Summary
A Remote Code Execution (RCE) vulnerability caused by insecure deserialization has been identified in the latest version(v1.4.2) of BentoML. It allows any unauthenticated user to execute arbitrary code on the server.
Details
It exists an unsafe code segment in serde.py:
def deserialize_value(self, payload: Payload) -> t.Any:
if "buffer-lengths" not in payload.metadata:
return pickle.loads(b"".join(payload.data))
Through data flow analysis, it is confirmed that the payload content is sourced from an HTTP request, which can be fully manipulated by the attack. Due to the lack of validation in the code, maliciously crafted serialized data can execute harmful actions during deserialization.
PoC
Environment:
- Server host:
- IP: 10.98.36.123
- OS: Ubuntu
- Attack host:
- IP: 10.98.36.121
- OS: Ubuntu
- Follow the instructions on the BentoML official README(https://github.com/bentoml/BentoML) to set up the environment.
1.1 Install BentoML (Server host: 10.98.36.123) :
pip install -U bentoml
1.2 Define APIs in a service.py file (Server host: 10.98.36.123) :
from __future__ import annotations
import bentoml
@bentoml.service(
resources={"cpu": "4"}
)
class Summarization:
def __init__(self) -> None:
import torch
from transformers import pipeline
device = "cuda" if torch.cuda.is_available() else "cpu"
self.pipeline = pipeline('summarization', device=device)
@bentoml.api(batchable=True)
def summarize(self, texts: list[str]) -> list[str]:
results = self.pipeline(texts)
return [item['summary_text'] for item in results]
1.3 Run the service code (Server host: 10.98.36.123) :
pip install torch transformers # additional dependencies for local run
bentoml serve