CVE-2025-0747
Published: 30 January 2025
Summary
CVE-2025-0747 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Thesamur Embedai. Its CVSS base score is 8.6 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique JavaScript (T1059.007); ranked at the 26.0th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified are NIST 800-53 SI-10 (Information Input Validation) and SI-15 (Information Output Filtering).
Deeper analysis
CVE-2025-0747 is a Stored Cross-Site Scripting (XSS) vulnerability, classified under CWE-79, affecting EmbedAI. Published on 2025-01-30, it carries a CVSS v3.1 base score of 8.6 (AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N). The issue enables injection of malicious JavaScript code into a message within the application.
An authenticated attacker can exploit this vulnerability by injecting malicious JavaScript into a message, which executes in the context of another user's browser when they open the chat. This leads to high-impact confidentiality violations through cross-origin data exfiltration, leveraging the changed scope.
Mitigation details are available in the INCIBE-CERT advisory on multiple vulnerabilities in EmbedAI at https://www.incibe.es/en/incibe-cert/notices/aviso/multiple-vulnerabilities-embedai.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-1851
- 🇪🇸 INCIBE: www.incibe.es
Vulnerability details
A Stored Cross-Site Scripting vulnerability has been found in EmbedAI. This vulnerability allows an authenticated attacker to inject a malicious JavaScript code into a message that will be executed when a user opens the chat.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Stored XSS allows authenticated attackers to inject arbitrary JavaScript into chat messages, enabling execution in victims' browsers upon viewing the chat (Command and Scripting Interpreter: JavaScript).
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Directly prevents authenticated attackers from injecting malicious JavaScript into stored messages by enforcing input validation mechanisms.
Prevents execution of injected JavaScript in victims' browsers by filtering and encoding chat message output during rendering.
Addresses the root cause of the stored XSS vulnerability in EmbedAI through timely flaw remediation and patching.