redexer

redexer Redexer es una herramienta de reingeniería que manipula binarios de aplicaciones Android. Esta herramienta es capaz de analizar un archivo DEX en una estructura de datos en memoria; inferir con qué parámetros la aplicación usa ciertos permisos nombramos esta característica RefineDroid;...

AutoRAN-public

🧠 AutoRAN: Secuestro automatizado del razonamiento de seguridad en grandes modelos de razonamiento AutoRAN es un secuestro automatizado del razonamiento de seguridad que aprovecha modelos auxiliares secundarios menos alineados para simular trazas de razonamiento, generar prompts narrativos y...

qlcoder

QLCoder Framework agéntico para sintetizar consultas CodeQL Tabla de contenidos Resumen Instalación Docker Recomendado Nativo Linux Uso Inicio rápido Herramientas de desarrollo Ejemplos Entorno del artículo Contribuciones Equipo Citación Proyectos afiliados Resumen QLCoder es un framework para us...

Unity Linux 20.1050a Security Update: kernel (UTSA-2026-098777)

The Unity Linux 20 host has a package installed that is affected by a vulnerability as referenced in the UTSA-2026-098777 advisory. In the Linux kernel, the following vulnerability has been resolved: bpf: Forget ranges when refining tnum after JSET Syzbot reported a kernel warning due to a range...

XSSaudit

XSSAudit v2.0 — Advanced XSS Vulnerability Scanner For au...

UNAD+: An Explainable Hybrid Framework for Unknown Network Attack Detection

The detection of previously unseen network attacks remains a major challenge for intrusion detection systems. Although supervised learning methods often perform well on known attack classes, they are limited when new attack types are not represented in the training data. Unsupervised methods are...

A Large Language Model Approach to Generating Bypass Rules for Malware Evasion in Analysis Sandbox

Sandbox evasion remains a critical challenge for automated malware analysis, as modern malware employs environment checks to detect analysis platforms and suppress malicious behavior. Existing approaches rely on manually crafted bypass rules that require deep reverse engineering of each evasion...

Babel: Jailbreaking Safety Attention Via Obfuscation Distribution Optimized Sampling

Despite rigorous safety alignment, Large Language Models LLMs remain vulnerable to jailbreak attacks. Existing black-box methods often rely on heuristic templates or exhaustive trials, lacking mechanistic interpretability and query efficiency. In this study, we investigate an intrinsic...

MemRepair: Hierarchical Memory for Agentic Repository-Level Vulnerability Repair

Modern software ecosystems face a rapidly growing number of disclosed vulnerabilities, increasing the need for automated repair techniques that can operate reliably at repository scale. Although Large Language Model LLM-based agents have recently shown promise for automated vulnerability repair...

FuzzAgent: Multi-Agent System for Evolutionary Library Fuzzing

Library fuzzing is essential for hardening the software supply chain, but adopting it at scale remains expensive. Practitioners still spend substantial effort on environment setup, struggle to generate harnesses that respect intricate API constraints, and lack reliable means to tell genuine libra...

MT-JailBench: A Modular Benchmark for Understanding Multi-Turn Jailbreak Attacks

Multi-turn jailbreaks exploit the ability of large language models to accumulate and act on conversational context. Instead of stating a harmful request directly, an attacker can gradually steer the conversation toward an unsafe answer. Recent methods demonstrate this risk, but they are usually...

SkillAttack: Automated Red Teaming of Agent Skills through Attack Path Refinement

LLM-based agent systems increasingly rely on agent skills sourced from open registries to extend their capabilities, yet the openness of such ecosystems makes skills difficult to thoroughly vet. Existing attacks rely on injecting malicious instructions into skills, making them easily detectable b...

Threat actor abuse of AI accelerates from tool to cyberattack surface

For the last year, one word has represented the conversation living at the intersection of AI and cybersecurity: speed. Speed matters, but it’s not the most important shift we are observing across the threat landscape today. Now, threat actors from nation states to cybercrime groups are embedding...

AutoEG: Exploiting Known Third-Party Vulnerabilities in Black-Box Web Applications

Large-scale web applications are widely deployed with complex third-party components, inheriting security risks arising from component vulnerabilities. Security assessment is therefore required to determine whether such known vulnerabilities remain practically exploitable in real applications...

Red-MIRROR: Agentic LLM-Based Autonomous Penetration Testing with Reflective Verification and Knowledge-Augmented Interaction

Web applications remain the dominant attack surface in cybersecurity, where vulnerabilities such as SQL injection, XSS, and business logic flaws continue to cause significant data breaches. While penetration testing is effective for identifying these weaknesses, traditional manual approaches are...

SUSE-SU-2026:20720-1 Security update for the Linux Kernel

The SUSE Linux Enterprise Micro 6.0 and Micro 6.1 kernel was updated to fix various security issues The following security issues were fixed: - CVE-2023-53817: crypto: lib/mpi - avoid null pointer deref in mpicmpui bsc1254992. - CVE-2025-37861: scsi: mpi3mr: Synchronous access b/w reset and tm...

Robust Provably Secure Image Steganography Via Latent Iterative Optimization

We propose a robust and provably secure image steganography framework based on latent-space iterative optimization. Within this framework, the receiver treats the transmitted image as a fixed reference and iteratively refines a latent variable to minimize the reconstruction error, thereby improvi...

Coverage-Guided Multi-Agent Harness Generation for Java Library Fuzzing

Coverage-guided fuzzing has proven effective for software testing, but targeting library code requires specialized fuzz harnesses that translate fuzzer-generated inputs into valid API invocations. Manual harness creation is time-consuming and requires deep understanding of API semantics,...

SCAFFOLD-CEGIS: Preventing Latent Security Degradation in LLM-Driven Iterative Code Refinement

The application of large language models to code generation has evolved from one-shot generation to iterative refinement, yet the evolution of security throughout iteration remains insufficiently understood. Through comparative experiments on three mainstream LLMs, this paper reveals the iterativ...

CodeHacker: Automated Test Case Generation for Detecting Vulnerabilities in Competitive Programming Solutions

The evaluation of Large Language Models LLMs for code generation relies heavily on the quality and robustness of test cases. However, existing benchmarks often lack coverage for subtle corner cases, allowing incorrect solutions to pass. To bridge this gap, we propose CodeHacker, an automated agen...