Vulnerability-Lookup

GHSA-H765-5XQM-7H48

Vulnerability from github – Published: 2024-05-21 18:31 – Updated: 2024-11-05 21:30

Details

In the Linux kernel, the following vulnerability has been resolved:

wifi: wilc1000: use vmm_table as array in wilc struct

Enabling KASAN and running some iperf tests raises some memory issues with vmm_table:

BUG: KASAN: slab-out-of-bounds in wilc_wlan_handle_txq+0x6ac/0xdb4 Write of size 4 at addr c3a61540 by task wlan0-tx/95

KASAN detects that we are writing data beyond range allocated to vmm_table. There is indeed a mismatch between the size passed to allocator in wilc_wlan_init, and the range of possible indexes used later: allocation size is missing a multiplication by sizeof(u32)

Severity

5.6 (Medium)


                  
                    CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:U/C:L/I:L/A:H

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{
  "affected": [],
  "aliases": [
    "CVE-2023-52768"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-129"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-05-21T16:15:15Z",
    "severity": "MODERATE"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nwifi: wilc1000: use vmm_table as array in wilc struct\n\nEnabling KASAN and running some iperf tests raises some memory issues with\nvmm_table:\n\nBUG: KASAN: slab-out-of-bounds in wilc_wlan_handle_txq+0x6ac/0xdb4\nWrite of size 4 at addr c3a61540 by task wlan0-tx/95\n\nKASAN detects that we are writing data beyond range allocated to vmm_table.\nThere is indeed a mismatch between the size passed to allocator in\nwilc_wlan_init, and the range of possible indexes used later: allocation\nsize is missing a multiplication by sizeof(u32)",
  "id": "GHSA-h765-5xqm-7h48",
  "modified": "2024-11-05T21:30:32Z",
  "published": "2024-05-21T18:31:20Z",
  "references": [
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      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-52768"
    },
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      "type": "WEB",
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      "url": "https://git.kernel.org/stable/c/3ce1c2c3999b232258f7aabab311d47dda75605c"
    },
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    },
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      "type": "WEB",
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      "type": "CVSS_V3"
    }
  ]
}

CVE-2023-52768 (GCVE-0-2023-52768)

Vulnerability from cvelistv5 – Published: 2024-05-21 15:30 – Updated: 2026-08-05 09:11

Title

wifi: wilc1000: use vmm_table as array in wilc struct

Summary

In the Linux kernel, the following vulnerability has been resolved: wifi: wilc1000: use vmm_table as array in wilc struct Enabling KASAN and running some iperf tests raises some memory issues with vmm_table: BUG: KASAN: slab-out-of-bounds in wilc_wlan_handle_txq+0x6ac/0xdb4 Write of size 4 at addr c3a61540 by task wlan0-tx/95 KASAN detects that we are writing data beyond range allocated to vmm_table. There is indeed a mismatch between the size passed to allocator in wilc_wlan_init, and the range of possible indexes used later: allocation size is missing a multiplication by sizeof(u32)

Severity

7.8 (High)


                        
                          CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

5.6 (Medium)


                        
                          CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:U/C:L/I:L/A:H

SSVC

Exploitation: none Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2024-05-29 18:50 UTC

CWE

CWE-noinfo Not enough information

Assigner

Linux mitre root

References

5 references

URL	Tags
https://git.kernel.org/stable/c/541b3757fd443a68e…
https://git.kernel.org/stable/c/4b0d6ddb6466d10df…
https://git.kernel.org/stable/c/6aaf7cd8bdfe245d3…
https://git.kernel.org/stable/c/3ce1c2c3999b23225…
https://git.kernel.org/stable/c/05ac1a198a63ad66b…

Impacted products

2 products

Vendor	Product	Version
Linux	Linux	Affected: 32dd0b22a5ba1dd296ccf2caf46ad44c3a8d5d98 , < 541b3757fd443a68ed8d25968eae511a8275e7c8 (git) Affected: 40b717bfcefab28a0656b8caa5e43d5449e5a671 , < 4b0d6ddb6466d10df878a7787f175a0e4adc3e27 (git) Affected: 40b717bfcefab28a0656b8caa5e43d5449e5a671 , < 6aaf7cd8bdfe245d3c9a8b48fe70c2011965948e (git) Affected: 40b717bfcefab28a0656b8caa5e43d5449e5a671 , < 3ce1c2c3999b232258f7aabab311d47dda75605c (git) Affected: 40b717bfcefab28a0656b8caa5e43d5449e5a671 , < 05ac1a198a63ad66bf5ae8b7321407c102d40ef3 (git) Affected: 5212d958f6518003cd98c9886f8e8aedcfc25741 (git) Affected: 5.15.68 , < 5.15.140 (semver) Affected: 5.19.9 , < 5.20 (semver)
Linux	Linux	Affected: 6.0 Unaffected: 0 , < 6.0 (semver) Unaffected: 5.15.140 , ≤ 5.15.* (semver) Unaffected: 6.1.64 , ≤ 6.1.* (semver) Unaffected: 6.5.13 , ≤ 6.5.* (semver) Unaffected: 6.6.3 , ≤ 6.6.* (semver) Unaffected: 6.7 , ≤ * (original_commit_for_fix)

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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.

Detection rules are retrieved from Rulezet.

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.

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.