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Technical details The problem comes from weak authentication in two different CCX components. CVE-2025-20354 targets the Java RMI service. CCX exposes this service to accept remote data, but it does not properly check who is sending it. That means an attacker can upload a specially crafted file and run commands on the underlying operating system.…

The post Cisco Unified CCX Remote Code Execution Vulnerabilities (CVE-2025-20354, CVE-2025-20358) appeared first on Sentrium Security.

The post Cisco Unified CCX Remote Code Execution Vulnerabilities (CVE-2025-20354, CVE-2025-20358) appeared first on Security Boulevard.

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In 2025, stolen credentials remain the most common and fastest path into an organization’s systems. Nearly half of breaches begin with compromised logins. The 2025 Verizon Data Breach Investigations Report puts it bluntly: “Hackers don’t break in anymore, they log in.” Web application attacks have followed suit, with 88% now using stolen credentials as the..

The post Stop Paying the Password Tax: A CFO’s Guide to Affordable Zero-Trust Access appeared first on Security Boulevard.

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SESSION
Session 2B: Web Security

Authors, Creators & Presenters: Aleksei Stafeev (CISPA Helmholtz Center for Information Security), Tim Recktenwald (CISPA Helmholtz Center for Information Security), Gianluca De Stefano (CISPA Helmholtz Center for Information Security), Soheil Khodayari (CISPA Helmholtz Center for Information Security), Glancarlo Pellegrino (CISPA Helmholtz Center for Information Security)

PAPER
YuraScanner: Leveraging LLMs for Task-driven Web App Scanning
Web application scanners are popular and effective black-box testing tools, automating the detection of vulnerabilities by exploring and interacting with user interfaces. Despite their effectiveness, these scanners struggle with discovering deeper states in modern web applications due to their limited understanding of workflows. This study addresses this limitation by introducing YuraScanner, a task-driven web application scanner that leverages large-language models (LLMs) to autonomously execute tasks and workflows.
YuraScanner operates as a goal-based agent, suggesting actions to achieve predefined objectives by processing webpages to extract semantic information. Unlike traditional methods that rely on user-provided traces, YuraScanner uses LLMs to bridge the semantic gap, making it web application-agnostic. Using the XSS engine of Black Widow, YuraScanner tests discovered input points for vulnerabilities, enhancing the scanning process's comprehensiveness and accuracy.
We evaluated YuraScanner on 20 diverse web applications, focusing on task extraction, execution accuracy, and vulnerability detection. The results
demonstrate YuraScanner's superiority in discovering new attack surfaces and deeper states, significantly improving vulnerability detection. Notably,
YuraScanner identified 12 unique zero-day XSS vulnerabilities, compared to three by Black Widow. This study highlights YuraScanner's potential to
revolutionize web application scanning with its automated, task-driven approach.

Our thanks to the Network and Distributed System Security (NDSS) Symposium for publishing their Creators, Authors and Presenter’s superb NDSS Symposium 2025 Conference content on the organization’s’ YouTube channel.

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The post NDSS 2025 – YuraScanner: Leveraging LLMs For Task-driven Web App Scanning4+ appeared first on Security Boulevard.