By Null Ventures MCP platform
Menu

vulnerability / NVI-00016347 / Revision 1

Picklescan missing detection when calling built-in python library function timeit.timeit()

GitHub lists this reviewed advisory for picklescan. Published version ranges and source prerequisites are shown below; this is not an inspection of a visitor’s application.

source listedactiveGHSA-v7x6-rv5q-mhwcCVE-2025-71351

This report has not inspected your inventory, configuration, deployed build, reachability or evidence. A catalog listing and a severity score do not establish exposure or compromise.

01 / Meaning

Why it matters

Published affected context helps an owner decide what evidence to gather. This report has not examined your application.

02 / Applicability

The affected context

Affected versions, configuration prerequisites and known exclusions are public. Confirm each one against the deployed service.

picklescan

source listed
  • < 0.0.25

### Summary Using timeit.timeit() function, which is a built-in python library function to execute remote pickle file. ### Details Pickle’s deserialization process is known to allow execution of function via reduce method. While Picklescan is meant to detect such exploits, this attack evades detection by calling built-in python library function like **timeit.timeit()**. And since timeit library wasn't inside unsafe globals blacklist, it may not raise red flag in the security scan. The attack payload executes in the following steps: First, the attacker craft the payload by calling to **timeit.timeit()** function from timeit library in __reduce__ method Then, inside reduce method, the attacker import dangerous libarary like os and calling **os.system()** to run OS commands, for example: curl command. And then the attacker send this malicious pickle file to the victim. Then when the victim after checking whether the pickle file is safe by using Picklescan library and this library doesn't dectect any dangerous functions, decide to pickle.load() this malicious pickle file, thus lead to remote code execution. ### PoC 1. The attacker crafted a malicious pickle file using built-in pyth

GitHub Advisory Database

03 / Response

What to do next

  1. investigate

    Identify the exact component and deployed version, examine the linked publisher’s conditions, and retain evidence of any mitigation.

    Confirm current vendor support, compatibility and deployment evidence. This report has not tested a fix in your system. GitHub Advisory Database

A fixed release is not deployment evidence.

Check current vendor support and compatibility. After making a change, verify the deployed build and relevant runtime conditions. Keep the evidence, owner and time. An updated lockfile alone does not prove what is running.

04 / Limits

What this report cannot establish

  • Customer inventory, deployment, reachability and exploitation have not been inspected.
Read the collection and interpretation limits ↗

05 / Provenance

Sources you can inspect

Each assertion retains its source. Mirrored records may repeat one underlying publisher; additional links are not independent corroboration.

  1. GHSA-v7x6-rv5q-mhwc ↗

    GitHub Advisory Database · vendor advisory

    Observed . GitHub Advisory Database; CC-BY-4.0. Each advisory links its original attribution. Null normalizes fields.

Public revision history

Only published revisions appear here. Routine fetches do not create a material-change event.

  1. Revision 1 ·

    First indexed by Null; source disclosure date is shown separately.

Read the public revision data ↗

The next step is private

Bring the question into your environment.

The connected workflow is a development preview for inventory, contextual matching, owner decisions and evidence-based verification. No system-specific result is generated by this page.

See the synthetic workflow preview ↗