CVE-2021-22708 (GCVE-0-2021-22708)
Vulnerability from cvelistv5 – Published: 2021-07-21 10:41 – Updated: 2024-08-03 18:51
VLAI
EPSS
VEX
Summary
A CWE-347: Improper Verification of Cryptographic Signature vulnerability exists in EVlink City (EVC1S22P4 / EVC1S7P4 all versions prior to R8 V3.4.0.1), EVlink Parking (EVW2 / EVF2 / EV.2 all versions prior to R8 V3.4.0.1), and EVlink Smart Wallbox (EVB1A all versions prior to R8 V3.4.0.1 ) that could allow an attacker to craft a malicious firmware package and bypass the signature verification mechanism.
Severity
7.2 (High)
CWE
- CWE-347 - Improper Verification of Cryptographic Signature
Assigner
References
1 reference
| URL | Tags |
|---|---|
| http://download.schneider-electric.com/files?p_Do… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| n/a | EVlink City (EVC1S22P4 / EVC1S7P4 all versions prior to R8 V3.4.0.1), EVlink Parking (EVW2 / EVF2 / EV.2 all versions prior to R8 V3.4.0.1), and EVlink Smart Wallbox (EVB1A all versions prior to R8 V3.4.0.1 ) |
Affected:
EVlink City (EVC1S22P4 / EVC1S7P4 all versions prior to R8 V3.4.0.1), EVlink Parking (EVW2 / EVF2 / EV.2 all versions prior to R8 V3.4.0.1), and EVlink Smart Wallbox (EVB1A all versions prior to R8 V3.4.0.1 )
|
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"url": "http://download.schneider-electric.com/files?p_Doc_Ref=SEVD-2021-194-06"
}
],
"sourceIdentifier": "cybersecurity@se.com",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-347"
}
],
"source": "cybersecurity@se.com",
"type": "Primary"
}
]
}
},
"redhat_vex": {
"current_release_date": "2026-03-27T14:49:24+00:00",
"cve": "CVE-2021-22708",
"id": "CVE-2021-22708",
"initial_release_date": "2021-01-01T00:00:00+00:00",
"product_status:known_not_affected": "1",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "CVE-2021-22708",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2021/cve-2021-22708.json",
"version": "3"
}
}
}
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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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