Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:LSummary
CVE-2026-32954 is a high-severity SQL Injection (CWE-89) vulnerability in Frappe Erpnext. Its CVSS base score is 7.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 24th 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-2026-32954 is a blind SQL injection vulnerability affecting ERPNext, a free and open-source Enterprise Resource Planning tool. In versions prior to 16.8.0 and 15.100.0, certain endpoints lack sufficient parameter validation, enabling time-based and boolean-based blind SQL injection attacks that allow attackers to infer sensitive database information. The vulnerability is rated with a CVSS v3.1 base score of 7.1 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:L) and is associated with CWE-89 (SQL Injection). It was published on 2026-03-20.
Attackers with low privileges, such as authenticated users, can exploit this vulnerability remotely over the network with low complexity and no user interaction required. Successful exploitation primarily grants high confidentiality impact by allowing inference of database contents, with a low availability impact possible due to potential query delays from time-based techniques.
The Frappe ERPNext security advisory (GHSA-j669-ghv2-gmqg) and release notes confirm the issue is fixed in versions 15.100.0 and 16.8.0, recommending immediate upgrades for affected installations. Relevant patch details are available in the GitHub release tags for v15.100.0 and v16.8.0.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-13547
Vulnerability Data
ERP is a free and open source Enterprise Resource Planning tool. In versions prior to 16.8.0 and 15.100.0, certain endpoints were vulnerable to time-based and boolean-based blind SQL injection due to insufficient parameter validation, allowing attackers to infer database information.…
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This issue has been fixed in versions 15.100.0 and 16.8.0.
- CWE(s)
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.