Risk Models As Mediating Artifacts: A Postphenomenological Analysis of the CIIM Framework in Cybersecurity Practice

This article applies postphenomenological theory to the field of cybersecurity risk management, arguing that formal risk models function as mediating artifacts that shape how security practitioners or analysts perceive, interpret, and act on threats. Based on Don Ihde's taxonomy on human-technolo...

Adaptive Instruction Composition for Automated LLM Red-Teaming

Many approaches to LLM red-teaming leverage an attacker LLM to discover jailbreaks against a target. Several of them task the attacker with identifying effective strategies through trial and error, resulting in a semantically limited range of successes. Another approach discovers diverse attacks ...

TL-RL-FusionNet: An Adaptive and Efficient Reinforcement Learning-Driven Transfer Learning Framework for Detecting Evolving Ransomware Threats

Modern ransomware exhibits polymorphic and evasive behaviors by frequently modifying execution patterns to evade detection. This dynamic nature disrupts feature spaces and limits the effectiveness of static or predefined models. To address this challenge, we propose TL-RL-FusionNet, a reinforceme...

SDNGuardStack: An Explainable Ensemble Learning Framework for High-Accuracy Intrusion Detection in Software-Defined Networks

Software-Defined Networking SDN is another technology that has been developing in the last few years as a relevant technique to improve network programmability and administration. Nonetheless, its centralized design presents a major security issue, which requires effective intrusion detection...

Involuntary In-Context Learning: Exploiting Few-Shot Pattern Completion to Bypass Safety Alignment in GPT-5.4

Safety alignment in large language models relies on behavioral training that can be overridden when sufficiently strong in-context patterns compete with learned refusal behaviors. We introduce Involuntary In-Context Learning IICL, an attack class that uses abstract operator framing with few-shot...

DP-FlogTinyLLM: Differentially Private Federated Log Anomaly Detection Using Tiny LLMs

Modern distributed systems generate massive volumes of log data that are critical for detecting anomalies and cyber threats. However, in real world settings, these logs are often distributed across multiple organizations and cannot be centralized due to privacy and security constraints. Existing...

API Security Based on Automatic OpenAPI Mapping

This paper presents Map Reduce Graph MRG, a novel unsupervised method for modeling and securing HTTP REST APIs. MRG learns API structure from real-world traffic without prior knowledge or labels, automatically generating OpenAPI-compliant documentation by reconstructing routes, methods, and...

ARES: Adaptive Red-Teaming and End-To-End Repair of Policy-Reward System

Reinforcement Learning from Human Feedback RLHF is central to aligning Large Language Models LLMs, yet it introduces a critical vulnerability: an imperfect Reward Model RM can become a single point of failure when it fails to penalize unsafe behaviors. While existing red-teaming approaches...

vantix

Vantix Vantix is a Codex-native offensive-security control pl...

Exploit for CVE-2025-15521

CVE-2025-15521 The Academy LMS – WordPress LMS Plugin for Comp...

CVE-2026-5502

The Tutor LMS – eLearning and online course solution plugin for WordPress is vulnerable to unauthorized course content manipulation in versions up to and including 3.9.8. This is due to a missing authorization check in the tutorupdatecoursecontentorder function. The function only validates the...

CVE-2026-4817

The MasterStudy LMS WordPress Plugin for Online Courses and Education plugin for WordPress is vulnerable to Time-based Blind SQL Injection via the 'order' and 'orderby' parameters in the /lms/stm-lms/order/items REST API endpoint in versions up to and including 3.7.25. This is due to insufficient...

Privacy-Aware Machine Unlearning with SISA for Reinforcement Learning-Based Ransomware Detection

Ransomware detection systems increasingly rely on behavior-based machine learning to address evolving attack strategies. However, emerging privacy compliance, data governance, and responsible AI deployment demand not only accurate detection but also the ability to efficiently remove the influence...

CVE-2025-69893

A side-channel vulnerability exists in the implementation of BIP-39 mnemonic processing, as observed in Trezor One v1.13.0 to v1.14.0, Trezor T v1.13.0 to v1.14.0, and Trezor Safe v1.13.0 to v1.14.0 hardware wallets. This originates from the BIP-39 standard guidelines, which induce non-constant...

MLDAS: Machine Learning Dynamic Algorithm Selection for Software-Defined Networking Security

Network security is a critical concern in the digital landscape of today, with users demanding secure browsing experiences and protection of their personal data. This study explores the dynamic integration of Machine Learning ML algorithms with Software-Defined Networking SDN controllers to enhan...

NFTDELTA: Detecting Permission Control Vulnerabilities in NFT Contracts through Multi-View Learning

Permission control vulnerabilities in Non-fungible token NFT contracts can result in significant financial losses, as attackers may exploit these weaknesses to gain unauthorized access or circumvent critical permission checks. In this paper, we propose NFTDELTA, a framework that leverages static...

CSLE: A Reinforcement Learning Platform for Autonomous Security Management

Reinforcement learning is a promising approach to autonomous and adaptive security management in networked systems. However, current reinforcement learning solutions for security management are mostly limited to simulation environments and it is unclear how they generalize to operational systems...

CVE-2026-33705

Chamilo LMS is a learning management system. Prior to 1.11.38, Twig template files .tpl under /main/template/default/ are directly accessible without authentication via HTTP GET requests. These templates expose internal application logic, variable names, AJAX endpoint URLs, and admin panel...

Towards Personalizing Secure Programming Education with LLM-Injected Vulnerabilities

According to constructivist theory, students learn software security more effectively when examples are grounded in their own code. Generic examples often fail to connect with students' prior work, limiting engagement and understanding. Advances in LLMs are now making it possible to automatically...

CVE-2026-35196

Chamilo LMS is an open-source learning management system. In versions prior to 2.0.0-RC.3, an OS Command Injection vulnerability exists in the main/inc/ajax/gradebook.ajax.php endpoint within the exportallcertificates action, where the course code retrieved from the session variable $SESSION'cid'...