GSD-2023-39946
Vulnerability from gsd - Updated: 2023-12-13 01:20Details
eprosima Fast DDS is a C++ implementation of the Data Distribution Service standard of the Object Management Group. Prior to versions 2.11.1, 2.10.2, 2.9.2, and 2.6.6, heap can be overflowed by providing a PID_PROPERTY_LIST parameter that contains a CDR string with length larger than the size of actual content. In `eprosima::fastdds::dds::ParameterPropertyList_t::push_back_helper`, `memcpy` is called to first copy the octet'ized length and then to copy the data into `properties_.data`. At the second memcpy, both `data` and `size` can be controlled by anyone that sends the CDR string to the discovery multicast port. This can remotely crash any Fast-DDS process. Versions 2.11.1, 2.10.2, 2.9.2, and 2.6.6 contain a patch for this issue.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2023-39946",
"id": "GSD-2023-39946"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
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"details": "eprosima Fast DDS is a C++ implementation of the Data Distribution Service standard of the Object Management Group. Prior to versions 2.11.1, 2.10.2, 2.9.2, and 2.6.6, heap can be overflowed by providing a PID_PROPERTY_LIST parameter that contains a CDR string with length larger than the size of actual content. In `eprosima::fastdds::dds::ParameterPropertyList_t::push_back_helper`, `memcpy` is called to first copy the octet\u0027ized length and then to copy the data into `properties_.data`. At the second memcpy, both `data` and `size` can be controlled by anyone that sends the CDR string to the discovery multicast port. This can remotely crash any Fast-DDS process. Versions 2.11.1, 2.10.2, 2.9.2, and 2.6.6 contain a patch for this issue.",
"id": "GSD-2023-39946",
"modified": "2023-12-13T01:20:33.728432Z",
"schema_version": "1.4.0"
}
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"lastModifiedDate": "2023-08-22T14:21Z",
"publishedDate": "2023-08-11T14:15Z"
}
}
}
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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
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Nomenclature
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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
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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
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