GSD-2022-36040
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
Rizin is a UNIX-like reverse engineering framework and command-line toolset. Versions 0.4.0 and prior are vulnerable to an out-of-bounds write when getting data from PYC(python) files. A user opening a malicious PYC file could be affected by this vulnerability, allowing an attacker to execute code on the user's machine. Commit number 68948017423a12786704e54227b8b2f918c2fd27 contains a patch.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2022-36040",
"description": "Rizin is a UNIX-like reverse engineering framework and command-line toolset. Versions 0.4.0 and prior are vulnerable to an out-of-bounds write when getting data from PYC(python) files. A user opening a malicious PYC file could be affected by this vulnerability, allowing an attacker to execute code on the user\u0027s machine. Commit number 68948017423a12786704e54227b8b2f918c2fd27 contains a patch.",
"id": "GSD-2022-36040"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
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"id": "GSD-2022-36040",
"modified": "2023-12-13T01:19:21.607683Z",
"schema_version": "1.4.0"
}
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"TITLE": "Rizin Out-of-bounds Write vulnerability in pyc/marshal.c"
},
"affects": {
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}
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"baseScore": 7.8,
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"url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/WQZLMHEI5D7EJASA5UW6XN4ODHLRHK6N/"
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"url": "https://github.com/rizinorg/rizin/commit/68948017423a12786704e54227b8b2f918c2fd27"
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"impact": {
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"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 7.8,
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"confidentialityImpact": "HIGH",
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"privilegesRequired": "NONE",
"scope": "UNCHANGED",
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"vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
"version": "3.1"
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"exploitabilityScore": 1.8,
"impactScore": 5.9
}
},
"lastModifiedDate": "2023-03-30T04:15Z",
"publishedDate": "2022-09-06T20:15Z"
}
}
}
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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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