CVE-2026-103098 (GCVE-0-2026-103098)
Vulnerability from cvelistv5 – Published: 2026-10-02 00:15 – Updated: 2026-10-02 00:15
VLAI
EPSS
VEX
Title
GV-Eye Sensitive information exposure in URL query parameter Vulnerability
Summary
Transmission of a sensitive key in the URL
over an unencrypted HTTP connection. The
request is sent over HTTP rather than HTTPS, meaning the key is transmitted in
plaintext across the network. An attacker with the ability to monitor network
traffic could intercept the request and obtain the key
Severity
7.5 (High)
CWE
- CWE-319 - Cleartext transmission of sensitive information
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://www.geovision.com.tw/cyber_security.php | vendor-advisory |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| GeoVision Inc. | GV-Eye |
Affected:
V3.6.0
Unaffected: V3.7.2 cpe:2.3:a:geovision_inc.:gv-eye:v3.6.0:*:android:*:*:*:*:* |
Date Public
2026-09-30 02:15
{
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"packageName": "tw.com.geovision.gveye",
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"vendor": "GeoVision Inc.",
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},
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}
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"type": "finder",
"value": "Lloyd Lexter Gealon"
}
],
"datePublic": "2026-09-30T02:15:00.000Z",
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}
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}
],
"impacts": [
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"capecId": "CAPEC-158",
"descriptions": [
{
"lang": "en",
"value": "CAPEC-158 Sniffing Network Traffic"
}
]
}
],
"metrics": [
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"attackVector": "NETWORK",
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"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
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"description": "CWE-319 Cleartext transmission of sensitive information",
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"providerMetadata": {
"dateUpdated": "2026-10-02T00:15:17.848Z",
"orgId": "0df08a0e-a200-4957-9bb0-084f562506f9",
"shortName": "GV"
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"references": [
{
"tags": [
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],
"url": "https://www.geovision.com.tw/cyber_security.php"
}
],
"source": {
"discovery": "UNKNOWN"
},
"title": "GV-Eye Sensitive information exposure in URL query parameter Vulnerability",
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"cveId": "CVE-2026-103098",
"datePublished": "2026-10-02T00:15:17.848Z",
"dateReserved": "2026-09-30T02:10:02.128Z",
"dateUpdated": "2026-10-02T00:15:17.848Z",
"state": "PUBLISHED"
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"dataType": "CVE_RECORD",
"dataVersion": "5.2",
"vulnerability-lookup:meta": {
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}
],
"id": "CVE-2026-103098",
"lastModified": "2026-10-02T01:16:43.193",
"metrics": {
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"url": "https://www.geovision.com.tw/cyber_security.php"
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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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