FKIE_CVE-2020-10275
Vulnerability from fkie_nvd - Published: 2020-06-24 05:15 - Updated: 2026-06-17 02:47
Severity
Summary
The access tokens for the REST API are directly derived from the publicly available default credentials for the web interface. Given a USERNAME and a PASSWORD, the token string is generated directly with base64(USERNAME:sha256(PASSWORD)). An unauthorized attacker inside the network can use the default credentials to compute the token and interact with the REST API to exfiltrate, infiltrate or delete data.
References
| URL | Tags | ||
|---|---|---|---|
| cve@aliasrobotics.com | https://github.com/aliasrobotics/RVD/issues/2565 | Third Party Advisory | |
| af854a3a-2127-422b-91ae-364da2661108 | https://github.com/aliasrobotics/RVD/issues/2565 | Third Party Advisory |
Impacted products
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"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "The access tokens for the REST API are directly derived from the publicly available default credentials for the web interface. Given a USERNAME and a PASSWORD, the token string is generated directly with base64(USERNAME:sha256(PASSWORD)). An unauthorized attacker inside the network can use the default credentials to compute the token and interact with the REST API to exfiltrate, infiltrate or delete data."
},
{
"lang": "es",
"value": "Los tokens de acceso para la API REST son derivados directamente desde las credenciales predeterminadas disponibles p\u00fablicamente para la interfaz web. Dado un NOMBRE DE USUARIO y una CONTRASE\u00d1A, la cadena de token est\u00e1 generada directamente con base64(USERNAME:sha256(PASSWORD)). Un atacante no autorizado dentro de la red puede utilizar las credenciales predeterminadas para calcular el token e interactuar con la API REST para filtrar, infiltrar o eliminar datos"
}
],
"id": "CVE-2020-10275",
"lastModified": "2026-06-17T02:47:36.587",
"metrics": {
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"acInsufInfo": false,
"baseSeverity": "HIGH",
"cvssData": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 7.5,
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"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:L/Au:N/C:P/I:P/A:P",
"version": "2.0"
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"impactScore": 6.4,
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"source": "nvd@nist.gov",
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"baseScore": 9.8,
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"confidentialityImpact": "HIGH",
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"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
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"attackVector": "NETWORK",
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"source": "nvd@nist.gov",
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"published": "2020-06-24T05:15:13.193",
"references": [
{
"source": "cve@aliasrobotics.com",
"tags": [
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}
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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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