163 matches found
CVE-2026-0284 PAN-OS: XML Injection Vulnerability in Large Scale VPN (LSVPN)
An XML injection vulnerability in the Large Scale VPN LSVPN functionality of Palo Alto Networks PAN-OS® software enables an unauthenticated attacker with network access to inject malicious XML content, potentially leading to information disclosure or corruption of internal LSVPN satellite data...
Palo Alto Networks PAN-OS 10.2.x / 11.1.x / 11.2.x / 12.1.x Vulnerability
The version of Palo Alto Networks PAN-OS running on the remote host is a vulnerable version of 10.2.x, 11.1.x, 11.2.x, or 12.1.x. It is, therefore, affected by a vulnerability. An XML injection vulnerability in the Large Scale VPN LSVPN functionality of Palo Alto Networks PAN-OS software enables ...
Palo Alto Networks PAN-OS 10.2.x / 11.1.x / 11.2.x / 12.1.x Vulnerability
The version of Palo Alto Networks PAN-OS running on the remote host is a vulnerable version of 10.2.x, 11.1.x, 11.2.x, or 12.1.x. It is, therefore, affected by a vulnerability. An authentication bypass vulnerability in Large Scale VPN LSVPN functionality of Palo Alto Networks PAN-OS software allo...
FreeType Automated Font Corpus Scanner
This Python framework implements a structured font-analysis pipeline for large-scale robustness testing of FreeType font parsing behavior...
The Fault in Our Drafts: Vulnerabilities in RPKI Specification and Software
The Resource Public Key Infrastructure RPKI secures the Internet's routing system by defining a complex trust and validation framework for certificates, Route Origin Authorizations ROAs, manifests, and Certificate Revocation Lists CRLs. These mechanisms are specified across dozens of RFCs. This...
Ghost CMS CVE-2026-26980 Exploited to Hijack 700+ Sites for ClickFix Attacks
Threat actors are exploiting a recently disclosed critical security flaw in Ghost CMS to inject malicious JavaScript code with an aim to fuel ClickFix attacks. According to QiAnXin XLab, the activity involves the exploitation of CVE-2026-26980 CVSS score: 9.4, an SQL injection vulnerability in...
ADR: An Agentic Detection System for Enterprise Agentic AI Security
We present the Agentic AI Detection and Response ADR system, the first large-scale, production-proven enterprise framework for securing AI agents operating through the Model Context Protocol MCP. We identify three persistent challenges in this domain: 1 limited observability -- existing Endpoint...
Indirect Prompt Injection in the Wild: An Empirical Study of Prevalence, Techniques, and Objectives
As LLMs are increasingly integrated into systems that browse, retrieve, summarize, and act on web content, webpages have become an untrusted input vector for downstream model behavior. This enables site owners, contributors, and adversaries to embed instructions directly in web resources, i.e.,...
VulStyle: A Multi-Modal Pre-Training for Code Stylometry-Augmented Vulnerability Detection
We present VulStyle, a multi-modal software vulnerability detection model that jointly encodes function-level source code, non-terminal Abstract Syntax Tree AST structure, and code stylometry CStyle features. Prior work in code representation primarily leverages token-level models or full AST...
Hackers or Hallucinators? A Comprehensive Analysis of LLM-Based Automated Penetration Testing
The rapid advancement of Large Language Models LLMs has created new opportunities for Automated Penetration Testing AutoPT, spawning numerous frameworks aimed at achieving end-to-end autonomous attacks. However, despite the proliferation of related studies, existing research generally lacks...
Inside an AI‑enabled device code phishing campaign
In this article 1. Attack chain overview 2. Mitigation and protection guidance 3. Indicators of compromise IOC 4. References 5. Learn more Microsoft Defender Security Research has observed a widespread phishing campaign leveraging the Device Code Authentication flow to compromise organizational...
Debt behind the AI Boom: A Large-Scale Empirical Study of AI-Generated Code in the Wild
AI coding assistants are now widely used in software development. Software developers increasingly integrate AI-generated code into their codebases to improve productivity. Prior studies have shown that AI-generated code may contain code quality issues under controlled settings. However, we still...
Policy-Driven Vulnerability Risk Quantification Framework for Large-Scale Cloud Infrastructure Data Security
The exponential growth of Common Vulnerabilities and Exposures CVE disclosures poses significant challenges for enterprise security management, necessitating automated and quantitative risk assessment methodologies. Existing vulnerability analysis approaches suffer from three critical limitations...
When the Abyss Looks Back: Unveiling Evolving Dark Patterns in Cookie Consent Banners
To comply with data protection regulations such as the EU General Data Protection Regulation GDPR and the California Consumer Privacy Act CCPA, websites widely deploy cookie consent banners to collect users' privacy preferences. In practice, however, these interfaces often embed dark patterns tha...
Favia: Forensic Agent for Vulnerability-Fix Identification and Analysis
Identifying vulnerability-fixing commits corresponding to disclosed CVEs is essential for secure software maintenance but remains challenging at scale, as large repositories contain millions of commits of which only a small fraction address security issues. Existing automated approaches, includin...
⚡ Weekly Recap: AI Skill Malware, 31Tbps DDoS, Notepad++ Hack, LLM Backdoors and More
Cyber threats are no longer coming from just malware or exploits. They’re showing up inside the tools, platforms, and ecosystems organizations use every day. As companies connect AI, cloud apps, developer tools, and communication systems, attackers are following those same paths. A clear pattern...
DuoLungo: Usability Study of Duo 2FA
Multi-Factor Authentication MFA enhances login security by requiring multiple authentication factors. Its adoption has increased in response to more frequent and sophisticated attacks. Duo is widely used by organizations including Fortune 500 companies and major educational institutions, yet its...
Okara: Detection and Attribution of TLS Man-In-The-Middle Vulnerabilities in Android Apps with Foundation Models
Transport Layer Security TLS is fundamental to secure online communication, yet vulnerabilities in certificate validation that enable Man-in-the-Middle MitM attacks remain a pervasive threat in Android apps. Existing detection tools are hampered by low-coverage UI interaction, costly...
AEGIS: White-Box Attack Path Generation Using LLMs and Training Effectiveness Evaluation for Large-Scale Cyber Defence Exercises
Creating attack paths for cyber defence exercises requires substantial expert effort. Existing automation requires vulnerability graphs or exploit sets curated in advance, limiting where it can be applied. We present AEGIS, a system that generates attack paths using LLMs, white-box access, and...
