FKIE_CVE-2017-1569
Vulnerability from fkie_nvd - Published: 2017-10-03 01:29 - Updated: 2026-06-17 01:14
Severity
Summary
IBM WebSphere Commerce 7.0 and 8.0 contains an unspecified vulnerability in Marketing ESpot's that could cause a denial of service. IBM X-Force ID: 131779.
References
| URL | Tags | ||
|---|---|---|---|
| psirt@us.ibm.com | http://www.ibm.com/support/docview.wss?uid=swg22008547 | Vendor Advisory | |
| psirt@us.ibm.com | http://www.securityfocus.com/bid/101073 | Third Party Advisory, VDB Entry | |
| psirt@us.ibm.com | https://exchange.xforce.ibmcloud.com/vulnerabilities/131779 | VDB Entry | |
| af854a3a-2127-422b-91ae-364da2661108 | http://www.ibm.com/support/docview.wss?uid=swg22008547 | Vendor Advisory | |
| af854a3a-2127-422b-91ae-364da2661108 | http://www.securityfocus.com/bid/101073 | Third Party Advisory, VDB Entry | |
| af854a3a-2127-422b-91ae-364da2661108 | https://exchange.xforce.ibmcloud.com/vulnerabilities/131779 | VDB Entry |
Impacted products
{
"affected": [
{
"affectedData": [
{
"product": "WebSphere Commerce Enterprise",
"vendor": "IBM",
"versions": [
{
"status": "affected",
"version": "7.0"
},
{
"status": "affected",
"version": "8.0"
}
]
}
],
"source": "psirt@us.ibm.com"
}
],
"configurations": [
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],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "IBM WebSphere Commerce 7.0 and 8.0 contains an unspecified vulnerability in Marketing ESpot\u0027s that could cause a denial of service. IBM X-Force ID: 131779."
},
{
"lang": "es",
"value": "Las versiones 7.0 y 8.0 de IBM WebSphere Commerce contienen una vulnerabilidad sin especificar en E-Marketing Spots que podr\u00eda provocar una denegaci\u00f3n de servicio (DoS). IBM X-Force ID: 131779."
}
],
"id": "CVE-2017-1569",
"lastModified": "2026-06-17T01:14:34.900",
"metrics": {
"cvssMetricV2": [
{
"acInsufInfo": false,
"baseSeverity": "MEDIUM",
"cvssData": {
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"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 5.0,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:L/Au:N/C:N/I:N/A:P",
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},
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"baseScore": 7.5,
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"published": "2017-10-03T01:29:03.060",
"references": [
{
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"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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