GHSA-4R4C-66GF-G9G5
Vulnerability from github – Published: 2024-05-28 21:22 – Updated: 2024-05-28 21:22
VLAI
Summary
rockhopper Buffer Overflow vulnerability
Details
A vulnerability, which was classified as critical, has been found in bwoodsend rockhopper up to 0.1.2. Affected by this issue is the function count_rows of the file rockhopper/src/ragged_array.c of the component Binary Parser. The manipulation of the argument raw leads to buffer overflow. Local access is required to approach this attack. Upgrading to version 0.2.0 is able to address this issue. The name of the patch is 1a15fad5e06ae693eb9b8908363d2c8ef455104e. It is recommended to upgrade the affected component. The identifier of this vulnerability is VDB-266312.
Severity
5.3 (Medium)
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 0.1.2"
},
"package": {
"ecosystem": "PyPI",
"name": "rockhopper"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.2.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2022-4969"
],
"database_specific": {
"cwe_ids": [
"CWE-120"
],
"github_reviewed": true,
"github_reviewed_at": "2024-05-28T21:22:45Z",
"nvd_published_at": "2024-05-27T17:15:09Z",
"severity": "MODERATE"
},
"details": "A vulnerability, which was classified as critical, has been found in bwoodsend rockhopper up to 0.1.2. Affected by this issue is the function `count_rows` of the file `rockhopper/src/ragged_array.c` of the component Binary Parser. The manipulation of the argument raw leads to buffer overflow. Local access is required to approach this attack. Upgrading to version 0.2.0 is able to address this issue. The name of the patch is 1a15fad5e06ae693eb9b8908363d2c8ef455104e. It is recommended to upgrade the affected component. The identifier of this vulnerability is VDB-266312.",
"id": "GHSA-4r4c-66gf-g9g5",
"modified": "2024-05-28T21:22:45Z",
"published": "2024-05-28T21:22:45Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-4969"
},
{
"type": "WEB",
"url": "https://github.com/bwoodsend/rockhopper/commit/1a15fad5e06ae693eb9b8908363d2c8ef455104e"
},
{
"type": "PACKAGE",
"url": "https://github.com/bwoodsend/rockhopper"
},
{
"type": "WEB",
"url": "https://github.com/bwoodsend/rockhopper/releases/tag/v0.2.0"
},
{
"type": "WEB",
"url": "https://vuldb.com/?ctiid.266312"
},
{
"type": "WEB",
"url": "https://vuldb.com/?id.266312"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L",
"type": "CVSS_V3"
}
],
"summary": "rockhopper Buffer Overflow vulnerability"
}
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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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