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CVE-2025-54381 — BentoML SSRF Vulnerability in bentoml — CVE Details

CRITICAL

BentoML SSRF Vulnerability in File Upload Processing

Published July 29, 2025Updated September 10, 2026Source: osv

Summary

### Description There's an SSRF in the file upload processing system that allows remote attackers to make arbitrary HTTP requests from the server without authentication. The vulnerability exists in the serialization/deserialization handlers for multipart form data and JSON requests, which automatically download files from user-provided URLs without proper validation of internal network addresses. The framework automatically registers any service endpoint with file-type parameters (`pathlib.Path`, `PIL.Image.Image`) as vulnerable to this attack, making it a framework-wide security issue that affects most real-world ML services handling file uploads. While BentoML implements basic URL scheme validation in the `JSONSerde` path, the `MultipartSerde` path has no validation whatsoever, and neither path restricts access to internal networks, cloud metadata endpoints, or localhost services. The documentation explicitly promotes this URL-based file upload feature, making it an intended but insecure design that exposes all deployed services to SSRF attacks by default. ### Source - Sink Analysis **Source:** User-controlled multipart form field values and JSON request bodies containing URLs **Call Chain - Path 1 (MultipartSerde - No Validation):** 1. HTTP POST request with multipart form data to any BentoML endpoint with file-type input parameters 2. `MultipartSerde.parse_request()` in `src/_bentoml_impl/serde.py:202` processes the request 3. `form = await request.form()` parses multipart data using Starlette 4. For file-type fields: `value = [await self.ensure_file(v) for v in form.getlist(k)]` at line 209 5. `MultipartSerde.ensure_file()` called at lines 186-200 with user-controlled string URL 6. **Sink:** `resp = await client.get(obj)` at line 193 - Direct HTTP request with zero validation **Call Chain - Path 2 (JSONSerde - Weak Validation):** 1. HTTP POST request with JSON body containing URL to endpoint with `IORootModel` + `multipart_fields` 2. `JSONSerde.parse_request()` in `src/_bentoml_impl/serde.py:157` processes the request 3. `body = await request.body()` extracts request body 4. Condition check: `if issubclass(cls, IORootModel) and cls.multipart_fields:` at line 164 5. Weak validation: `if is_http_url(url := body.decode("utf-8", "ignore")):` at line 165 (only checks scheme) 6. **Sink:** `resp = await client.get(url)` at line 168 - HTTP request after insufficient validation ### Proof of Concept Create a BentoML service: ```python from pathlib import Path import bentoml @bentoml.service class ImageProcessor: @bentoml.api def process_image(self, image: Path) -> str: return f"Processed image: {image}" ``` Deploy and exploit: ```bash # Start service (binds to 0.0.0.0:3000 by default) bentoml serve service.py:ImageProcessor # SSRF Attack 1 - Access AWS metadata curl -X POST http://target:3000/process_image \ -F 'image=http://169.254.169.254/latest/meta-data/' # SSRF Attack 2 - Internal service enumeration curl -X POST http://target:3000/process_image \ -F 'image=http://localhost:8080/admin' # SSRF Attack 3 - Internal network scanning curl -X POST http://target:3000/process_image \ -F 'image=http://10.0.0.1:22' ``` Expected result: Server makes HTTP requests to internal/cloud endpoints, potentially returning sensitive data in error messages or logs. ### Impact - Access AWS/GCP/Azure cloud metadata services for credential theft - Enumerate and interact with internal HTTP services and APIs - Bypass firewall restrictions to reach internal network resources - Perform network reconnaissance from the server's perspective - Retrieve sensitive information disclosed in HTTP response data - Potential for internal service exploitation through crafted requests ### Remediation Implement comprehensive URL validation in both serialization paths by adding network restriction checks to prevent access to internal/private network ranges, localhost, and cloud metadata endpoints. The existing `is_http_url()` function should be enhanced to include allowlist validation rather than just scheme checking.

Advisory Timeline

  • First published July 29, 2025 (440 days ago).
  • Last revised September 10, 2026 — 407 days after initial publication.

Remediation

Upgrade to the fixed version using your package manager.

pip
Update bentoml to 1.4.19 or later
pip install "bentoml>=1.4.19"

After upgrading, run your dependency scanner again to confirm the vulnerability is resolved.

Affected Packages (1)

Affects 1 ecosystem: pypi (1).

PackageEcosystemAffectedFixed In
bentoml
pypi
1.4.0, 1.4.1, 1.4.10, 1.4.11 (+15 more)1.4.19

Vulnerability Classification

Common Weakness Enumeration (CWE) identifiers for this vulnerability type.

  • CWE-918
    Server-Side Request Forgery (SSRF)MITRE

CVSS Score Breakdown

What the CVSS (Common Vulnerability Scoring System) 9.9 score means for each attack dimension.

Attack Vector
Network
Attack Complexity
Low
Privileges Required
None
User Interaction
None
Scope
Changed
Confidentiality
High
Integrity
Low
Availability
Low

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:L/A:L

Frequently Asked Questions

What is CVE-2025-54381?
BentoML SSRF Vulnerability in File Upload Processing This vulnerability has been assigned a severity rating of CRITICAL (CVSS score: 9.9/10).
How do I check if my project is affected by CVE-2025-54381?
CVE-2025-54381 affects bentoml. Use GeekWala's free vulnerability scanner to check your dependencies against CVE-2025-54381 and 200,000+ other known vulnerabilities.

Severity & Exploitability

CVSS Score
9.9

Exploitation is straightforward and causes maximum impact. Patch immediately.

Also Known As

GHSA-mrmq-3q62-6cc8
PYSEC-2026-297

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