Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:H/UI:N/VC:H/VI:H/VA:H/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-2026-33539 is a high-severity SQL Injection (CWE-89) vulnerability in Parseplatform Parse-Server. Its CVSS base score is 8.6 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 37th 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-2026-33539 is a SQL injection vulnerability (CWE-89) in Parse Server, an open-source backend deployable on any Node.js-compatible infrastructure. It affects Parse Server versions prior to 8.6.59 and 9.6.0-alpha.53 when using PostgreSQL as the database backend. The flaw arises from insufficient sanitization, allowing SQL metacharacters to be injected into field name parameters of the aggregate $group pipeline stage or the distinct operation, enabling arbitrary SQL statement execution on the underlying PostgreSQL database. MongoDB deployments remain unaffected.
Exploitation requires an attacker to possess master key access to Parse Server, aligning with the high privileges required (PR:H) in its CVSS v3.1 base score of 7.2 (AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H). With this access, an attacker can craft requests to inject malicious SQL, resulting in privilege escalation from Parse Server application-level administrator rights to full PostgreSQL database-level access, potentially allowing data exfiltration, modification, or destruction.
The issue has been patched in Parse Server versions 8.6.59 and 9.6.0-alpha.53, as detailed in the GitHub security advisory GHSA-p2w6-rmh7-w8q3 and associated commits and pull requests (e.g., #10272, #10273). Security practitioners should prioritize upgrading affected PostgreSQL-based deployments to these versions for mitigation.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-14976
Vulnerability Data
Parse Server is an open source backend that can be deployed to any infrastructure that can run Node.js. Prior to versions 8.6.59 and 9.6.0-alpha.53, an attacker with master key access can execute arbitrary SQL statements on the PostgreSQL database by…
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injecting SQL metacharacters into field name parameters of the aggregate $group pipeline stage or the distinct operation. This allows privilege escalation from Parse Server application-level administrator to PostgreSQL database-level access. Only Parse Server deployments using PostgreSQL are affected. MongoDB deployments are not affected. This issue has been patched in versions 8.6.59 and 9.6.0-alpha.53.
- 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.