GSD-2018-15795
Vulnerability from gsd - Updated: 2023-12-13 01:22Details
Pivotal CredHub Service Broker, versions prior to 1.1.0, uses a guessable form of random number generation in creating service broker's UAA client. A remote malicious user may guess the client secret and obtain or modify credentials for users of the CredHub Service.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2018-15795",
"description": "Pivotal CredHub Service Broker, versions prior to 1.1.0, uses a guessable form of random number generation in creating service broker\u0027s UAA client. A remote malicious user may guess the client secret and obtain or modify credentials for users of the CredHub Service.",
"id": "GSD-2018-15795"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2018-15795"
],
"details": "Pivotal CredHub Service Broker, versions prior to 1.1.0, uses a guessable form of random number generation in creating service broker\u0027s UAA client. A remote malicious user may guess the client secret and obtain or modify credentials for users of the CredHub Service.",
"id": "GSD-2018-15795",
"modified": "2023-12-13T01:22:23.822284Z",
"schema_version": "1.4.0"
}
},
"namespaces": {
"cve.org": {
"CVE_data_meta": {
"ASSIGNER": "security_alert@emc.com",
"DATE_PUBLIC": "2018-11-09T08:00:00.000Z",
"ID": "CVE-2018-15795",
"STATE": "PUBLIC",
"TITLE": "CredHub Service Broker uses guessable client secret"
},
"affects": {
"vendor": {
"vendor_data": [
{
"product": {
"product_data": [
{
"product_name": "CredHub Service Broker",
"version": {
"version_data": [
{
"affected": "\u003c",
"version_name": "all versions",
"version_value": "1.1.0"
}
]
}
}
]
},
"vendor_name": "Pivotal Cloud Foundry"
}
]
}
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"data_type": "CVE",
"data_version": "4.0",
"description": {
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{
"lang": "eng",
"value": "Pivotal CredHub Service Broker, versions prior to 1.1.0, uses a guessable form of random number generation in creating service broker\u0027s UAA client. A remote malicious user may guess the client secret and obtain or modify credentials for users of the CredHub Service."
}
]
},
"impact": {
"cvss": {
"attackComplexity": "LOW",
"attackVector": "ADJACENT_NETWORK",
"availabilityImpact": "NONE",
"baseScore": 8.1,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "HIGH",
"scope": "CHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:A/AC:L/PR:H/UI:N/S:C/C:H/I:H/A:N",
"version": "3.0"
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"value": "Predictability problems"
}
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},
"references": {
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{
"name": "https://pivotal.io/security/cve-2018-15795",
"refsource": "CONFIRM",
"url": "https://pivotal.io/security/cve-2018-15795"
},
{
"name": "105915",
"refsource": "BID",
"url": "http://www.securityfocus.com/bid/105915"
}
]
},
"source": {
"discovery": "UNKNOWN"
}
},
"gitlab.com": {
"advisories": [
{
"affected_range": "(,1.1.0)",
"affected_versions": "All versions before 1.1.0",
"cvss_v2": "AV:N/AC:L/Au:S/C:P/I:P/A:N",
"cvss_v3": "CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N",
"cwe_ids": [
"CWE-1035",
"CWE-338",
"CWE-937"
],
"date": "2021-09-16",
"description": "Pivotal CredHub Service Broker, versions prior to 1.1.0, uses a guessable form of random number generation in creating service broker\u0027s UAA client. A remote malicious user may guess the client secret and obtain or modify credentials for users of the CredHub Service.",
"fixed_versions": [
"1.1.0"
],
"identifier": "CVE-2018-15795",
"identifiers": [
"GHSA-q3jg-4c82-j4xh",
"CVE-2018-15795"
],
"not_impacted": "All versions starting from 1.1.0",
"package_slug": "maven/org.springframework.credhub/spring-credhub-core",
"pubdate": "2018-11-29",
"solution": "Upgrade to version 1.1.0 or above.",
"title": "Use of Cryptographically Weak Pseudo-Random Number Generator (PRNG)",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2018-15795",
"https://github.com/advisories/GHSA-q3jg-4c82-j4xh",
"https://pivotal.io/security/cve-2018-15795"
],
"uuid": "d784fa87-a069-46dd-b914-a24123d20424"
}
]
},
"nvd.nist.gov": {
"configurations": {
"CVE_data_version": "4.0",
"nodes": [
{
"children": [],
"cpe_match": [
{
"cpe23Uri": "cpe:2.3:a:pivotal_software:credhub_service_broker:*:*:*:*:*:*:*:*",
"cpe_name": [],
"versionEndExcluding": "1.1.0",
"vulnerable": true
}
],
"operator": "OR"
}
]
},
"cve": {
"CVE_data_meta": {
"ASSIGNER": "secure@dell.com",
"ID": "CVE-2018-15795"
},
"data_format": "MITRE",
"data_type": "CVE",
"data_version": "4.0",
"description": {
"description_data": [
{
"lang": "en",
"value": "Pivotal CredHub Service Broker, versions prior to 1.1.0, uses a guessable form of random number generation in creating service broker\u0027s UAA client. A remote malicious user may guess the client secret and obtain or modify credentials for users of the CredHub Service."
}
]
},
"problemtype": {
"problemtype_data": [
{
"description": [
{
"lang": "en",
"value": "CWE-338"
}
]
}
]
},
"references": {
"reference_data": [
{
"name": "https://pivotal.io/security/cve-2018-15795",
"refsource": "CONFIRM",
"tags": [
"Mitigation",
"Vendor Advisory"
],
"url": "https://pivotal.io/security/cve-2018-15795"
},
{
"name": "105915",
"refsource": "BID",
"tags": [
"Third Party Advisory",
"VDB Entry"
],
"url": "http://www.securityfocus.com/bid/105915"
}
]
}
},
"impact": {
"baseMetricV2": {
"acInsufInfo": false,
"cvssV2": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "SINGLE",
"availabilityImpact": "NONE",
"baseScore": 5.5,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:L/Au:S/C:P/I:P/A:N",
"version": "2.0"
},
"exploitabilityScore": 8.0,
"impactScore": 4.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": false
},
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 8.1,
"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:N",
"version": "3.0"
},
"exploitabilityScore": 2.8,
"impactScore": 5.2
}
},
"lastModifiedDate": "2019-10-09T23:35Z",
"publishedDate": "2018-11-13T14:29Z"
}
}
}
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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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