CVE-2023-6634 (GCVE-0-2023-6634)
Vulnerability from cvelistv5 – Published: 2024-01-11 08:32 – Updated: 2026-04-08 16:41Title
LearnPress <= 4.2.5.7 - Command Injection
Summary
The LearnPress plugin for WordPress is vulnerable to Command Injection in all versions up to, and including, 4.2.5.7 via the get_content function. This is due to the plugin making use of the call_user_func function with user input. This makes it possible for unauthenticated attackers to execute any public function with one parameter, which could result in remote code execution.
Severity
8.1 (High)
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-05-08 15:47 UTC
CWE
Assigner
References
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| thimpress | LearnPress – WordPress LMS Plugin for Create and Sell Online Courses |
Affected:
0 , ≤ 4.2.5.7
(semver)
|
guessed |
Shadowserver
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 10288923-d9d6-44d2-beac-ce6b5e205a5a
Exploited: Yes
Characteristics
Severity:
98.0
Timestamps
First Seen: 2024-04-06
Asserted: 2024-04-06
Last Seen: 2026-07-15
Scope
Asset Exposure: ['internet-facing']
Notes: Affected: Wordpress / Wordpress LearnPress plugin | Class: cms | Severity: Critical (CVSS 9.8) | IoT: no | In CISA KEV: no | Honeypot connections on 2026-07-15: 2
Evidence
Type: Honeypot
Signal: In The Wild Attempts
Confidence: 70%
Source: shadowserver
Details
| 1D | 1 |
|---|---|
| Iot | no |
| Feed | Shadowserver Foundation honeypot/exploited-vulnerabilities |
| Type | http-scan |
| Class | cms |
| 7D Avg | 0 |
| Vendor | Wordpress |
| 30D Avg | 0 |
| 90D Avg | 0 |
| Product | Wordpress LearnPress plugin |
| Cisa Kev | no |
| Connections | 2 |
| Observation Date | 2026-07-15 |
| Vulnerability Class | CVSS |
| Vulnerability Score | 9.8 |
| Vulnerability Severity | Critical |
References
Created: 2026-07-01 07:17 UTC
| Updated: 2026-07-17 01:01 UTC
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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