Context-Aware Phishing Email Detection Using Machine Learning and NLP

Phishing attacks remain among the most prevalent cybersecurity threats, causing significant financial losses for individuals and organizations worldwide. This paper presents a machine learning-based phishing email detection system that analyzes email body content using natural language processing...

Detecting Protracted Vulnerabilities in Open Source Projects

Timely resolution and disclosure of vulnerabilities are essential for maintaining the security of open-source software. However, many vulnerabilities remain unreported, unpatched, or undisclosed for extended periods, exposing users to prolonged security threats. While various vulnerability...

Machine Learning Transferability for Malware Detection

Malware continues to be a predominant operational risk for organizations, especially when obfuscation techniques are used to evade detection. Despite the ongoing efforts in the development of Machine Learning ML detection approaches, there is still a lack of feature compatibility in public...

TLS Certificate and Domain Feature Analysis of Phishing Domains in the Danish .Dk Namespace

Phishing attacks remain a persistent cybersecurity threat, and the widespread adoption of TLS certificates has unintentionally enabled malicious websites to appear trustworthy to users. This study examines whether certificate metadata and domain characteristics can help distinguish phishing domai...

AEGIS: From Clues to Verdicts -- Graph-Guided Deep Vulnerability Reasoning Via Dialectics and Meta-Auditing

Large Language Models LLMs are increasingly adopted for vulnerability detection, yet their reasoning remains fundamentally unsound. We identify a root cause shared by both major mitigation paradigms agent-based debate and retrieval augmentation: reasoning in an ungrounded deliberative space that...

CVE-2026-33147

A flaw was found in GMT Generic Mapping Tools, an open-source collection of command-line tools. This vulnerability, a stack-based buffer overflow, occurs when a specially crafted long string is used as a dataset identifier. An attacker could exploit this to cause the application to crash or...

CVE-2026-33147

GMT is an open source collection of command-line tools for manipulating geographic and Cartesian data sets. In versions from 6.6.0 and prior, a stack-based buffer overflow vulnerability was identified in the gmtremotedatasetid function within src/gmtremote.c. This issue occurs when a specially...

CVE-2026-33147

GMT is an open-source suite of CLI tools for geographic/Cartesian data. A stack-based buffer overflow was identified in the gmt_remote_dataset_id function (src/gmt_remote.c) affecting versions up to 6.6.0. Trigger occurs when a specially crafted long string is passed as a dataset identifier (e.g....

CVE-2026-33147

GMT is an open source collection of command-line tools for manipulating geographic and Cartesian data sets. In versions from 6.6.0 and prior, a stack-based buffer overflow vulnerability was identified in the gmtremotedatasetid function within src/gmtremote.c. This issue occurs when a specially...

CVE-2026-33147 GMT: Stack-based Buffer Overflow in gmt_remote_dataset_id

GMT is an open source collection of command-line tools for manipulating geographic and Cartesian data sets. In versions from 6.6.0 and prior, a stack-based buffer overflow vulnerability was identified in the gmtremotedatasetid function within src/gmtremote.c. This issue occurs when a specially...

CVE-2026-33147 GMT: Stack-based Buffer Overflow in gmt_remote_dataset_id

GMT is an open source collection of command-line tools for manipulating geographic and Cartesian data sets. In versions from 6.6.0 and prior, a stack-based buffer overflow vulnerability was identified in the gmtremotedatasetid function within src/gmtremote.c. This issue occurs when a specially...

CVE-2026-33147 GMT: Stack-based Buffer Overflow in gmt_remote_dataset_id

GMT is an open source collection of command-line tools for manipulating geographic and Cartesian data sets. In versions from 6.6.0 and prior, a stack-based buffer overflow vulnerability was identified in the gmtremotedatasetid function within src/gmtremote.c. This issue occurs when a specially...

EUVD-2026-13784

GMT is an open source collection of command-line tools for manipulating geographic and Cartesian data sets. In versions from 6.6.0 and prior, a stack-based buffer overflow vulnerability was identified in the gmtremotedatasetid function within src/gmtremote.c. This issue occurs when a specially...

Generic Mapping Tools 安全漏洞

The Generic Mapping Tools is an open-source set of geographic data mapping and processing tools. Versions of Generic Mapping Tools 6.6.0 and earlier contain security vulnerabilities. These vulnerabilities stem from the gmtremotedatasetid function, which handles specially crafted long strings and...

PT-2026-26669

GMT is an open source collection of command-line tools for manipulating geographic and Cartesian data sets. In versions from 6.6.0 and prior, a stack-based buffer overflow vulnerability was identified in the gmt remote dataset id function within src/gmt remote.c. This issue occurs when a speciall...

Cyber-Resilient Digital Twins: Discriminating Attacks for Safe Critical Infrastructure Control

Industrial Cyber-Physical Systems ICPS face growing threats from cyber-attacks that exploit sensor and control vulnerabilities. Digital Twin DT technology can detect anomalies via predictive modelling, but current methods cannot distinguish attack types and often rely on costly full-system...

A Novel Solution for Zero-Day Attack Detection in IDS Using Self-Attention and Jensen-Shannon Divergence in WGAN-GP

The increasing sophistication of cyber threats, especially zero-day attacks, poses a significant challenge to cybersecurity. Zero-day attacks exploit unknown vulnerabilities, making them difficult to detect and defend against. Existing approaches patch flaws and deploy an Intrusion Detection Syst...

Exploit for Uncontrolled Resource Consumption in Siemens 6Bk1602-0Aa12-0Tp0_Firmware

AetherGuard Security Test Dataset !License: MIThttps://im...

Incremental Federated Learning for Intrusion Detection in IoT Networks under Evolving Threat Landscape

The expansion of Internet of Things IoT devices has increased the attack surface of networks, necessitating a robust and adaptive intrusion detection systems. Machine learning based systems have been considered promising in enhancing the detection performance. Federated learning settings enabled ...

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...