CVE-2026-39424
Maxkb ≤ 2.8.0
Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:L/SC:N/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-2026-39424 is a medium-severity Improper Neutralization of Formula Elements in a CSV File (CWE-1236) vulnerability in Maxkb Maxkb. Its CVSS base score is 5.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique User Execution (T1204); ranked at the 30th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as Enterprise AI Assistants; in the Data-Related Vulnerabilities risk domain.
The strongest mitigations our analysis identified map to SI-15 (Information Output Filtering) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-22186
Vulnerability Data
MaxKB is an open-source AI assistant for enterprise. In versions 2.7.1 and below, the chat export feature is vulnerable to Improper Neutralization of Formula Elements in a CSV File. When an administrator exports the application chat history to an Excel…
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file (.xlsx) via the /admin/api/workspace/{workspace_id}/application/{application_id}/chat/export endpoint, strings starting with formula characters are written directly without proper sanitization. Opening this file in spreadsheet applications like Microsoft Excel can lead to Arbitrary Code Execution (RCE) on the administrator's workstation via Dynamic Data Exchange (DDE). The issue is a variant of CVE-2025-4546, which fixed the exact same pattern in apps/dataset/serializers/document_serializers.py but missed the application chat export sink. This issue has been fixed in version 2.8.0.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Enterprise AI Assistants
- Risk Domain
- Data-Related Vulnerabilities
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: ai
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.2.10
Mitigating Controls (NIST 800-53 r5) AI
Output filtering/validation directly stops unneutralized formula elements from being written into CSV files.
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 output neutralization for untrusted CSV content to block formula injection.
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.
Security testing in development can detect formula injection but does not itself implement the mitigation.
Secure SDLC mandates input validation and output encoding that directly prevents formula injection in CSV exports.
Application security requirements include rules for safe CSV generation and handling of untrusted data.
Secure architecture principles encourage safe data export design but do not specifically address CSV formula neutralization.
Secure coding standards explicitly require neutralization of special characters when writing CSV files.