GSD-2017-15089
Vulnerability from gsd - Updated: 2023-12-13 01:20Details
It was found that the Hotrod client in Infinispan before 9.2.0.CR1 would unsafely read deserialized data on information from the cache. An authenticated attacker could inject a malicious object into the data cache and attain deserialization on the client, and possibly conduct further attacks.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2017-15089",
"description": "It was found that the Hotrod client in Infinispan before 9.2.0.CR1 would unsafely read deserialized data on information from the cache. An authenticated attacker could inject a malicious object into the data cache and attain deserialization on the client, and possibly conduct further attacks.",
"id": "GSD-2017-15089",
"references": [
"https://access.redhat.com/errata/RHSA-2020:2561",
"https://access.redhat.com/errata/RHSA-2019:1326",
"https://access.redhat.com/errata/RHSA-2018:0501",
"https://access.redhat.com/errata/RHSA-2018:0481",
"https://access.redhat.com/errata/RHSA-2018:0480",
"https://access.redhat.com/errata/RHSA-2018:0479",
"https://access.redhat.com/errata/RHSA-2018:0478",
"https://access.redhat.com/errata/RHSA-2018:0294"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2017-15089"
],
"details": "It was found that the Hotrod client in Infinispan before 9.2.0.CR1 would unsafely read deserialized data on information from the cache. An authenticated attacker could inject a malicious object into the data cache and attain deserialization on the client, and possibly conduct further attacks.",
"id": "GSD-2017-15089",
"modified": "2023-12-13T01:20:58.507661Z",
"schema_version": "1.4.0"
}
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"DATE_PUBLIC": "2018-02-12T00:00:00",
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"STATE": "PUBLIC"
},
"affects": {
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}
]
},
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"value": "CWE-502"
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{
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"refsource": "CONFIRM",
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},
{
"name": "RHSA-2018:0294",
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},
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}
]
}
},
"gitlab.com": {
"advisories": [
{
"affected_range": "(,9.2.0.Beta2]",
"affected_versions": "All versions up to 9.2.0.beta2",
"cvss_v2": "AV:N/AC:L/Au:S/C:P/I:P/A:P",
"cvss_v3": "CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-502",
"CWE-937"
],
"date": "2022-08-16",
"description": "It was found that the Hotrod client in Infinispan before 9.2.0.CR1 would unsafely read deserialized data on information from the cache. An authenticated attacker could inject a malicious object into the data cache and attain deserialization on the client, and possibly conduct further attacks.",
"fixed_versions": [
"9.2.0.CR1"
],
"identifier": "CVE-2017-15089",
"identifiers": [
"GHSA-46r5-59fg-2fjc",
"CVE-2017-15089"
],
"not_impacted": "All versions after 9.2.0.beta2",
"package_slug": "maven/org.infinispan/infinispan-core",
"pubdate": "2022-05-14",
"solution": "Upgrade to version 9.2.0.CR1 or above.",
"title": "Deserialization of Untrusted Data",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2017-15089",
"https://github.com/infinispan/infinispan/pull/5639",
"https://access.redhat.com/errata/RHSA-2018:0294",
"https://access.redhat.com/errata/RHSA-2018:0478",
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"https://access.redhat.com/errata/RHSA-2018:0480",
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"https://access.redhat.com/errata/RHSA-2018:0501",
"https://access.redhat.com/errata/RHSA-2019:1326",
"https://github.com/advisories/GHSA-46r5-59fg-2fjc"
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"uuid": "bbc33908-62f2-41b6-9397-de28990fad68"
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},
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{
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"versionEndIncluding": "9.1.6",
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{
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"description": {
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}
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},
"impact": {
"baseMetricV2": {
"cvssV2": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "SINGLE",
"availabilityImpact": "PARTIAL",
"baseScore": 6.5,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:L/Au:S/C:P/I:P/A:P",
"version": "2.0"
},
"exploitabilityScore": 8.0,
"impactScore": 6.4,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": false
},
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"version": "3.0"
},
"exploitabilityScore": 2.8,
"impactScore": 5.9
}
},
"lastModifiedDate": "2019-06-04T17:29Z",
"publishedDate": "2018-02-15T17:29Z"
}
}
}
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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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