CVE-2026-26794
SQLi in Gl-Inet Ar300M16 Firmware 4.3.11
Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2026-26794 is a high-severity SQL Injection (CWE-89) vulnerability in Gl-Inet Ar300M16 Firmware. Its CVSS base score is 8.8 (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; a public proof-of-concept is referenced.
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-2026-26794 is a SQL injection vulnerability (CWE-89) affecting the GL-iNet GL-AR300M16 router on firmware version 4.3.11. The issue exists in the add_group() function, which does not properly sanitize user inputs, enabling attackers to execute arbitrary SQL database operations via a crafted HTTP request. Published on 2026-03-12, it carries a CVSS v3.1 base score of 8.8 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H), reflecting its high severity due to network accessibility and significant impacts.
The vulnerability can be exploited by low-privileged users (PR:L) who can send a specially crafted HTTP request over the network with low attack complexity and no user interaction required. Successful exploitation grants attackers the ability to perform arbitrary SQL operations on the device's database, leading to high confidentiality, integrity, and availability impacts, such as data exfiltration, modification, or denial of service.
A reference to a proof-of-concept exploit is available at https://github.com/sezangel/IOT-vul/tree/main/GL-iNet/GL-AR300M16/acl--add_group. No vendor advisories or patches are detailed in the provided information.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-11625
Vulnerability Data
GL-iNet GL-AR300M16 v4.3.11 was discovered to contain a SQL injection vulnerability via the add_group() function. This vulnerability allows attackers to execute arbitrary SQL database operations via a crafted HTTP request.
- 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.