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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: 2026-08-12 19:19
    VLAI
    Title
    Fujitsu OneCompression 1.2.0 Arbitrary Code Execution via torch.load Deserialization
    Summary
    Fujitsu Research's OneCompression library 1.2.0 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 , ≤ 1.2.0 (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: 2026-08-12 19:19
    VLAI
    Title
    Fujitsu OneCompression 1.2.0 Arbitrary Code Execution via torch.load Deserialization
    Summary
    Fujitsu Research's OneCompression library 1.2.0 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 , ≤ 1.2.0 (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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