Cyber Resilience

CVE-2025-1323

SQLi in Plechevandrey Wp-Recall ≤ 16.26.12

Published
08 March 2025
Modified
12 March 2025
Patch / advisory
CVSS Score v3.1 7.5
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
EPSS Score 0.029 86th percentile
Risk Priority 79 floored blend · peak EPSS

CVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.

Summary

CVE-2025-1323 is a high-severity SQL Injection (CWE-89) vulnerability in Plechevandrey Wp-Recall. Its CVSS base score is 7.5 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 14% of CVEs by exploit likelihood; 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.

The WP-Recall plugin for WordPress, which provides registration, profile, commerce, and related functionality, contains a SQL injection vulnerability in all versions through 16.26.10. The flaw exists in the handling of the 'databeat' parameter, where insufficient escaping of user input and the absence of prepared statements allow an attacker to modify existing database queries.

Unauthenticated attackers can exploit the issue over the network by supplying crafted input that appends additional SQL statements, enabling extraction of sensitive data from the WordPress database. The vulnerability carries a CVSS 3.1 score of 7.5, reflecting its remote exploitability without authentication or user interaction and its impact on confidentiality.

A patch addressing the parameter handling was committed to the plugin's repository, and Wordfence published corresponding threat intelligence. Administrators should update to a fixed version once released and apply standard WordPress plugin hygiene such as restricting unnecessary database exposure.

The EPSS score rose from a low baseline to a peak of 0.5321 on 2025-12-11 before receding to 0.2862, indicating increased exploitation interest after public disclosure.

OWASP Top 10 for Web (2025)

EU & UK References

Vulnerability Data

The WP-Recall – Registration, Profile, Commerce & More plugin for WordPress is vulnerable to SQL Injection via the 'databeat' parameter in all versions up to, and including, 16.26.10 due to insufficient escaping on the user supplied parameter and lack of…

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sufficient preparation on the existing SQL query. This makes it possible for unauthenticated attackers to append additional SQL queries into already existing queries that can be used to extract sensitive information from the database.

CWE(s)

Related Threats

MITRE ATT&CK Enterprise Techniques

T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2024-32087Same product class: WordPress / CMS plugin
CVE-2022-0412Same product class: WordPress / CMS plugin
CVE-2024-50479Same product class: WordPress / CMS plugin
CVE-2024-51626Same product class: WordPress / CMS plugin
CVE-2023-32743Same product class: WordPress / CMS plugin
CVE-2024-3055Same product class: WordPress / CMS plugin
CVE-2024-6166Same product class: WordPress / CMS plugin
CVE-2023-3677Same product class: WordPress / CMS plugin
CVE-2024-22147Same product class: WordPress / CMS plugin
CVE-2023-41685Same product class: WordPress / CMS plugin

Affected Assets

plechevandrey
wp-recall
≤ 16.26.12

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

—

Detect
Catch it (NIST detect / respond)

—

Harden
Shrink the surface (DISA STIG)

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Validate
Prove the fix (OWASP ASVS)
  • 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.

PR.PS-06 mostly match
prevents

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.

PR.AT-02 partial match
prevents

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.

finds

The same secure-coding and static-analysis activities surface missing neutralization of SQL metacharacters before the system is accepted.

prevents

Early warnings and shared best-practice information help organizations apply the latest remediation techniques against SQL-injection vulnerabilities.

prevents

Threat-intelligence feeds that surface new SQL-injection campaigns enable rapid updates to query-construction defenses and detection signatures before exploitation occurs.

prevents

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.

prevents

Language-specific secure coding rules, peer review and SAST together prevent the construction of SQL statements from untrusted data without proper parameterization or escaping.

References