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optuna Pickle Deserialization RCE PoC (CWE-502)
Proof of Concept for arbitrary code execution via two independent pickle.loads() sinks in optuna <= 4.9.0 (latest on PyPI).
Vulnerability
optuna uses raw pickle.loads() on data from shared external storage backends with zero security mitigations:
Sink 1: CMA-ES Sampler (samplers/_cmaes.py:504)
return pickle.loads(bytes.fromhex(optimizer_str))
The CMA-ES sampler serializes optimizer state via pickle.dumps().hex() and stores it in trial system_attrs in the shared database (MySQL/PostgreSQL/SQLite). When any optuna worker restores a previous optimizer via _restore_optimizer(), the hex-encoded pickle is deserialized without any validation.
Attack vector: An attacker with write access to the shared database inserts a malicious hex-encoded pickle payload into the trial_system_attributes table with a key matching cma:optimizer:N. Any worker using CmaEsSampler that reads trials from this database will execute arbitrary code.
Sink 2: JournalRedisBackend Snapshot (storages/journal/_storage.py:129)
r: JournalStorageReplayResult | None = pickle.loads(snapshot)
The JournalStorage saves periodic snapshots via pickle.dumps() to Redis. When a new JournalStorage instance is created, the constructor calls load_snapshot() then restore_replay_result() which calls pickle.loads() on the raw Redis bytes.
Attack vector: An attacker with write access to the Redis server (commonly unprotected, default no-auth) sets the {prefix}:snapshot key to a malicious pickle payload. Any optuna process that connects to this Redis backend will execute arbitrary code during initialization, before any user code runs.
Note: The isinstance() check on line 135 is NOT a security mitigation -- it runs after pickle.loads() has already executed. In pickle attacks, __reduce__ runs during deserialization itself.
Reproduction
pip install optuna==4.9.0
python verify_bypass.py
Expected output: [+] *** RCE CONFIRMED via Sink 1 (CMA-ES)! *** and [+] *** RCE CONFIRMED via Sink 2 (Redis snapshot)! ***
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