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    2 vulnerabilities found for OneCompression by Fujitsu Research

    CVE-2026-73325 (GCVE-0-2026-73325)

    Vulnerability from nvd – Published: 2026-08-12 15:35 – Updated: 2026-08-25 01:15
    VLAI
    Title
    Fujitsu OneCompression < 1.2.1 Arbitrary Code Execution via torch.load Deserialization
    Summary
    Fujitsu Research's OneCompression library before 1.2.1 contains an unsafe deserialization vulnerability that allows attackers to execute arbitrary code by supplying a crafted model.pt checkpoint file, as QuantizedModelLoader.load_quantized_model_pt() unconditionally calls torch.load with weights_only=False, invoking Python's pickle machinery during deserialization. Attackers can embed malicious __reduce__ methods in a crafted model checkpoint to execute arbitrary Python code, including system commands, when the library loads the file from a caller-selected model directory.
    Severity
    8.4 (High)
    CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
    7.8 (High)
    CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
    SSVC
    Exploitation: none Automatable: no Technical Impact: total
    CISA Coordinator · CISA-ADP (v2.0.3)
    Decision recorded 2026-08-12 17:03 UTC
    CWE
    • CWE-502 - Deserialization of Untrusted Data
    Assigner
    References
    Impacted products
    Vendor Product Version
    Fujitsu Research OneCompression Affected: 0 , < 1.2.1 (custom)
    		Create a notification for this product.
    Date Public
    2026-08-12 00:00
    Credits
    Nir Yehoshua from Cipher Security Labs
    Show details on NVD website
    To clipboard 

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    CVE-2026-73325 (GCVE-0-2026-73325)

    Vulnerability from cvelistv5 – Published: 2026-08-12 15:35 – Updated: 2026-08-25 01:15
    VLAI
    Title
    Fujitsu OneCompression < 1.2.1 Arbitrary Code Execution via torch.load Deserialization
    Summary
    Fujitsu Research's OneCompression library before 1.2.1 contains an unsafe deserialization vulnerability that allows attackers to execute arbitrary code by supplying a crafted model.pt checkpoint file, as QuantizedModelLoader.load_quantized_model_pt() unconditionally calls torch.load with weights_only=False, invoking Python's pickle machinery during deserialization. Attackers can embed malicious __reduce__ methods in a crafted model checkpoint to execute arbitrary Python code, including system commands, when the library loads the file from a caller-selected model directory.
    Severity
    8.4 (High)
    CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
    7.8 (High)
    CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
    SSVC
    Exploitation: none Automatable: no Technical Impact: total
    CISA Coordinator · CISA-ADP (v2.0.3)
    Decision recorded 2026-08-12 17:03 UTC
    CWE
    • CWE-502 - Deserialization of Untrusted Data
    Assigner
    References
    Impacted products
    Vendor Product Version
    Fujitsu Research OneCompression Affected: 0 , < 1.2.1 (custom)
    		Create a notification for this product.
    Date Public
    2026-08-12 00:00
    Credits
    Nir Yehoshua from Cipher Security Labs
    Show details on NVD website
    To clipboard 

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