CVE-2023-6198 (GCVE-0-2023-6198)
Vulnerability from cvelistv5 – Published: 2024-06-25 01:34 – Updated: 2024-08-02 08:21
VLAI
EPSS
VEX
Title
Hard Coded Credential
Summary
Use of Hard-coded Credentials vulnerability in Baicells Snap Router BaiCE_BMI on EP3011 (User Passwords modules) allows unauthorized access to the device.
Severity
9.3 (Critical)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-06-26 19:19 UTC
CWE
- CWE-798 - Use of Hard-coded Credentials
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://www.baicells.com |
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Baicells | Snap Router |
Affected:
1.3.5.6 , ≤ BaiCE_BMI_1.3.5.10_NAC
(custom)
|
guessed | |
| baicells | ep3011_firmware |
Affected:
1.3.5.6 , ≤ 1.3.5.10
(custom)
cpe:2.3:o:baicells:ep3011_firmware:-:*:*:*:*:*:*:* |
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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
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