CVE-2026-33909

OpenEMR prior to v8.0.0.3 is vulnerable to SQL injection in the MedEx recall/reminder processing code, where several variables are concatenated directly into SQL queries without parameterization or type casting. The issue affects components used for recall/reminder processing; CVE-2026-33909 is m...

CVE-2026-33909 OpenEMR Vulnerable to SQL Injection via Unsanitized Variables in MedEx Recall/Reminder Processing

OpenEMR is a free and open source electronic health records and medical practice management application. Prior to version 8.0.0.3, several variables in the MedEx recall/reminder processing code are concatenated directly into SQL queries without parameterization or type casting, enabling SQL...

CVE-2026-33909 OpenEMR Vulnerable to SQL Injection via Unsanitized Variables in MedEx Recall/Reminder Processing

OpenEMR is a free and open source electronic health records and medical practice management application. Prior to version 8.0.0.3, several variables in the MedEx recall/reminder processing code are concatenated directly into SQL queries without parameterization or type casting, enabling SQL...

EUVD-2026-16014

OpenEMR is a free and open source electronic health records and medical practice management application. Prior to version 8.0.0.3, several variables in the MedEx recall/reminder processing code are concatenated directly into SQL queries without parameterization or type casting, enabling SQL...

PT-2026-28138

Name of the Vulnerable Software and Affected Versions OpenEMR versions prior to 8.0.0.3 Description OpenEMR is an electronic health records and medical practice management application. Versions prior to 8.0.0.3 contain a flaw where variables used in the MedEx recall/reminder processing code are...

Mining the YARA Ecosystem: From Ad-Hoc Sharing to Data-Driven Threat Intelligence

YARA has established itself as the de facto standard for "Detection as Code," enabling analysts and DevSecOps practitioners to define signatures for malware identification across the software supply chain. Despite its pervasive use, the open-source YARA ecosystem remains characterized by ad-hoc...

MemoPhishAgent: Memory-Augmented Multi-Modal LLM Agent for Phishing URL Detection

Traditional phishing website detection relies on static heuristics or reference lists, which lag behind rapidly evolving attacks. While recent systems incorporate large language models LLMs, they are still prompt-based, deterministic pipelines that underutilize reasoning capability. We present...

MultiVer: Zero-Shot Multi-Agent Vulnerability Detection

We present MultiVer, a zero-shot multi-agent system for vulnerability detection that achieves state-of-the-art recall without fine-tuning. A four-agent ensemble security, correctness, performance, style with union voting achieves 82.7% recall on PyVul, exceeding fine-tuned GPT-3.5 81.3% by 1.4...

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...

TRACE: Timely Retrieval and Alignment for Cybersecurity Knowledge Graph Construction and Expansion

The rapid evolution of cyber threats has highlighted significant gaps in security knowledge integration. Cybersecurity Knowledge Graphs CKGs relying on structured data inherently exhibit hysteresis, as the timely incorporation of rapidly evolving unstructured data remains limited, potentially...

Evaluating Large Language Models for Security Bug Report Prediction

Early detection of security bug reports SBRs is critical for timely vulnerability mitigation. We present an evaluation of prompt-based engineering and fine-tuning approaches for predicting SBRs using Large Language Models LLMs. Our findings reveal a distinct trade-off between the two approaches...

CVE-2025-1325

The WP-Recall – Registration, Profile, Commerce & More plugin for WordPress is vulnerable to arbitrary shortcode execution due to a missing capability check on the 'rclpreviewpost' AJAX endpoint in all versions up to, and including, 16.26.10. This makes it possible for authenticated attackers, wi...

CVE-2025-1323

The WP-Recall – Registration, Profile, Commerce & More plugin for WordPress is vulnerable to SQL Injection via the 'databeat' parameter in all versions up to, and including, 16.26.10 due to insufficient escaping on the user supplied parameter and lack of sufficient preparation on the existing SQL...

Unity Linux 20.1060a / 20.1070a Security Update: kernel (UTSA-2025-993232)

The Unity Linux 20 host has a package installed that is affected by a vulnerability as referenced in the UTSA-2025-993232 advisory. In the Linux kernel, the following vulnerability has been resolved: nfsd: decrease sccount directly if fail to queue dlrecall A deadlock warning occurred when invoki...

Unity Linux 20.1060e / 20.1070e Security Update: kernel (UTSA-2025-992326)

The Unity Linux 20 host has a package installed that is affected by a vulnerability as referenced in the UTSA-2025-992326 advisory. In the Linux kernel, the following vulnerability has been resolved: nfsd: decrease sccount directly if fail to queue dlrecall A deadlock warning occurred when invoki...

Unity Linux 20.1060e / 20.1070e Security Update: kernel (UTSA-2025-992477)

The Unity Linux 20 host has a package installed that is affected by a vulnerability as referenced in the UTSA-2025-992477 advisory. In the Linux kernel, the following vulnerability has been resolved: nfsd: put dlstid if fail to queue dlrecall Before calling nfsd4runcb to queue dlrecall to the...

Beyond Single Bugs: Benchmarking Large Language Models for Multi-Vulnerability Detection

Large Language Models LLMs have demonstrated significant potential in automated software security, particularly in vulnerability detection. However, existing benchmarks primarily focus on isolated, single-vulnerability samples or function-level classification, failing to reflect the complexity of...

AutoDFBench 1.0: A Benchmarking Framework for Digital Forensic Tool Testing and Generated Code Evaluation

The National Institute of Standards and Technology NIST Computer Forensic Tool Testing CFTT programme has become the de facto standard for providing digital forensic tool testing and validation. However to date, no comprehensive framework exists to automate benchmarking across the diverse forensi...

Injecting Falsehoods: Adversarial Man-In-The-Middle Attacks Undermining Factual Recall in LLMs

LLMs are now an integral part of information retrieval. As such, their role as question answering chatbots raises significant concerns due to their shown vulnerability to adversarial man-in-the-middle MitM attacks. Here, we propose the first principled attack evaluation on LLM factual memory unde...

The king is dead, long live the king! Windows 10 EOL and Windows 11 forensic artifacts

Introduction Windows 11 was released a few years ago, yet it has seen relatively weak enterprise adoption. According to statistics from our Global Emergency Response Team GERT investigations, as recently as early 2025, we found that Windows 7, which reached end of support in 2020, was encountered...