GHSA-4H53-XCVW-8WPX
Vulnerability from github – Published: 2024-05-17 12:31 – Updated: 2026-05-12 12:31
VLAI
Details
In the Linux kernel, the following vulnerability has been resolved:
cpumap: Zero-initialise xdp_rxq_info struct before running XDP program
When running an XDP program that is attached to a cpumap entry, we don't initialise the xdp_rxq_info data structure being used in the xdp_buff that backs the XDP program invocation. Tobias noticed that this leads to random values being returned as the xdp_md->rx_queue_index value for XDP programs running in a cpumap.
This means we're basically returning the contents of the uninitialised memory, which is bad. Fix this by zero-initialising the rxq data structure before running the XDP program.
Severity
5.5 (Medium)
{
"affected": [],
"aliases": [
"CVE-2024-27431"
],
"database_specific": {
"cwe_ids": [
"CWE-908"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2024-05-17T12:15:16Z",
"severity": "MODERATE"
},
"details": "In the Linux kernel, the following vulnerability has been resolved:\n\ncpumap: Zero-initialise xdp_rxq_info struct before running XDP program\n\nWhen running an XDP program that is attached to a cpumap entry, we don\u0027t\ninitialise the xdp_rxq_info data structure being used in the xdp_buff\nthat backs the XDP program invocation. Tobias noticed that this leads to\nrandom values being returned as the xdp_md-\u003erx_queue_index value for XDP\nprograms running in a cpumap.\n\nThis means we\u0027re basically returning the contents of the uninitialised\nmemory, which is bad. Fix this by zero-initialising the rxq data\nstructure before running the XDP program.",
"id": "GHSA-4h53-xcvw-8wpx",
"modified": "2026-05-12T12:31:46Z",
"published": "2024-05-17T12:31:01Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-27431"
},
{
"type": "WEB",
"url": "https://cert-portal.siemens.com/productcert/html/ssa-265688.html"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/2487007aa3b9fafbd2cb14068f49791ce1d7ede5"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/3420b3ff1ff489c177ea1cb7bd9fbbc4e9a0be95"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/5f4e51abfbe6eb444fa91906a5cd083044278297"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/eaa7cb836659ced2d9f814ac32aa3ec193803ed6"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/f0363af9619c77730764f10360e36c6445c12f7b"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/f562e4c4aab00986dde3093c4be919c3f2b85a4a"
},
{
"type": "WEB",
"url": "https://lists.debian.org/debian-lts-announce/2024/06/msg00017.html"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
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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.
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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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