CVE-2023-37897
Getgrav Grav 1.7.42 … 1.7.42.1
Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2023-37897 is a high-severity Injection (CWE-74) vulnerability in Getgrav Grav. Its CVSS base score is 7.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 15% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-2010
Vulnerability Data
Grav is a file-based Web-platform built in PHP. Grav is subject to a server side template injection (SSTI) vulnerability. The fix for another SSTI vulnerability using `|map`, `|filter` and `|reduce` twigs implemented in the commit `71bbed1` introduces bypass of the…
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denylist due to incorrect return value from `isDangerousFunction()`, which allows to execute the payload prepending double backslash (`\\`). The `isDangerousFunction()` check in version 1.7.42 and onwards retuns `false` value instead of `true` when the `\` symbol is found in the `$name`. This vulnerability can be exploited if the attacker has access to: 1. an Administrator account, or 2. a non-administrator, user account that has Admin panel access and Create/Update page permissions. A fix for this vulnerability has been introduced in commit `b4c6210` and is included in release version `1.7.42.2`. Users are advised to upgrade. There are no known workarounds for this vulnerability.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.2.1V1.2.3V1.2.5V1.2.8
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.
Developer assessments and testing (including injection-focused techniques) identify improper neutralization of special elements, and the verifiable flaw remediation corrects them pre-deployment.
Identifies indicators of injection attacks (command, SQL, LDAP, etc.) via anomaly and attack monitoring.
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 require input validation and output encoding that prevent injection flaws.
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.
Security testing in development catches injection vulnerabilities before release.
Logging supports detection of injection attempts but does not prevent the weakness.
Monitoring activities can identify active injection attacks after they occur.
Secure development life cycle mandates input validation and output encoding that directly prevent injection flaws.
Application security requirements explicitly call for controls against injection attacks in software design.
Secure architecture principles reduce injection surfaces but do not prescribe specific neutralization techniques.