GSD-2021-3702
Vulnerability from gsd - Updated: 2023-12-13 01:23Details
A race condition flaw was found in ansible-runner, where an attacker could watch for rapid creation and deletion of a temporary directory, substitute their directory at that name, and then have access to ansible-runner's private_data_dir the next time ansible-runner made use of the private_data_dir. The highest Threat out of this flaw is to integrity and confidentiality.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2021-3702",
"description": "A race condition flaw was found in ansible-runner, where an attacker could watch for rapid creation and deletion of a temporary directory, substitute their directory at that name, and then have access to ansible-runner\u0027s private_data_dir the next time ansible-runner made use of the private_data_dir. The highest Threat out of this flaw is to integrity and confidentiality.",
"id": "GSD-2021-3702"
},
"gsd": {
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"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
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"id": "GSD-2021-3702",
"modified": "2023-12-13T01:23:35.028516Z",
"schema_version": "1.4.0"
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"gitlab.com": {
"advisories": [
{
"affected_range": "\u003e=2.0.0,\u003c2.1.0",
"affected_versions": "All versions starting from 2.0.0 before 2.1.0",
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"CWE-937"
],
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"fixed_versions": [
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"identifiers": [
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"CVE-2021-3702"
],
"not_impacted": "All versions before 2.0.0, all versions starting from 2.1.0",
"package_slug": "pypi/ansible-runner",
"pubdate": "2022-08-24",
"solution": "Upgrade to version 2.1.0 or above.",
"title": "Concurrent Execution using Shared Resource with Improper Synchronization (\u0027Race Condition\u0027)",
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},
"impact": {
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "HIGH",
"attackVector": "LOCAL",
"availabilityImpact": "NONE",
"baseScore": 6.3,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:N",
"version": "3.1"
},
"exploitabilityScore": 1.0,
"impactScore": 5.2
}
},
"lastModifiedDate": "2022-08-29T18:26Z",
"publishedDate": "2022-08-23T16:15Z"
}
}
}
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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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