Fujitsu OneCompression < 1.2.1 Arbitrary Code Execution via torch.load Deserialization
Default status is the baseline for the product, each version can override it (e.g. patched versions marked unaffected).
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| Fujitsu Research | OneCompression | affected |
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| Fujitsu Research | Onecompression |
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No CVSS v3.0
No CVSS v2
This CVE is not in the KEV list.
Exploit prediction score: < 1% (0.400% probability within 30 days)
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| Description | 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. | 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. |
| Title | Fujitsu OneCompression 1.2.0 Arbitrary Code Execution via torch.load Deserialization | Fujitsu OneCompression < 1.2.1 Arbitrary Code Execution via torch.load Deserialization |
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| First Time appeared |
Fujitsu Research
Fujitsu Research onecompression |
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| Vendors & Products |
Fujitsu Research
Fujitsu Research onecompression |
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| Metrics |
ssvc
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| Description | 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. | |
| Title | Fujitsu OneCompression 1.2.0 Arbitrary Code Execution via torch.load Deserialization | |
| Weaknesses | CWE-502 | |
| References |
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| Metrics |
cvssV3_1
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