Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:NSummary
CVE-2026-34747 is a high-severity SQL Injection (CWE-89) vulnerability in Payloadcms Payload. Its CVSS base score is 8.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 24th 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-2026-34747 is a SQL injection vulnerability (CWE-89) in Payload, a free and open-source headless content management system. Prior to version 3.79.1, the software fails to properly validate certain request inputs, allowing attackers to craft malicious requests that influence SQL query execution. This could result in the exposure or modification of data within collections. The vulnerability carries a CVSS v3.1 base score of 8.5 (AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:N), indicating high severity due to its network accessibility, low complexity, and cross-scope impact.
An authenticated attacker with low privileges (PR:L) can exploit this vulnerability remotely over the network without user interaction. By sending specially crafted requests, they can manipulate SQL queries to achieve high confidentiality impact, such as extracting sensitive data from collections, and low integrity impact, such as limited data modification. The high scope (S:C) amplifies the risk, as exploitation affects not only the vulnerable component but also related system resources.
The issue has been addressed in Payload version 3.79.1, where input validation was strengthened to prevent SQL injection. Security practitioners should upgrade to this version or later. Official details are available in the Payload release notes at https://github.com/payloadcms/payload/releases/tag/v3.79.1 and the GitHub security advisory at https://github.com/payloadcms/payload/security/advisories/GHSA-7xxh-373w-35vg.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-18013
Vulnerability Data
Payload is a free and open source headless content management system. Prior to version 3.79.1, certain request inputs were not properly validated. An attacker could craft requests that influence SQL query execution, potentially exposing or modifying data in collections. This…
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issue has been patched in version 3.79.1.
- 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.