Описание
Pydantic AI has Server-Side Request Forgery (SSRF) in URL Download Handling
Summary
A Server-Side Request Forgery (SSRF) vulnerability exists in Pydantic AI's URL download functionality. When applications accept message history from untrusted sources, attackers can include malicious URLs that cause the server to make HTTP requests to internal network resources, potentially accessing internal services or cloud credentials.
This vulnerability only affects applications that accept message history from external users, such as those using:
Agent.to_weborclai webto serve a chat interfaceVercelAIAdapterfor Vercel AI SDK integrationAGUIAdapterorAgent.to_ag_uifor AG-UI protocol integration- Custom APIs that accept message history from user input
Applications that only use hardcoded or developer-controlled URLs are not affected.
Description
The download_item() helper function downloads content from URLs without validating that the target is a public internet address. When user-supplied message history contains URLs, attackers can:
- Access internal services: Request
http://127.0.0.1,localhost, or private IP ranges (10.x.x.x,172.16.x.x,192.168.x.x) - Steal cloud credentials: Access cloud metadata endpoints (AWS IMDSv1 at
169.254.169.254, GCP, Azure, Alibaba Cloud) - Scan internal networks: Enumerate internal hosts and ports
Who Is Affected
You are affected if your application:
-
Uses
Agent.to_weborclai web- The web interface accepts file attachments via the Vercel AI Data Stream Protocol, where users can provide arbitrary URLs through chat messages. -
Uses
VercelAIAdapter- Chat interfaces built with Vercel AI SDK allow users to submit messages containing URLs that are processed server-side. -
Uses
AGUIAdapterorAgent.to_ag_ui- The AG-UI protocol allows users to provide file references with URLs as part of agent interactions. -
Exposes a custom API accepting message history - Any endpoint that accepts message history or
ImageUrl,AudioUrl,VideoUrl,DocumentUrlobjects from user input.
Attack Scenario
Via chat interface, an attacker submits a message with a file attachment pointing to an internal resource:
Affected Model Integrations
Multiple model integrations download URL content in certain conditions:
| Provider | Downloaded Types |
|---|---|
OpenAIChatModel | AudioUrl, DocumentUrl |
AnthropicModel | DocumentUrl (text/plain) |
GoogleModel (GLA) | All URL types (except YouTube and Files API URLs) |
XaiModel | DocumentUrl |
BedrockConverseModel | ImageUrl, DocumentUrl, VideoUrl (non-S3 URLs) |
OpenRouterModel | AudioUrl |
Remediation
Upgrade to Patched Version
Upgrade to the patched version or later. The fix adds comprehensive SSRF protection:
- Blocks private/internal IP addresses by default
- Always blocks cloud metadata endpoints (even with
allow-local) - Only allows
http://andhttps://protocols - Resolves hostnames before requests to prevent DNS rebinding
- Validates each redirect target
New force_download='allow-local' Option
If an application legitimately needs to access local/private network resources (e.g., in a fully trusted internal environment), it can explicitly opt in:
Important: Cloud metadata endpoints (169.254.169.254, fd00:ec2::254, 100.100.100.200) are always blocked, even with allow-local.
Workaround for Older Versions
If a project cannot upgrade immediately, use a history processor to filter out URLs targeting local/private addresses:
Technical Details of the Fix
The fix introduces a new _ssrf.py module with comprehensive protection:
- Protocol validation: Only
http://andhttps://allowed - DNS resolution before request: Prevents DNS rebinding attacks
- Private IP blocking (by default):
127.0.0.0/8,::1/128(loopback)10.0.0.0/8,172.16.0.0/12,192.168.0.0/16(private)169.254.0.0/16,fe80::/10(link-local)100.64.0.0/10(CGNAT)fc00::/7(unique local)2002::/16(6to4, can embed private IPv4)
- Cloud metadata always blocked:
169.254.169.254,fd00:ec2::254,100.100.100.200 - Safe redirect handling: Each redirect validated before following (max 10)
Пакеты
pydantic-ai
>= 0.0.26, < 1.56.0
1.56.0
pydantic-ai-slim
>= 0.0.26, < 1.56.0
1.56.0