Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/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-2026-17346 is a high-severity SQL Injection (CWE-89) vulnerability in Pgadmin Pgadmin 4. Its CVSS base score is 8.7 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 35th 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.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-51559
Vulnerability Data
The fix for CVE-2026-12044 in pgAdmin 4 9.16 hardened qtLiteral and switched sixteen COMMENT ON / pgstattuple / pgstatindex templates to it, but missed several sinks that had been placed in test_sql_string_literal_lint.py's ALLOWLIST on the incorrect assumption that schema, table,…
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publication, and subscription names sourced from pg_catalog via the browser tree could never contain an apostrophe. PostgreSQL permits arbitrary characters in quoted identifiers, so a low-privileged user able to CREATE TABLE, CREATE PUBLICATION, or CREATE SUBSCRIPTION can plant an apostrophe'd object name that breaks out of the unescaped '{{ name }}' template interpolation the moment any user (including a higher-privileged one) opens that object's Statistics or Dependencies tab, allowing arbitrary SQL statement injection in the viewing user's database session. Affected sinks: the Index Statistics query for all-indexes listing (coll_stats.sql, both the 16_plus and default PostgreSQL-version template variants -- distinct from the single-index stats.sql path already fixed in CVE-2026-12044), and the publication and subscription dependencies.sql / get_position.sql templates (both the pg and ppas/EPAS dialect variants for publications). Fix switches all of these templates to qtLiteral(conn) for name interpolation, and updates publications/__init__.py and subscriptions/__init__.py to pass conn=self.conn into the dependencies.sql render_template call so the qtLiteral filter has a connection to quote against. The corresponding ALLOWLIST entries in test_sql_string_literal_lint.py are removed now that these sinks are properly escaped rather than merely assumed safe. A behavioral regression test renders each fixed template with a stacked-statement apostrophe payload and asserts both that the object name appears exactly as qtLiteral-escaped and that the rendered SQL parses as exactly one statement, verifying the assertion genuinely fails against the pre-patch raw-interpolation form. This issue affects pgAdmin 4: the Index Statistics sink from 1.0, and the Publications/Subscriptions sinks from 5.0, both before 9.17.
- 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.