CVE-2012-10028 (GCVE-0-2012-10028)
Vulnerability from cvelistv5 – Published: 2025-08-05 20:04 – Updated: 2026-05-15 11:13
VLAI
EPSS
VEX
Title
Netwin SurgeFTP <= v23c8 Authenticated RCE
Summary
Netwin SurgeFTP version 23c8 and prior contains a vulnerability in its web-based administrative console that allows authenticated users to execute arbitrary system commands via crafted POST requests to `surgeftpmgr.cgi`. This can lead to full remote code execution on the underlying system.
Severity
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-08-07 15:49 UTC
CWE
- CWE-78 - Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')
Assigner
References
5 references
| URL | Tags |
|---|---|
| https://raw.githubusercontent.com/rapid7/metasplo… | exploit |
| https://www.exploit-db.com/exploits/23522 | exploit |
| https://www.exploit-db.com/exploits/23601 | exploit |
| https://netwinsite.com/surgeftp/ | product |
| https://www.vulncheck.com/advisories/netwin-surge… | third-party-advisory |
Impacted products
Date Public
2012-12-20 00:00
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Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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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.
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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.