Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:H/SC:N/SI:N/SA:N/E:U/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-2026-26186 is a medium-severity SQL Injection (CWE-89) vulnerability in Fleetdm Fleet. Its CVSS base score is 5.1 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 23th 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-2026-26186 is a SQL injection vulnerability affecting Fleet, an open source device management software. The flaw exists in versions prior to 4.80.1 and stems from the unsafe use of the `goqu.I()` function when constructing the `ORDER BY` clause, allowing authenticated users to inject arbitrary SQL expressions via the `order_key` query parameter. This enables specially crafted input to escape identifier quoting and be interpreted as executable SQL in the underlying MySQL query.
An authenticated attacker with access to the affected endpoint can exploit this vulnerability over the network with low complexity and no user interaction required. Although the injection occurs in an `ORDER BY` context, it supports blind SQL injection techniques to disclose database information through conditional expressions that influence result ordering. Attackers may also trigger excessive computation or query failures, leading to degraded performance or denial of service. The CVSS v3.1 base score is 8.8 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H), with no demonstrated reliable data modification or stacked query execution, and it maps to CWE-89.
The advisory recommends upgrading to version 4.80.1, which fixes the issue. If immediate upgrading is not feasible, restrict access to the affected endpoint to trusted roles only and strictly allow-list any user-supplied sort or column parameters at the application or proxy layer. Further details are available in the GitHub Security Advisory at https://github.com/fleetdm/fleet/security/advisories/GHSA-49xw-vfc4-7p43.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-8780
Vulnerability Data
Fleet is open source device management software. A SQL injection vulnerability in versions prior to 4.80.1 allowed authenticated users to inject arbitrary SQL expressions via the `order_key` query parameter. Due to unsafe use of `goqu.I()` when constructing the `ORDER BY`…
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clause, specially crafted input could escape identifier quoting and be interpreted as executable SQL. An authenticated attacker with access to the affected endpoint could inject SQL expressions into the underlying MySQL query. Although the injection occurs in an `ORDER BY` context, it is sufficient to enable blind SQL injection techniques that can disclose database information through conditional expressions that affect result ordering. Crafted expressions may also cause excessive computation or query failures, potentially leading to degraded performance or denial of service. No direct evidence of reliable data modification or stacked query execution was demonstrated. Version 4.80.1 fixes the issue. If an immediate upgrade is not possible, users should restrict access to the affected endpoint to trusted roles only and ensure that any user-supplied sort or column parameters are strictly allow-listed at the application or proxy layer.
- 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.