CVE-2023-26750
SQLi in Yiiframework Yii 2.0.0 – 2.0.47
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2023-26750 is a critical-severity SQL Injection (CWE-89) vulnerability in Yiiframework Yii. Its CVSS base score is 9.8 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); 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.
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-2023-26750 is a SQL injection vulnerability in the Yii 2 Framework prior to version 2.0.47 that permits remote code execution through the runAction function. The issue is tracked under CWE-89 and CWE-79 and carries a CVSS 3.1 base score of 9.8. The framework maintainers have stated that the flaw resides in third-party code rather than the Yii codebase itself.
An unauthenticated remote attacker can invoke runAction over the network to inject SQL and achieve arbitrary code execution, resulting in full confidentiality, integrity, and availability impact on affected installations.
Public discussion of the issue is contained in the referenced GitHub issue thread, which includes maintainer comments reiterating that the root cause lies outside the framework and providing guidance on responsible disclosure and patching of the implicated third-party component. The associated EPSS score reached a peak of 0.1364 and currently stands at 0.1102.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-1313
Vulnerability Data
SQL injection vulnerability found in Yii Framework Yii 2 Framework before v.2.0.47 allows the a remote attacker to execute arbitrary code via the runAction function. NOTE: the software maintainer's position is that the vulnerability is in third-party code, not in…
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the framework.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.1.2V1.3.2V6.2.5
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Penetration testing submits XSS payloads to web applications, detecting cross-site scripting flaws for subsequent remediation.
Validates web inputs to reject script-related content that could produce XSS.
Output validation against expected content can reject or sanitize script content in generated web pages, reducing XSS exploitability.
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.
Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).
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.
Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.