CVE-2025-62577 (GCVE-0-2025-62577)
Vulnerability from cvelistv5 – Published: 2025-10-20 05:32 – Updated: 2025-11-03 16:06
VLAI
EPSS
VEX
Summary
ETERNUS SF provided by Fsas Technologies Inc. contains an incorrect default permissions vulnerability. A low-privileged user with access to the management server may obtain database credentials, potentially allowing execution of OS commands with administrator privileges.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-10-20 14:12 UTC
CWE
- CWE-276 - Incorrect default permissions
Assigner
References
Impacted products
8 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Fsas Technologies Inc. | ETERNUS SF AdvancedCopy Manager Standard Edition (for Solaris 10/ 11) |
Affected:
15.0/ 15.1/ 15.2/ 15.3/ 16.0/ 16.1/ 16.2/ 16.3/ 16.4/ 16.5/ 16.6/ 16.7/ 16.8/ 16.9/ 16.9.1
|
guessed | |
| Fsas Technologies Inc. | ETERNUS SF Storage Cruiser (for Solaris 10/ 11) |
Affected:
15.0/ 15.1/ 15.2/ 15.3/ 16.0/ 16.1/ 16.2/ 16.3/ 16.4/ 16.5/ 16.6/ 16.7/ 16.8/ 16.9/ 16.9.1
|
guessed | |
| Fsas Technologies Inc. | ETERNUS SF AdvancedCopy Manager Standard Edition (for RHEL 7/ 8/ 9) |
Affected:
16.2/ 16.3/ 16.4/ 16.5/ 16.6/ 16.7/ 16.8/ 16.9/ 16.9.1
|
guessed | |
| Fsas Technologies Inc. | ETERNUS SF Expressn (for RHEL 7/ 8/ 9) |
Affected:
16.2/ 16.3/ 16.4/ 16.5/ 16.6/ 16.7/ 16.8/ 16.9/ 16.9.1
|
guessed | |
| Fsas Technologies Inc. | ETERNUS SF Storage Cruisern (for RHEL 7/ 8/ 9) |
Affected:
16.2/ 16.3/ 16.4/ 16.5/ 16.6/ 16.7/ 16.8/ 16.9/ 16.9.1
|
guessed | |
| Fsas Technologies Inc. | ETERNUS SF AdvancedCopy Manager Standard Edition (for Windows Server 2016/ 2019/ 2022) |
Affected:
16.4/ 16.5/ 16.6/ 16.7/ 16.8/ 16.9/ 16.9.1
|
guessed | |
| Fsas Technologies Inc. | ETERNUS SF Express (for Windows Server 2016/ 2019/ 2022) |
Affected:
16.4/ 16.5/ 16.6/ 16.7/ 16.8/ 16.9/ 16.9.1
|
guessed | |
| Fsas Technologies Inc. | ETERNUS SF Storage Cruiser (for Windows Server 2016/ 2019/ 2022) |
Affected:
16.4/ 16.5/ 16.6/ 16.7/ 16.8/ 16.9/ 16.9.1
|
guessed |
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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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