CVE-2026-21913

An Incorrect Initialization of Resource vulnerability in the Internal Device Manager IDM of Juniper Networks Junos OS on EX4000 models allows an unauthenticated, network-based attacker to cause a Denial-of-Service DoS. On EX4000 models with 48 ports EX4000-48T, EX4000-48P, EX4000-48MP a high volu...

CVE-2026-21913

CVE-2026-21913 affects Juniper Networks Junos OS on EX4000-48T, EX4000-48P and EX4000-48MP. The vulnerability is an incorrect initialization of the Internal Device Manager (IDM) that allows an unauthenticated, network-based attacker to cause a Denial-of-Service (DoS). A high volume of traffic dir...

EUVD-2026-2664

A potential vulnerability was reported in the BIOS of L13 Gen 6, L13 Gen 6 2-in-1, L14 Gen 6, and L16 Gen 2 ThinkPads which could result in Secure Boot being disabled even when configured as “On” in the BIOS setup menu. This issue only affects systems where Secure Boot is set to User Mode...

Multi-Agent Taint Specification Extraction for Vulnerability Detection

Static Application Security Testing SAST tools using taint analysis are widely viewed as providing higher-quality vulnerability detection results compared to traditional pattern-based approaches. However, performing static taint analysis for JavaScript poses two major challenges. First,...

Blue Teaming Function-Calling Agents

We present an experimental evaluation that assesses the robustness of four open source LLMs claiming function-calling capabilities against three different attacks, and we measure the effectiveness of eight different defences. Our results show how these models are not safe by default, and how the...

CVE-2026-0853

Certain NVR models developed by A-Plus Video Technologies has a Sensitive Data Exposure vulnerability, allowing unauthenticated remote attackers to access the debug page and obtain device status information...

GHSA-GRG2-63FW-F2QR vLLM is vulnerable to DoS in Idefics3 vision models via image payload with ambiguous dimensions

Summary Users can crash the vLLM engine serving multimodal models that use the Idefics3 vision model implementation by sending a specially crafted 1x1 pixel image. This causes a tensor dimension mismatch that results in an unhandled runtime error, leading to complete server termination. Details T...

Data broker fined after selling Alzheimer’s patient info and millions of sensitive profiles

California's privacy regulator has fined a Texas data broker $45,000 and banned it from selling Californians' personal information after it sold Alzheimer patients' data. Texan company Rickenbacher Data LLC, which does business as Datamasters, bought and resold the names, addresses, phone numbers...

CVE-2026-22755 Legacy Vivotek Camera Firmware Command Injection in upload_map.cgi

Improper Neutralization of Special Elements used in a Command 'Command Injection' vulnerability in Vivotek Affected device model numbers are FD8365, FD8365v2, FD9165, FD9171, FD9187, FD9189, FD9365, FD9371, FD9381, FD9387, FD9389, FD9391,FE9180,FE9181, FE9191, FE9381, FE9382, FE9391, FE9582,...

EUVD-2026-2345

Improper Neutralization of Special Elements used in a Command 'Command Injection' vulnerability in Vivotek Affected device model numbers are FD8365, FD8365v2, FD9165, FD9171, FD9187, FD9189, FD9365, FD9371, FD9381, FD9387, FD9389, FD9391,FE9180,FE9181, FE9191, FE9381, FE9382, FE9391, FE9582,...

CVE-2026-22755

CVE-2026-22755 is a command-injection flaw in Vivotek legacy firmware (upload_map.cgi) that allows OS command execution as root on multiple camera models. Affected devices include FD8365, FD8365v2, FD9165, FD9171, FD9187, FD9189, FD9365, FD9371, FD9381, FD9387, FD9389, FD9391, FE9180, FE9181, FE9...

Proactively Detecting Threats: A Novel Approach Using LLMs

Enterprise security faces escalating threats from sophisticated malware, compounded by expanding digital operations. This paper presents the first systematic evaluation of large language models LLMs to proactively identify indicators of compromise IOCs from unstructured web-based threat...

LLMs in Code Vulnerability Analysis: A Proof of Concept

Context: Traditional software security analysis methods struggle to keep pace with the scale and complexity of modern codebases, requiring intelligent automation to detect, assess, and remediate vulnerabilities more efficiently and accurately. Objective: This paper explores the incorporation of...

Deep Learning-Based Binary Analysis for Vulnerability Detection in X86-64 Machine Code

While much of the current research in deep learning-based vulnerability detection relies on disassembled binaries, this paper explores the feasibility of extracting features directly from raw x86-64 machine code. Although assembly language is more interpretable for humans, it requires more comple...

PT-2026-2794

Name of the Vulnerable Software and Affected Versions Vivotek devices versions 0100a through 012502 Description The affected devices contain an Improper Neutralization of Special Elements used in a Command 'Command Injection' issue. This allows for potential OS Command Injection through the uploa...

Memory-Based Malware Detection under Limited Data Conditions: A Comparative Evaluation of TabPFN and Ensemble Models

Artificial intelligence and machine learning have significantly advanced malware research by enabling automated threat detection and behavior analysis. However, the availability of exploitable data is limited, due to the absence of large datasets with real-world data. Despite the progress of AI i...

PT-2026-2043

Name of the Vulnerable Software and Affected Versions A-Plus Video Technologies NVR models affected versions not specified Description A security issue exists in certain NVR models developed by A-Plus Video Technologies that allows unauthenticated remote attackers to access the debug page...

PYSEC-2026-143

vLLM is an inference and serving engine for large language models LLMs. In versions from 0.6.4 to before 0.12.0, users can crash the vLLM engine serving multimodal models that use the Idefics3 vision model implementation by sending a specially crafted 1x1 pixel image. This causes a tensor dimensi...

CVE-2026-22773

vLLM is an inference and serving engine for large language models LLMs. In versions from 0.6.4 to before 0.12.0, users can crash the vLLM engine serving multimodal models that use the Idefics3 vision model implementation by sending a specially crafted 1x1 pixel image. This causes a tensor dimensi...

PYSEC-2026-143

vLLM is an inference and serving engine for large language models LLMs. In versions from 0.6.4 to before 0.12.0, users can crash the vLLM engine serving multimodal models that use the Idefics3 vision model implementation by sending a specially crafted 1x1 pixel image. This causes a tensor dimensi...