Answer in brief
CVE-2026-73325 records a Unknown severity vulnerability in Fujitsu OneCompression 1.2.0 Arbitrary Code Execution via torch.load Deserialization. The current sources do not mark it as known exploited. The current feed maps Fujitsu Research/OneCompression (generic). Check affected ranges and fixed versions before updating.
Analysis pending evidence review
HOL Guard separates source facts from reviewed analysis. See the methodology.
A CVSS score is not reported in the current record. The current sources do not mark it as known exploited. Treat this as a source-backed prioritization signal, not a statement about your environment.
Analysis status
Analysis pending evidence review
Factual feed record only; HOL analysis is not approved for indexing. Read the methodology.
The current feed maps Fujitsu Research/OneCompression (generic). Check affected ranges and fixed versions before updating.
| Package | Affected range | Fixed version |
|---|---|---|
| Fujitsu Research/OneCompressiongeneric | 0 | Not reported |
Published upstream
Aug 12, 2026
Evidence: source:cvelist:source_dates:source-dates:recordSource modified
Aug 12, 2026
Evidence: source:cvelist:source_dates:source-dates:recordFirst seen by HOL
Aug 12, 2026
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.
Quoted source text, attributed separately from HOL analysis.
Answer in brief
CVE-2026-73325 records a Unknown severity vulnerability in Fujitsu OneCompression 1.2.0 Arbitrary Code Execution via torch.load Deserialization. The current sources do not mark it as known exploited. The current feed maps Fujitsu Research/OneCompression (generic). Check affected ranges and fixed versions before updating.
Analysis pending evidence review
HOL Guard separates source facts from reviewed analysis. See the methodology.
A CVSS score is not reported in the current record. The current sources do not mark it as known exploited. Treat this as a source-backed prioritization signal, not a statement about your environment.
Analysis status
Analysis pending evidence review
Factual feed record only; HOL analysis is not approved for indexing. Read the methodology.
The current feed maps Fujitsu Research/OneCompression (generic). Check affected ranges and fixed versions before updating.
| Package | Affected range | Fixed version |
|---|---|---|
| Fujitsu Research/OneCompressiongeneric | 0 | Not reported |
Published upstream
Aug 12, 2026
Evidence: source:cvelist:source_dates:source-dates:recordSource modified
Aug 12, 2026
Evidence: source:cvelist:source_dates:source-dates:recordFirst seen by HOL
Aug 12, 2026
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.
Quoted source text, attributed separately from HOL analysis.