CVE-2023-4220 (GCVE-0-2023-4220)
Vulnerability from cvelistv5 – Published: 2023-11-28 07:11 – Updated: 2024-08-02 07:17Title
Chamilo LMS Unauthenticated Big Upload File Remote Code Execution
Summary
Unrestricted file upload in big file upload functionality in `/main/inc/lib/javascript/bigupload/inc/bigUpload.php` in Chamilo LMS <= v1.11.24 allows unauthenticated attackers to perform stored cross-site scripting attacks and obtain remote code execution via uploading of web shell.
Severity
8.1 (High)
CWE
- CWE-434 - Unrestricted Upload of File with Dangerous Type
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://support.chamilo.org/projects/chamilo-18/w… | vendor-advisory |
| https://starlabs.sg/advisories/23/23-4220 | third-party-advisory |
| https://github.com/chamilo/chamilo-lms/commit/3b4… | patch |
Impacted products
Shadowserver
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 6bfca658-35a1-454d-8963-07a22de64b76
Exploited: Yes
Characteristics
Severity:
61.0
Timestamps
First Seen: 2024-12-05
Asserted: 2024-12-05
Last Seen: 2026-09-06
Scope
Asset Exposure: ['internet-facing']
Notes: Affected: Chamilo / Chamilo | Class: cms | Severity: Medium (CVSS 6.1) | IoT: no | In CISA KEV: no | Honeypot connections on 2026-09-06: 1
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 | 2 |
| Vendor | Chamilo |
| 30D Avg | 0 |
| 90D Avg | 0 |
| Product | Chamilo |
| Cisa Kev | no |
| Connections | 1 |
| Observation Date | 2026-09-06 |
| Vulnerability Class | CVSS |
| Vulnerability Score | 6.1 |
| Vulnerability Severity | Medium |
References
Created: 2026-07-01 05:54 UTC
| Updated: 2026-09-08 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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