SEVulDet

SEVulDet SEVulDet is a semantics-enhanced deep learning-based framework that can accurately pinpoint vulnerability patterns by extracting, preserving, and learning more semantics. E-mail for communication: [email protected] Details of SEVulDet Recent years have seen increased attention to de...

Multi-View Fusion for Encrypted C2 Detection: A Leakage-Controlled Measurement Study of Evaluation Pitfalls

Command-and-control C2 traffic increasingly hides within TLS, so defenders now apply machine learning to traffic metadata. Many studies assume that combining two metadata views, namely flow statistics and TLS handshake fingerprints, improves both accuracy and robustness. We tested this assumption...

Confidence-Guided Cross-Modal Knowledge Transfer for Multimodal Anomaly Detection in Microservice Systems

Accurate anomaly detection is essential for reliable and secure operations of microservice systems. While an increasing number of studies have shifted from unimodal modeling to multimodal interaction and fusion, effectively leveraging reliable cross-modal information remains challenging. The...

Vulnerability Localization Benchmark: Measuring Agentic Security Analysis at Repository Scale

Language-model agents increasingly operate over complete software repositories, yet cybersecurity evaluations primarily measure whether they can detect, reproduce, or repair vulnerabilities rather than whether they can locate the relevant code. We study vulnerability localization: given a weaknes...

Ranked by the Matcher: A Reproducibility Audit of Knowledge Graph Extraction from Threat Reports

Security teams and researchers choose knowledge-graph extraction tooling for threat reports on the strength of published triple-F1 scores, yet those scores depend on how predicted triples are matched to gold annotations. We could reimplement the stated matching rule for only five of twelve...

CVE-2026-80566: Undefined Security Weakness

In the Linux kernel, the following vulnerability has been resolved: Input: hynitroncstxxx - validate touch count and finger IDs The driver allocates maxtouchnum input slots, which are indexed from zero through maxtouchnum - 1. The current check allows a finger ID equal to maxtouchnum to reach...

A Deployment-Oriented and Resource-Efficient Neuro-Symbolic Framework for Explainable DDoS Detection in Operational Technology Networks

Operational technology OT environments, including programmable logic controllers PLCs, industrial control systems ICS, and supervisory control and data acquisition SCADA systems, are increasingly targeted by distributed denial-of-service DDoS attacks. This paper presents a neuro-symbolic framewor...

Checked-In Secret Detection: Strings Are All You Need

Hardcoded secrets in source code pose critical security vulnerabilities which can be easily exploited by malicious adversaries. Existing regex-based detection approaches suffer from fundamental limitations, as secrets often lack identifiable patterns, resulting in poor precision and recall. Recen...

A Multi-Objective AutoML-Based Efficient Intrusion Detection System for EV Charging Networks

Electric Vehicle Charging Systems EVCSs are increasingly connected with Internet of Things IoT devices, which improves charging intelligence but also expands their exposure to cyber-attacks. Intrusion Detection Systems IDSs are essential for securing EV charging networks; however, conventional...

LionWiki <3.2.12 - Local File Inclusion Detection

LionWiki before 3.2.12 allows an unauthenticated user to read files as the web server user via crafted strings in the index.php f1 variable, aka local file inclusion. !/usr/bin/env python3 -- coding: utf-8 -- """LionWiki before 3.""" import re from kittysploit import from...

A Structured Cyber Threat Intelligence Dataset Using STIX 2.1 Entities and MITRE ATT&CK Mappings

Cyber threat intelligence CTI reports are typically written in unstructured formats, which complicates the extraction and analysis of important entities and adversarial behaviors. Although existing CTI research provides extraction tools, knowledge-graph frameworks, and MITRE ATT&CK mapped dataset...

Comparative Analysis of Machine Learning Based Intrusion Detection in Realistic IoT Networks

The Internet of Things IoT is rapidly growing and expanding into various sectors, such as healthcare, transportation, smart homes, and more. Despite the benefits of using IoT devices, they present several challenges. Given the significant role these devices play in our lives, it is crucial to...

Multi-View Decompilation for LLM-Based Malware Classification

Malware analysts often inspect compiled binaries through decompiled pseudo-C, when source code is unavailable. Recent work suggests that large language models LLMs can assist this process by classifying decompiled code as benign or malicious, but existing pipelines typically rely on a single...

Separating Secrets from Placeholders: A Hybrid CNN-CodeBERT Framework for Three-Class Credential Leakage Detection

Credential leakage in public source code repositories poses a critical security threat, with over 23.8 million secrets exposed in 2024 alone. Existing detection tools suffer from high false-positive rates because rigid pattern matching and binary classification schemes fail to distinguish genuine...

Weaponizing the Commons: A Taxonomy and Detection Framework of Abuse on GitHub

GitHub plays a critical role in modern software supply chains, making its security an important research concern. Existing studies have primarily focused on CI/CD automation, collaboration patterns, and community management, while abuse behaviors on GitHub have received little systematic...

A Synthetic Conversational Smishing Dataset for Social Engineering Detection

Smishing SMS phishing has become a serious cybersecurity threat, especially for elderly and cyber-unaware individuals, causing financial loss and undermining user trust. Although prior work has focused on detecting smishing at the level of individual messages, real-world attackers often rely on...

Learning the APT Kill Chain: Temporal Reasoning over Provenance Data for Attack Stage Estimation

Advanced Persistent Threats APTs evolve through multiple stages, each exhibiting distinct temporal and structural behaviors. Accurate stage estimation is critical for enabling adaptive cyber defense. This paper presents StageFinder, a temporal graph learning framework for multi-stage attack...

SafePickle: Robust and Generic ML Detection of Malicious Pickle-Based ML Models

Model repositories such as Hugging Face increasingly distribute machine learning artifacts serialized with Python's pickle format, exposing users to remote code execution RCE risks during model loading. Recent defenses, such as PickleBall, rely on per-library policy synthesis that requires comple...

An Empirical Study of the Imbalance Issue in Software Vulnerability Detection

Vulnerability detection is crucial to protect software security. Nowadays, deep learning DL is the most promising technique to automate this detection task, leveraging its superior ability to extract patterns and representations within extensive code volumes. Despite its promise, DL-based...

Hydra: Robust Hardware-Assisted Malware Detection

Malware detection using Hardware Performance Counters HPCs offers a promising, low-overhead approach for monitoring program behavior. However, a fundamental architectural constraint, that only a limited number of hardware events can be monitored concurrently, creates a significant bottleneck,...