GSD-2018-19295
Vulnerability from gsd - Updated: 2023-12-13 01:22Details
Sylabs Singularity 2.4 to 2.6 allows local users to conduct Improper Input Validation attacks.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2018-19295",
"description": "Sylabs Singularity 2.4 to 2.6 allows local users to conduct Improper Input Validation attacks.",
"id": "GSD-2018-19295",
"references": [
"https://www.suse.com/security/cve/CVE-2018-19295.html",
"https://ubuntu.com/security/CVE-2018-19295"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2018-19295"
],
"details": "Sylabs Singularity 2.4 to 2.6 allows local users to conduct Improper Input Validation attacks.",
"id": "GSD-2018-19295",
"modified": "2023-12-13T01:22:39.447962Z",
"schema_version": "1.4.0"
}
},
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"STATE": "PUBLIC"
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"affects": {
"vendor": {
"vendor_data": [
{
"product": {
"product_data": [
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"version": {
"version_data": [
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"references": {
"reference_data": [
{
"name": "https://github.com/sylabs/singularity/releases/tag/2.6.1",
"refsource": "CONFIRM",
"url": "https://github.com/sylabs/singularity/releases/tag/2.6.1"
}
]
}
},
"gitlab.com": {
"advisories": [
{
"affected_range": "\u003e=v2.4 \u003c=v2.6",
"affected_versions": "All versions starting from 2.4 up to 2.6",
"cvss_v2": "AV:L/AC:L/Au:N/C:C/I:C/A:C",
"cvss_v3": "CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-20",
"CWE-937"
],
"date": "2023-07-25",
"description": "Sylabs Singularity 2.4 to 2.6 allows local users to conduct Improper Input Validation attacks.",
"fixed_versions": [],
"identifier": "CVE-2018-19295",
"identifiers": [
"GHSA-p83v-8vmr-qfv9",
"CVE-2018-19295"
],
"not_impacted": "",
"package_slug": "go/github.com/sylabs/singularity",
"pubdate": "2022-05-14",
"solution": "Unfortunately, there is no solution available yet.",
"title": "Improper Input Validation",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2018-19295",
"https://github.com/sylabs/singularity/releases/tag/2.6.1",
"https://github.com/advisories/GHSA-p83v-8vmr-qfv9"
],
"uuid": "bc554bac-a4b6-4c73-bf0d-39a0ef092b45",
"versions": [
{
"commit": {
"sha": "e40bc91b58a26e4a977b1d439d7ac3e3d1fd59a3",
"tags": [
"2.4"
],
"timestamp": "20171012021318"
},
"number": "v2.4"
},
{
"commit": {
"sha": "6b4f6fc878ed55f9056d90d95533b9f70aabf926",
"tags": [
"2.6.0"
],
"timestamp": "20180804010049"
},
"number": "v2.6"
}
]
}
]
},
"nvd.nist.gov": {
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"nodes": [
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"cpe_match": [
{
"cpe23Uri": "cpe:2.3:a:sylabs:singularity:*:*:*:*:*:*:*:*",
"cpe_name": [],
"versionEndIncluding": "2.6.0",
"versionStartIncluding": "2.4",
"vulnerable": true
}
],
"operator": "OR"
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"description": {
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}
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},
"problemtype": {
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"references": {
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{
"name": "https://github.com/sylabs/singularity/releases/tag/2.6.1",
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"tags": [
"Release Notes",
"Third Party Advisory"
],
"url": "https://github.com/sylabs/singularity/releases/tag/2.6.1"
}
]
}
},
"impact": {
"baseMetricV2": {
"acInsufInfo": false,
"cvssV2": {
"accessComplexity": "LOW",
"accessVector": "LOCAL",
"authentication": "NONE",
"availabilityImpact": "COMPLETE",
"baseScore": 7.2,
"confidentialityImpact": "COMPLETE",
"integrityImpact": "COMPLETE",
"vectorString": "AV:L/AC:L/Au:N/C:C/I:C/A:C",
"version": "2.0"
},
"exploitabilityScore": 3.9,
"impactScore": 10.0,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "HIGH",
"userInteractionRequired": false
},
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 7.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"version": "3.0"
},
"exploitabilityScore": 1.8,
"impactScore": 5.9
}
},
"lastModifiedDate": "2019-01-24T17:23Z",
"publishedDate": "2018-12-17T15:29Z"
}
}
}
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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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