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GHSA-q5qq-mvfm-j35x

Опубликовано: 09 янв. 2026
Источник: github
Github: Прошло ревью
CVSS4: 8.9

Описание

Fickling has Static Analysis Bypass via Incomplete Dangerous Module Blocklist

#Fickling's assessment

ctypes, importlib, runpy, code and multiprocessing were added the list of unsafe imports (https://github.com/trailofbits/fickling/commit/9a2b3f89bd0598b528d62c10a64c1986fcb09f66, https://github.com/trailofbits/fickling/commit/eb299b453342f1931c787bcb3bc33f3a03a173f9, https://github.com/trailofbits/fickling/commit/29d5545e74b07766892c1f0461b801afccee4f91, https://github.com/trailofbits/fickling/commit/b793563e60a5e039c5837b09d7f4f6b92e6040d1, https://github.com/trailofbits/fickling/commit/b793563e60a5e039c5837b09d7f4f6b92e6040d1).

Original report

Summary

The unsafe_imports() method in Fickling's static analyzer fails to flag several high-risk Python modules that can be used for arbitrary code execution. Malicious pickles importing these modules will not be detected as unsafe, allowing attackers to bypass Fickling's primary static safety checks.

Details

In fickling/fickle.py lines 866-884, the unsafe_imports() method checks imported modules against a hardcoded tuple:

def unsafe_imports(self) -> Iterator[ast.Import | ast.ImportFrom]: for node in self.properties.imports: if node.module in ( "__builtin__", "__builtins__", "builtins", "os", "posix", "nt", "subprocess", "sys", "builtins", "socket", "pty", "marshal", "types", ): yield node

This list is incomplete. The following dangerous modules are NOT detected:

  • ctypes: Allows arbitrary memory access, calling C functions, and bypassing Python restrictions entirely
  • importlib: Can dynamically import any module at runtime
  • runpy: Can execute Python modules as scripts
  • code: Can compile and execute arbitrary Python code
  • multiprocessing: Can spawn processes with arbitrary code

Since ctypes is part of the Python standard library, it also bypasses the NonStandardImports analysis.

PoC

from fickling.fickle import Pickled from fickling.analysis import check_safety, Severity # Pickle that imports ctypes.pythonapi (allows arbitrary code execution) # PROTO 4, GLOBAL 'ctypes pythonapi', STOP payload = b'\x80\x04cctypes\npythonapi\n.' pickled = Pickled.load(payload) results = check_safety(pickled) print(f"Severity: {results.severity.name}") print(f"Is safe: {results.severity == Severity.LIKELY_SAFE}") # Output: Severity is LIKELY_SAFE or low - the ctypes import is not flagged # A truly malicious pickle using ctypes could execute arbitrary code

Impact

Security Bypass (Confidentiality, Integrity, Availability)

An attacker can craft a malicious pickle that:

  1. Imports ctypes to gain arbitrary memory access
  2. Uses ctypes.pythonapi or ctypes.CDLL to execute arbitrary code
  3. Passes Fickling's safety analysis as "likely safe"
  4. Executes malicious code when the victim loads the pickle after trusting Fickling's verdict

This undermines the core purpose of Fickling as a pickle safety scanner.

Пакеты

Наименование

fickling

pip
Затронутые версииВерсия исправления

<= 0.1.6

0.1.7

EPSS

Процентиль: 25%
0.00083
Низкий

8.9 High

CVSS4

Дефекты

CWE-184
CWE-502

Связанные уязвимости

CVSS3: 7.8
nvd
10 дней назад

Fickling is a Python pickling decompiler and static analyzer. Prior to version 0.1.7, the unsafe_imports() method in Fickling's static analyzer fails to flag several high-risk Python modules that can be used for arbitrary code execution. Malicious pickles importing these modules will not be detected as unsafe, allowing attackers to bypass Fickling's primary static safety checks. This issue has been patched in version 0.1.7.

EPSS

Процентиль: 25%
0.00083
Низкий

8.9 High

CVSS4

Дефекты

CWE-184
CWE-502