GSD-2018-1330
Vulnerability from gsd - Updated: 2023-12-13 01:22Details
When parsing a malformed JSON payload, libprocess in Apache Mesos versions 1.4.0 to 1.5.0 might crash due to an uncaught exception. Parsing chunked HTTP requests with trailers can lead to a libprocess crash too because of the mistakenly planted assertion. A malicious actor can therefore cause a denial of service of Mesos masters rendering the Mesos-controlled cluster inoperable.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2018-1330",
"description": "When parsing a malformed JSON payload, libprocess in Apache Mesos versions 1.4.0 to 1.5.0 might crash due to an uncaught exception. Parsing chunked HTTP requests with trailers can lead to a libprocess crash too because of the mistakenly planted assertion. A malicious actor can therefore cause a denial of service of Mesos masters rendering the Mesos-controlled cluster inoperable.",
"id": "GSD-2018-1330"
},
"gsd": {
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"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
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"id": "GSD-2018-1330",
"modified": "2023-12-13T01:22:37.129477Z",
"schema_version": "1.4.0"
}
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"cwe_ids": [
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"CWE-20",
"CWE-937"
],
"date": "2019-01-29",
"description": "When parsing a malformed JSON payload, libprocess in Apache Mesos crashes due to an uncaught exception. Parsing chunked HTTP requests with trailers can lead to a libprocess crash because of the mistakenly planted assertion.",
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"package_slug": "maven/org.apache.mesos/mesos",
"pubdate": "2018-09-13",
"solution": "Upgrade to versions 1.5.2, 1.6.1 or above.",
"title": "Improper Input Validation",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2018-1330"
],
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"impact": {
"baseMetricV2": {
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"cvssV2": {
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"accessVector": "NETWORK",
"authentication": "NONE",
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"baseScore": 5.0,
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"vectorString": "AV:N/AC:L/Au:N/C:N/I:N/A:P",
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},
"lastModifiedDate": "2019-01-29T13:53Z",
"publishedDate": "2018-09-13T19:29Z"
}
}
}
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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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