Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2026-27885 is a high-severity SQL Injection (CWE-89) vulnerability in Piwigo Piwigo. Its CVSS base score is 7.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 29th 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-2026-27885 is a SQL injection vulnerability in the Activity List API endpoint of Piwigo, an open-source photo gallery application for the web. It affects all versions prior to 16.3.0. The flaw, classified under CWE-89, carries a CVSS v3.1 base score of 7.2 (AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H), indicating high confidentiality, integrity, and availability impacts with network accessibility and low attack complexity, but requiring high privileges.
An authenticated administrator can exploit this vulnerability remotely to extract sensitive data from the database, including user credentials, email addresses, and all stored content. No user interaction is needed, and the attack does not alter the scope, allowing full compromise of the database contents accessible to the admin role.
Piwigo has addressed the issue in version 16.3.0, as detailed in the project's security advisory (GHSA-wfmr-9hg8-jh3m), the patching commit (c172d284e11eab4a5dbadd2844d26f734d5c8c72), and the release announcement. Security practitioners should upgrade to 16.3.0 or later and review access controls for admin accounts.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-18874
Vulnerability Data
Piwigo is an open source photo gallery application for the web. Prior to version 16.3.0, a SQL Injection vulnerability was discovered in Piwigo affecting the Activity List API endpoint. This vulnerability allows an authenticated administrator to extract sensitive data from…
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the database, including user credentials, email addresses, and all stored content. This issue has been patched in version 16.3.0.
- 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.