Raw vector
CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2026-41640 is a high-severity SQL Injection (CWE-89) vulnerability in Nocobase Nocobase. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 23% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as LLM Application Platforms; in the Data-Related Vulnerabilities risk domain.
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.
NocoBase, an AI-powered no-code/low-code platform, is affected by a SQL injection vulnerability (CWE-89) in the queryParentSQL() function of its core database package prior to version 2.0.39. The function builds a recursive CTE by concatenating values from a nodeIds array directly into the query string rather than using parameterized queries, where the array contents are primary keys retrieved from existing database rows.
An attacker with low privileges who can insert a record containing a malicious string primary key can trigger arbitrary SQL execution whenever a subsequent operation performs recursive eager loading against the affected collection. The CVSS 7.5 vector reflects network attack reachability with high complexity but full impact on confidentiality, integrity, and availability.
The issue is addressed in the v2.0.39 release, as documented in the corresponding GitHub commit, pull request, and security advisory GHSA-4948-f92q-f432, which recommend upgrading to the patched version. The associated EPSS score has remained flat at 0.0550 with no indicated rise after disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-28261
Vulnerability Data
NocoBase is an AI-powered no-code/low-code platform for building business applications and enterprise solutions. Prior to version 2.0.39, the queryParentSQL() function in the core database package constructs a recursive CTE query by joining nodeIds with string concatenation instead of using parameterized…
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queries. The nodeIds array contains primary key values read from database rows. An attacker who can create a record with a malicious string primary key can inject arbitrary SQL when any subsequent request triggers recursive eager loading on that collection. This issue has been patched in version 2.0.39.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- 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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V6.2.5
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover SQLi flaws before deployment but does not stop their introduction.
Input validation directly stops untrusted data from reaching SQL query construction without neutralization.
Secure engineering principles require parameterized queries and input sanitization that structurally eliminate SQLi.
System monitoring can identify attempted SQLi exploitation via anomalous queries after the weakness exists.
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 injection flaws during coding and review so largely prevent CWE-89 introduction, yet the single broad outcome leaves residual risk from incomplete neutralization techniques or missed edge cases.
Training raises developer awareness of SQLi risks and can reduce introduction likelihood (partial) but removes none of the actual coding flaw's risk by itself since technical neutralization is still required.
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.
The same secure-coding and static-analysis activities surface missing neutralization of SQL metacharacters before the system is accepted.
Early warnings and shared best-practice information help organizations apply the latest remediation techniques against SQL-injection vulnerabilities.
Threat-intelligence feeds that surface new SQL-injection campaigns enable rapid updates to query-construction defenses and detection signatures before exploitation occurs.
Secure-coding rules and security testing phases mandate the use of parameterized queries or equivalent escaping, preventing the construction of dynamic SQL statements from untrusted input.
Language-specific secure coding rules, peer review and SAST together prevent the construction of SQL statements from untrusted data without proper parameterization or escaping.