cyber Resilience Via a Co-Evolutionary Arms Race within a Fortified Digital Twin Sandbox

The convergence of IT and OT has created hyper-connected ICS, exposing critical infrastructure to a new class of adaptive, intelligent adversaries that render static defenses obsolete. Existing security paradigms often fail to address a foundational "Trinity of Trust," comprising the fidelity of...

CVE-2025-30642

A link following vulnerability in Trend Micro Deep Security 20.0 agents could allow a local attacker to create a denial of service DoS situation on affected installations. Please note: an attacker must first obtain the ability to execute low-privileged code on the target system in order to exploi...

CVE-2025-30641

A link following vulnerability in the anti-malware solution portion of Trend Micro Deep Security 20.0 agents could allow a local attacker to escalate privileges on affected installations. Please note: an attacker must first obtain the ability to execute low-privileged code on the target system in...

CVE-2025-30640

A link following vulnerability in Trend Micro Deep Security 20.0 agents could allow a local attacker to escalate privileges on affected installations. Please note: an attacker must first obtain the ability to execute low-privileged code on the target system in order to exploit this vulnerability...

Adaptive Alert Prioritisation in Security Operations Centres Via Learning to Defer with Human Feedback

Alert prioritisation AP is crucial for security operations centres SOCs to manage the overwhelming volume of alerts and ensure timely detection and response to genuine threats, while minimising alert fatigue. Although predictive AI can process large alert volumes and identify known patterns, it...

Deep CNN Face Matchers Inherently Support Revocable Biometric Templates

One common critique of biometric authentication is that if an individual's biometric is compromised, then the individual has no recourse. The concept of revocable biometrics was developed to address this concern. A biometric scheme is revocable if an individual can have their current enrollment i...

Technical Evaluation of a Disruptive Approach in Homomorphic AI

We present a technical evaluation of a new, disruptive cryptographic approach to data security, known as HbHAI Hash-based Homomorphic Artificial Intelligence. HbHAI is based on a novel class of key-dependent hash functions that naturally preserve most similarity properties, most AI algorithms rel...

Deep Spatial Neural Net Models with Functional Predictors: Application in Large-Scale Crop Yield Prediction

Accurate prediction of crop yield is critical for supporting food security, agricultural planning, and economic decision-making. However, yield forecasting remains a significant challenge due to the complex and nonlinear relationships between weather variables and crop production, as well as...

Efficient Retail Video Annotation: a Robust Key Frame Generation Approach for Product and Customer Interaction Analysis

Accurate video annotation plays a vital role in modern retail applications, including customer behavior analysis, product interaction detection, and in-store activity recognition. However, conventional annotation methods heavily rely on time-consuming manual labeling by human annotators,...

Exploiting Efficiency Vulnerabilities in Dynamic Deep Learning Systems

The growing deployment of deep learning models in real-world environments has intensified the need for efficient inference under strict latency and resource constraints. To meet these demands, dynamic deep learning systems DDLSs have emerged, offering input-adaptive computation to optimize runtim...