Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2025-65267 is a critical-severity Cross-site Scripting (CWE-79) vulnerability in Frappe Erpnext. Its CVSS base score is 9.0 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 26th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2025-65267, published on 2025-12-03, is a stored cross-site scripting (XSS) vulnerability (CWE-79) affecting ERPNext version 15.83.2 and Frappe Framework version 15.86.0. The issue arises from improper validation of uploaded SVG avatar images, which allows attackers to embed malicious JavaScript payloads within these files.
An attacker with low-privilege network access (PR:L) can exploit this by uploading a specially crafted SVG avatar containing JavaScript. The payload remains stored and executes only when an administrator clicks the image link to view the avatar, requiring user interaction (UI:R) but enabling a scoped impact (S:C). Successful exploitation can result in high confidentiality, integrity, and availability impacts (C:H/I:H/A:H), potentially leading to administrator account takeover, privilege escalation, or full compromise of the affected ERPNext instance. The vulnerability carries a CVSS v3.1 base score of 9.0 (AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:H).
Mitigation details and potential patches can be found in the referenced advisories, including the proof-of-concept repository at https://github.com/PhDg1410/CVE/tree/main/CVE-2025-65267 and the official project repositories at https://github.com/frappe/erpnext and https://github.com/frappe/frappe.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-200968
Vulnerability Data
In ERPNext v15.83.2 and Frappe Framework v15.86.0, improper validation of uploaded SVG avatar images allows attackers to embed malicious JavaScript. The payload executes when an administrator clicks the image link to view the avatar, resulting in stored cross-site scripting (XSS).…
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Successful exploitation may lead to account takeover, privilege escalation, or full compromise of the affected ERPNext instance.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.1.2V1.3.2
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover missing or incorrect input neutralization through targeted web-application tests.
Input validation directly enforces neutralization of untrusted data before it reaches web output generation.
Output filtering can catch or sanitize unneutralized script content before it is served to users.
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.