Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:LSummary
CVE-2026-34563 is a critical-severity Cross-site Scripting (CWE-79) vulnerability in Ci4-Cms-Erp Ci4Ms. Its CVSS base score is 9.1 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 19th 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 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-2026-34563 is a stored blind cross-site scripting (XSS) vulnerability (CWE-79) affecting CI4MS, a CodeIgniter 4-based CMS skeleton providing production-ready modular architecture with RBAC authorization and theme support. In versions prior to 0.31.0.0, the application does not properly sanitize user-controlled input during backup upload handling and metadata processing. This allows injection of a malicious JavaScript payload into the backup filename, such as via an uploaded file named xss.sql, which leverages SQL functionality to insert the payload server-side. The stored payload is then rendered without proper output encoding in multiple backup management views. The vulnerability carries a CVSS v3.1 base score of 9.1 (AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:L).
An authenticated attacker with low privileges (PR:L) can exploit this issue remotely over the network with low complexity and no user interaction required. By uploading a specially crafted backup file containing the XSS payload in its filename, the attacker triggers server-side SQL insertion of the payload. When administrators or other users view affected backup management interfaces, the unsafely rendered payload executes in their browsers, enabling theft of session cookies, keystrokes, or other sensitive data due to the changed scope (S:C) and high confidentiality impact (C:H).
The issue has been addressed in CI4MS version 0.31.0.0, as detailed in the project's GitHub release notes and security advisory (GHSA-85m8-g393-jcxf). Security practitioners should upgrade to the patched version and review backup upload functionalities for similar input sanitization gaps.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-18075
Vulnerability Data
CI4MS is a CodeIgniter 4-based CMS skeleton that delivers a production-ready, modular architecture with RBAC authorization and theme support. Prior to version 0.31.0.0, the application fails to properly sanitize user-controlled input when handling backup uploads and processing backup metadata. An…
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attacker can inject a malicious JavaScript payload into the backup filename via the uploaded xss.sql, which uses SQL functionality to insert the XSS payload server-side. This stored payload is later rendered unsafely in multiple backup management views without proper output encoding, leading to stored blind cross-site scripting (Blind XSS). This issue has been patched in version 0.31.0.0.
- 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.
Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.