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Fickling has Static Analysis Bypass via Incomplete Dangerous Module Blocklist

High severity GitHub Reviewed Published Jan 9, 2026 in trailofbits/fickling • Updated Jan 11, 2026

Package

pip fickling (pip)

Affected versions

<= 0.1.6

Patched versions

0.1.7

Description

#Fickling's assessment

ctypes, importlib, runpy, code and multiprocessing were added the list of unsafe imports (trailofbits/fickling@9a2b3f8, trailofbits/fickling@eb299b4, trailofbits/fickling@29d5545, trailofbits/fickling@b793563, trailofbits/fickling@b793563).

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.

References

@thomas-chauchefoin-tob thomas-chauchefoin-tob published to trailofbits/fickling Jan 9, 2026
Published to the GitHub Advisory Database Jan 9, 2026
Reviewed Jan 9, 2026
Published by the National Vulnerability Database Jan 10, 2026
Last updated Jan 11, 2026

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality High
Integrity High
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:P

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(34th percentile)

Weaknesses

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. Learn more on MITRE.

Deserialization of Untrusted Data

The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid. Learn more on MITRE.

CVE ID

CVE-2026-22609

GHSA ID

GHSA-q5qq-mvfm-j35x

Source code

Credits

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