GSD-2022-22979
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
In Spring Cloud Function versions prior to 3.2.6, it is possible for a user who directly interacts with framework provided lookup functionality to cause a denial-of-service condition due to the caching issue in the Function Catalog component of the framework.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2022-22979",
"description": "In Spring Cloud Function versions prior to 3.2.6, it is possible for a user who directly interacts with framework provided lookup functionality to cause a denial-of-service condition due to the caching issue in the Function Catalog component of the framework.",
"id": "GSD-2022-22979"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
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],
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"id": "GSD-2022-22979",
"modified": "2023-12-13T01:19:28.979949Z",
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}
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"name": "https://tanzu.vmware.com/security/cve-2022-22979",
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"url": "https://tanzu.vmware.com/security/cve-2022-22979"
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},
"gitlab.com": {
"advisories": [
{
"affected_range": "(,3.2.6)",
"affected_versions": "All versions before 3.2.6",
"cwe_ids": [
"CWE-1035",
"CWE-937"
],
"date": "2022-06-22",
"description": "In Spring Cloud Function versions prior to 3.2.6, it is possible for a user who directly interacts with framework provided lookup functionality to cause a denial-of-service condition due to the caching issue in the Function Catalog component of the framework.",
"fixed_versions": [
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],
"identifier": "CVE-2022-22979",
"identifiers": [
"GHSA-q588-3544-8g33",
"CVE-2022-22979"
],
"not_impacted": "All versions starting from 3.2.6",
"package_slug": "maven/org.springframework.cloud/spring-cloud-function-parent",
"pubdate": "2022-06-22",
"solution": "Upgrade to version 3.2.6 or above.",
"title": "Denial of Service in Spring Cloud Function",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2022-22979",
"https://tanzu.vmware.com/security/cve-2022-22979",
"https://github.com/advisories/GHSA-q588-3544-8g33"
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"uuid": "4f4ff44a-2eec-42db-b041-d817c92f53e0"
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"versionEndExcluding": "3.2.6",
"vulnerable": true
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},
"impact": {
"baseMetricV2": {
"acInsufInfo": false,
"cvssV2": {
"accessComplexity": "LOW",
"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",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": false
},
"baseMetricV3": {
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"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 3.6
}
},
"lastModifiedDate": "2022-06-28T19:12Z",
"publishedDate": "2022-06-21T15:15Z"
}
}
}
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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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