CVE-2018-25117 (GCVE-0-2018-25117)
Vulnerability from cvelistv5 – Published: 2025-10-15 01:23 – Updated: 2026-06-23 16:13 X_Known Exploited Vulnerability
VLAI
EPSS
VEX
Title
VestaCP Debian Installer Malicious Backdoor Supply Chain Compromise
Summary
VestaCP commit a3f0fa1 (2018-05-31) up to commit ee03eff (2018-06-13) contain embedded malicious code that resulted in a supply-chain compromise. New installations created from the compromised installer since at least May 2018 were subject to installation of Linux/ChachaDDoS, a multi-stage DDoS bot that uses Lua for second- and third-stage components. The compromise leaked administrative credentials (base64-encoded admin password and server domain) to an external URL during installation and/or resulted in the installer dropping and executing a DDoS malware payload under local system privileges. Compromised servers were subsequently observed participating in large-scale DDoS activity. Vesta acknowledged exploitation in the wild in October 2018.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-10-15 18:54 UTC
CWE
- CWE-506 - Embedded Malicious Code
Assigner
References
8 references
| URL | Tags |
|---|---|
| https://www.welivesecurity.com/2018/10/18/new-lin… | technical-description |
| https://github.com/outroll/vesta/commit/ee03eff01… | patch |
| https://github.com/outroll/vesta/commit/a3f0fa150… | patch |
| https://forum.vestacp.com/viewtopic.php?f=10&t=17… | issue-tracking |
| https://forum.vestacp.com/viewtopic.php?f=10&t=17… | vendor-advisorypatch |
| https://vestacp.com/ | product |
| https://github.com/outroll/vesta | product |
| https://www.vulncheck.com/advisories/vestacp-debi… | third-party-advisory |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Vesta | Control Panel (CP) |
Affected:
a3f0fa1501d424477786e3e7150bb05c0b99518f , < ee03eff016e03cb76fac7ae3a0f9d1ef0f8ee35b
(git)
cpe:2.3:a:vestacp:control_panel:*:*:*:*:*:*:*:* |
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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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