XSSaudit

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

MAL-2026-4739 Malicious code in zkjson (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 758a19e42db66cf6ae7a08d462278b30e3a154b56613d2d95f8020de3add3816 package.json declares "preinstall": "./.github/scripts/precheck", pointing to a 976 KB Linux ELF executable sha256...

Context-Aware Entity-Relation Extraction for Threat Intelligence Knowledge Graphs

Cybersecurity Knowledge Graphs CKGs unify diverse Cyber Threat Intelligence CTI sources into structured, queryable formats, offering scalable solutions for automating proactive and real-time security responses. Their increasing adoption has significantly enhanced the workflow and decision-making...

Iterative Audit Convergence in LLM-Managed Multi-Agent Systems: A Case Study in Prompt Engineering Quality Assurance

Prompt specifications for multi-agent large language model LLM systems carry data contracts and integration logic across many interdependent files but are rarely subjected to structured-inspection rigor. This paper reports a single-system empirical case study of iterative, agent-driven auditing...

From Controlled to the Wild: Evaluation of Pentesting Agents for the Real-World

AI pentesting agents are increasingly credible as offensive security systems, but current benchmarks still provide limited guidance on which will perform best in real-world targets. Existing evaluation protocols assess and optimize for predefined goals such as capture-the-flag, remote code...

SNF - Shadow Network Fingerprinting Engine

SNF Shadow Network Fingerprinting Engine is a 100% offline, air-gap-native passive network intelligence engine written entirely in Rust. It was designed from the ground up for environments where outbound connectivity is not just unavailable but prohibited: classified defense networks, nuclear...

Supporting Artifact Evaluation with LLMs: A Study with Published Security Research Papers

Artifact Evaluation AE is essential for ensuring the transparency and reliability of research, closing the gap between exploratory work and real-world deployment is particularly important in cybersecurity, particularly in IoT and CPSs, where large-scale, heterogeneous, and privacy-sensitive data...

nfstream 6.6.0

nfstream is a Python package providing fast, flexible, and expressive data structures designed to make working with online or offline network data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world network data analysis in Python...

FirmReBugger: A Benchmark Framework for Monolithic Firmware Fuzzers

Monolithic Firmware is widespread. Unsurprisingly, fuzz testing firmware is an active research field with new advances addressing the unique challenges in the domain. However, understanding and evaluating improvements by deriving metrics such as code coverage and unique crashes are problematic,...

S-DAPT-2026: A Stage-Aware Synthetic Dataset for Advanced Persistent Threat Detection

The detection of advanced persistent threats APTs remains a crucial challenge due to their stealthy, multistage nature and the limited availability of realistic, labeled datasets for systematic evaluation. Synthetic dataset generation has emerged as a practical approach for modeling APT campaigns...

The Evolution of Agentic AI in Cybersecurity: From Single LLM Reasoners to Multi-Agent Systems and Autonomous Pipelines

Cybersecurity has become one of the earliest adopters of agentic AI, as security operations centers increasingly rely on multi-step reasoning, tool-driven analysis, and rapid decision-making under pressure. While individual large language models can summarize alerts or interpret unstructured...

Exploring Hidden Geographic Disparities in Android Apps

While mobile app evolution has been widely studied, geographical variation in app behavior remains largely unexplored. This paper presents a large-scale study of location-based Android app differentiation, uncovering two important and underexamined phenomena with security and fairness implication...

A Research and Development Portfolio of GNN Centric Malware Detection, Explainability, and Dataset Curation

Graph Neural Networks GNNs have become an effective tool for malware detection by capturing program execution through graph-structured representations. However, important challenges remain regarding scalability, interpretability, and the availability of reliable datasets. This paper brings togeth...

Real-World Usability of Vulnerability Proof-Of-Concepts: A Comprehensive Study

The Proof-of-Concept PoC for a vulnerability is crucial in validating its existence, mitigating false positives, and illustrating the severity of the security threat it poses. However, research on PoCs significantly lags behind studies focusing on vulnerability data. This discrepancy can be...

Distilling Lightweight Language Models for C/C++ Vulnerabilities

The increasing complexity of modern software systems exacerbates the prevalence of security vulnerabilities, posing risks of severe breaches and substantial economic loss. Consequently, robust code vulnerability detection is essential for software security. While Large Language Models LLMs have...

EUVD-2024-45355

Malicious code in bioql PyPI...

EUVD-2025-25742

Malicious code in bioql PyPI...

SoK: Potentials and Challenges of Large Language Models for Reverse Engineering

Reverse Engineering RE is central to software security, enabling tasks such as vulnerability discovery and malware analysis, but it remains labor-intensive and requires substantial expertise. Earlier advances in deep learning start to automate parts of RE, particularly for malware detection and...

ConCap: Practical Network Traffic Generation for Flow-Based Intrusion Detection Systems

Network Intrusion Detection Systems NIDS have been studied in research for almost four decades. Yet, despite thousands of papers claiming scientific advances, a non-negligible number of recent works suggest that the findings of prior literature may be questionable. At the root of such a...

ATLANTIS: AI-Driven Threat Localization, Analysis, and Triage Intelligence System

We present ATLANTIS, the cyber reasoning system developed by Team Atlanta that won 1st place in the Final Competition of DARPA's AI Cyber Challenge AIxCC at DEF CON 33 August 2025. AIxCC 2023-2025 challenged teams to build autonomous cyber reasoning systems capable of discovering and patching...