Security Resilience

CVE-2023-6981

SQLi in Veronalabs Wp Sms ≤ 6.5.1

Published
03 January 2024
Modified
08 April 2026
Patch / advisory
CVSS Score v3.1 6.1
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N
EPSS Score 0.0041 34th percentile
Risk Priority 46 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-2023-6981 is a medium-severity SQL Injection (CWE-89) vulnerability in Veronalabs Wp Sms. Its CVSS base score is 6.1 (Medium).

Operationally, exploitation aligns with the MITRE ATT&CK technique Steganography (T1001.002); ranked at the 34th 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.

OWASP Top 10 for Web (2025)

EU & UK References

Vulnerability Data

The WP SMS – Messaging & SMS Notification for WordPress, WooCommerce, GravityForms, etc plugin for WordPress is vulnerable to SQL Injection via the 'group_id' parameter in all versions up to, and including, 6.5 due to insufficient escaping on the user…

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supplied parameter and lack of sufficient preparation on the existing SQL query. This makes it possible for authenticated attackers, with contributor-level access and above, to append additional SQL queries into already existing queries that can be used to extract sensitive information from the database. This can leveraged to achieve Reflected Cross-site Scripting.

CWE(s)

Related Threats

MITRE ATT&CK Enterprise Techniques

T1001.002 Steganography Command And Control
Adversaries may use steganographic techniques to hide command and control traffic to make detection efforts more difficult.
T1001.003 Protocol or Service Impersonation Command And Control
Adversaries may impersonate legitimate protocols or web service traffic to disguise command and control activity and thwart analysis efforts.
T1003 OS Credential Dumping Credential Access
Adversaries may attempt to dump credentials to obtain account login and credential material, normally in the form of a hash or a clear text password.
T1003.001 LSASS Memory Credential Access
Adversaries may attempt to access credential material stored in the process memory of the Local Security Authority Subsystem Service (LSASS).
T1003.002 Security Account Manager Credential Access
Adversaries may attempt to extract credential material from the Security Account Manager (SAM) database either through in-memory techniques or through the Windows Registry where the SAM database is stored.
T1003.003 NTDS Credential Access
Adversaries may attempt to access or create a copy of the Active Directory domain database in order to steal credential information, as well as obtain other information about domain members such as devices, users, and access rights.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2022-25148Same vendor: Veronalabs
CVE-2022-25149Same vendor: Veronalabs
CVE-2022-0513Same vendor: Veronalabs
CVE-2023-30605Shared CWE-89
CVE-2023-5813Shared CWE-89
CVE-2023-30465Shared CWE-89
CVE-2023-2035Shared CWE-89
CVE-2024-37381Shared CWE-89
CVE-2019-13373Shared CWE-89
CVE-2024-10023Shared CWE-89

Affected Assets

veronalabs
wp sms
≤ 6.5.1

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

—

Detect
Catch it (NIST detect / respond)

—

Harden
Shrink the surface (DISA STIG)

—

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
blocks

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
blocks

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.

removes
removes
removes
removes
blocks

A.5.6 only improves knowledge flow, awareness of threats/patches and access to specialist advice; it does not stop SQL injection from being exploitable in code that still contains the flaw.

References