GHSA-p523-jq9w-64x9

Описание

Fickling's assessment

cProfile was added to the list of unsafe imports (https://github.com/trailofbits/fickling/commit/dc8ae12966edee27a78fe05c5745171a2b138d43).

Original report

Description

Summary

Fickling versions up to and including 0.1.6 do not treat Python's cProfile module as unsafe. Because of this, a malicious pickle that uses cProfile.run() is classified as SUSPICIOUS instead of OVERTLY_MALICIOUS.

If a user relies on Fickling's output to decide whether a pickle is safe to deserialize, this misclassification can lead them to execute attacker-controlled code on their system.

This affects any workflow or product that uses Fickling as a security gate for pickle deserialization.

Details

The cProfile module is missing from fickling's block list of unsafe module imports in fickling/analysis.py. This is the same root cause as CVE-2025-67748 (pty) and CVE-2025-67747 (marshal/types).

Incriminated source code:

• File: fickling/analysis.py
• Class: UnsafeImports
• Issue: The blocklist does not include cProfile, cProfile.run, or cProfile.runctx

Reference to similar fix:

• PR #187 added pty to the blocklist to fix CVE-2025-67748
• PR #108 documented the blocklist approach
• The same fix pattern should be applied for cProfile

How the bypass works:

1. Attacker creates a pickle using cProfile.run() in __reduce__
2. cProfile.run() accepts a Python code string and executes it directly (C-accelerated version of profile.run)
3. Fickling's UnsafeImports analysis does not flag cProfile as dangerous
4. Only the UnusedVariables heuristic triggers, resulting in SUSPICIOUS severity
5. The pickle should be rated OVERTLY_MALICIOUS like os.system, eval, and exec

Tested behavior (fickling 0.1.6):

Suggested fix:

Add to the unsafe imports blocklist in fickling/analysis.py:

• cProfile
• cProfile.run
• cProfile.runctx
• _lsprof (underlying C module)

PoC

Complete instructions, including specific configuration details, to reproduce the vulnerability.

Environment:

• Python 3.13.2
• fickling 0.1.6 (latest version, installed via pip)

Step 1: Create malicious pickle

Step 2: Analyze with fickling

Expected output (if properly detected):

Actual output (bypass confirmed):

Step 3: Prove RCE by loading the pickle

Output

Check: The code executes, proving RCE.

Pickle disassembly (evidence):

Impact

Vulnerability Type:

Incomplete blocklist leading to safety check bypass (CWE-184) and arbitrary code execution via insecure deserialization (CWE-502).

Who is impacted:

Any user or system that relies on fickling to vet pickle files for security issues before loading them. This includes:

• ML model validation pipelines
• Model hosting platforms (Hugging Face, MLflow, etc.)
• Security scanning tools that use fickling
• CI/CD pipelines that validate pickle artifacts

Attack scenario:

An attacker uploads a malicious ML model or pickle file to a model repository. The victim's pipeline uses fickling to scan uploads. Fickling rates the file as "SUSPICIOUS" (not "OVERTLY_MALICIOUS"), so the file is not rejected. When the victim loads the model, arbitrary code executes on their system.

Why cProfile.run() is dangerous:

Unlike runpy.run_path() which requires a file on disk, cProfile.run() takes a code string directly. This means the entire attack is self-contained in the pickle - no external files needed. Python docs explicitly state that cProfile.run() takes "a single argument that can be passed to the exec() function".

cProfile is the C-accelerated version and is more commonly available than profile. It's also the recommended profiler per Python docs ("cProfile is recommended for most users"), so it's present in virtually all Python installations.

Severity: HIGH

• The attacker achieves arbitrary code execution
• The security control (fickling) is specifically designed to prevent this
• The bypass requires no special conditions beyond crafting the pickle with cProfile
• Attack is fully self-contained (no external files needed)
• cProfile is more commonly used than profile, increasing attack surface