CVE-2026-108955 (GCVE-0-2026-108955)

Vulnerability from cvelistv5 – Published: 2026-10-13 01:45 – Updated: 2026-10-13 01:45
VLAI
Title
Tiiny-AI PowerInfer GGUF ggml.c gguf_init_from_file out-of-bounds
Summary
A vulnerability was determined in Tiiny-AI PowerInfer up to 8bd56d69906c9d2dba4d3bf6899763401e01a9a4. Impacted is the function gguf_init_from_file of the file ggml.c of the component GGUF Parser. This manipulation of the argument data_offset causes out-of-bounds read. The attack requires local access. The exploit has been publicly disclosed and may be utilized. This product uses a rolling release model to deliver continuous updates. As a result, specific version information for affected or updated releases is not available. The pull request to fix this issue awaits acceptance.
Severity
4.8 (Medium)
CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P
5.3 (Medium)
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L/E:P/RL:X/RC:R
5.3 (Medium)
CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L/E:P/RL:X/RC:R
CWE
Assigner
VulDB CNA under the mitre root
CNA scorecard B 82/100 over 3868 records in the last 180 days details
References
URL Tags
https://vuldb.com/vuln/416774 vdb-entrytechnical-description
https://vuldb.com/vuln/416774/cti signaturepermissions-required
https://vuldb.com/cve/CVE-2026-108955 third-party-advisory
https://vuldb.com/submit/997844 third-party-advisory
https://github.com/Tiiny-AI/PowerInfer/issues/283 exploitissue-tracking
https://github.com/Tiiny-AI/PowerInfer/ product
Impacted products
Vendor Product Version CPE status
Tiiny-AI PowerInfer Affected: 8bd56d69906c9d2dba4d3bf6899763401e01a9a4
    cpe:2.3:a:tiiny-ai:powerinfer:*:*:*:*:*:*:*:*
Create a notification for this product.
Credits
dem0000 (VulDB User) VulDB CNA Team
Show details on NVD website
To clipboard 

{
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          "value": "VulDB entry last update"
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      "title": "Tiiny-AI PowerInfer GGUF ggml.c gguf_init_from_file out-of-bounds",
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    "dateReserved": "2026-10-11T19:11:22.275Z",
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    "state": "PUBLISHED"
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                ],
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          }
        ],
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        "lastModified": "2026-10-13T13:29:12.567",
        "metrics": {
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                "Recovery": "NOT_DEFINED",
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                "modifiedAttackRequirements": "NOT_DEFINED",
                "modifiedAttackVector": "NOT_DEFINED",
                "modifiedPrivilegesRequired": "NOT_DEFINED",
                "modifiedSubAvailabilityImpact": "NOT_DEFINED",
                "modifiedSubConfidentialityImpact": "NOT_DEFINED",
                "modifiedSubIntegrityImpact": "NOT_DEFINED",
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}



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Tags
Taxonomy of the tags.





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.



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.