CVE-2025-66258
XSS in Dbbroadcast Mozart Next 6000 Firmware
Raw vector
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:P/VC:H/VI:L/VA:L/SC:H/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2025-66258 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Dbbroadcast Mozart Next 6000 Firmware. Its CVSS base score is 7.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 9th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to SI-10 (Information Input Validation) and SI-15 (Information Output Filtering) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-199674
Vulnerability Data
Stored Cross-Site Scripting via XML Injection in DB Electronica Telecomunicazioni S.p.A. Mozart FM Transmitter versions 30, 50, 100, 300, 500, 1000, 2000, 3000, 3500, 6000, 7000 allows an attacker to perform Stored XSS via crafted filenames injected into patchlist.xml. User-controlled…
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filenames are directly concatenated into `patchlist.xml` without encoding, allowing injection of malicious JavaScript payloads via crafted filenames (e.g., `<img src=x onerror=alert()>.bin`). The XSS executes when ajax.js processes and renders the XML file.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Stored XSS via unsanitized filename injection into XML directly enables exploitation of the device's web interface (T1190) and arbitrary JavaScript execution in the admin browser context (T1059.007).
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Requires validation and sanitization of untrusted input (filenames) before concatenation into patchlist.xml, directly blocking the XML/JS injection vector.
Mandates filtering of information outputs when ajax.js renders the stored XML, neutralizing malicious payloads before browser execution.
Provides integrity verification of the generated patchlist.xml file, enabling detection of unauthorized script content injected via filenames.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly target introduction of XSS via coding standards/testing (mostly), yet the single broad outcome leaves many specific neutralization vectors unaddressed (partial).
Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.
Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.
Operational indicators of compromise for web-application attacks can be incorporated into WAF or input-filtering rules, lowering the likelihood that unsanitized data reaches the browser.
Requiring language-specific secure-coding standards and automated scanning during the SDLC catches missing output encoding or improper neutralization of untrusted data before the software reaches production.
Secure-coding standards, SAST scans and removal of insecure code samples together eliminate the failure to neutralize script content that produces cross-site scripting flaws.
Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.