CVE-2025-55006
Frappe Learning 2.0.0 – 2.34.0
Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:U/C:L/I:L/A:LCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2025-55006 is a medium-severity Improper Input Validation (CWE-20) vulnerability in Frappe Learning. Its CVSS base score is 4.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 18th 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-2025-55006 is an improper input validation vulnerability (CWE-20) in Frappe Learning, a learning management system for structuring content. It affects versions 2.33.0 and below, specifically in the image upload functionality, which fails to adequately sanitize uploaded SVG files. This allows attackers to upload SVGs containing embedded JavaScript or other malicious content.
The vulnerability has a CVSS v3.1 base score of 4.3 (AV:N/AC:L/PR:H/UI:R/S:U/C:L/I:L/A:L). Exploitation requires an authenticated attacker with high privileges to upload a malicious SVG via the image upload feature. When other users view or interact with the uploaded image, the embedded scripts execute in the victim's browser context, enabling arbitrary script execution such as cross-site scripting (XSS).
The GitHub security advisory (GHSA-mvxw-r9x4-3vrr) documents the issue. Mitigation involves upgrading to version 2.34.0, where a fix is planned.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-24031
Vulnerability Data
Frappe Learning is a learning system that helps users structure their content. In versions 2.33.0 and below, the image upload functionality did not adequately sanitize uploaded SVG files. This allowed users to upload SVG files containing embedded JavaScript or other…
more
potentially malicious content. Malicious SVG files could be used to execute arbitrary scripts in the context of other users. A fix for this issue is planned for version 2.34.0.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
—
—
- 6 hardening rules · 3 OS baselines
—
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover missing input validation through analysis or test cases.
SI-10 directly requires validity checks on information inputs, structurally preventing improper or missing validation.
Requiring documented development standards and tools can embed input-validation practices into the engineering process.
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 require and enforce input validation during development.
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.
Testing against a defined set of requirements and using code review plus vulnerability scanning forces validation of inputs and handling of unanticipated conditions, reducing the chance that malformed data will be accepted.
Secure-coding guidelines and mandatory security testing (including code scans) compel developers to validate and sanitize inputs at design and implementation time, lowering the incidence of malformed or malicious data reaching downstream components.
Mandating input controls that include integrity checks and input validation ensures that untrusted data is examined before use, blocking the root cause of many injection and malformed-data weaknesses.
Security-by-design principles explicitly call for data validation and sanitization at every layer, reducing the chance that malformed or malicious input will be processed without scrutiny.
Requiring language-specific secure coding standards, peer review, SAST and documented mitigation of common programming errors forces validation of all inputs before they are trusted.
Hardening callouts derived
Configuration rules from DISA STIG baselines that bear on weaknesses of the type cited by this CVE. Each rule is shown with the relationship its mapping actually records, against the CWE it was authored against. Derived via CVE→CWE over `controls_xwalks` (authoritative rows only; rows rated `none` are excluded).
RHEL 8 (1 rule)
- V-230265 RHEL 8 must prevent the installation of software, patches, service packs, device drivers, or operating system components of local packages without verification they have been digitally signed using a certificate that is issued by a Certificate Authority (CA) that is recognized and approved by the organization. prevents CWE-20