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🐍 PyPI

GHSA-2jrp-274c-jhv3

HIGH

Pydantic AI has Server-Side Request Forgery (SSRF) in URL Download Handling

Also known asCVE-2026-25580
Published
Feb 6, 2026
Updated
Feb 6, 2026
Affected
2 pkgs
Patched
2 / 2
Exploits
None indexed

EPSS Exploitation Probability

via FIRST.org ↗
0.5%probability of exploitation in next 30 days
Lower Risk37th percentile+0.45%
0.00%0.32%0.64%0.96%0.0%0.0%0.0%0.0%0.5%Mar 26May 26Jun 26

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

2 pkgs affected
🐍pydantic-ai🐍pydantic-ai-slim

Real-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 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_web or clai web to serve a chat interface
  • VercelAIAdapter for Vercel AI SDK integration
  • AGUIAdapter or Agent.to_ag_ui for 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:

  1. 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)
  2. Steal cloud credentials: Access cloud metadata endpoints (AWS IMDSv1 at 169.254.169.254, GCP, Azure, Alibaba Cloud)
  3. Scan internal networks: Enumerate internal hosts and ports

Who Is Affected

You are affected if your application:

  1. Uses Agent.to_web or clai web - The web interface accepts file attachments via the Vercel AI Data Stream Protocol, where users can provide arbitrary URLs through chat messages.

  2. Uses VercelAIAdapter - Chat interfaces built with Vercel AI SDK allow users to submit messages containing URLs that are processed server-side.

  3. Uses AGUIAdapter or Agent.to_ag_ui - The AG-UI protocol allows users to provide file references with URLs as part of agent interactions.

  4. Exposes a custom API accepting message history - Any endpoint that accepts message history or ImageUrl, AudioUrl, VideoUrl, DocumentUrl objects from user input.

Attack Scenario

Via chat interface, an attacker submits a message with a file attachment pointing to an internal resource:

{
  "role": "user",
  "parts": [
    {"type": "file", "mediaType": "image/png", "url": "http://169.254.169.254/latest/meta-data/iam/security-credentials/"}
  ]
}

Affected Model Integrations

Multiple model integrations download URL content in certain conditions:

ProviderDownloaded Types
OpenAIChatModelAudioUrl, DocumentUrl
AnthropicModelDocumentUrl (text/plain)
GoogleModel (GLA)All URL types (except YouTube and Files API URLs)
XaiModelDocumentUrl
BedrockConverseModelImageUrl, DocumentUrl, VideoUrl (non-S3 URLs)
OpenRouterModelAudioUrl

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:// and https:// 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:

from pydantic_ai import ImageUrl

# Default behavior: private IPs are blocked
ImageUrl(url="http://internal-service/image.png")  # Raises ValueError

# Opt-in to allow local access (use with caution)
ImageUrl(url="http://internal-service/image.png", force_download='allow-local')

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:

import ipaddress
import socket
from urllib.parse import urlparse

from pydantic_ai import Agent, ModelMessage, ModelRequest
from pydantic_ai.messages import AudioUrl, DocumentUrl, ImageUrl, VideoUrl

def is_private_url(url: str) -> bool:
    """Check if a URL targets a private/internal IP address."""
    try:
        parsed = urlparse(url)
        hostname = parsed.hostname
        if not hostname:
            return True  # Invalid URL, block it

        # Resolve hostname to IP
        ip_str = socket.gethostbyname(hostname)
        ip = ipaddress.ip_address(ip_str)

        # Block private, loopback, and link-local addresses
        return ip.is_private or ip.is_loopback or ip.is_link_local
    except (socket.gaierror, ValueError):
        return True  # DNS resolution failed, block it

def filter_private_urls(messages: list[ModelMessage]) -> list[ModelMessage]:
    """Remove URL parts that target private/internal addresses."""
    url_types = (ImageUrl, AudioUrl, VideoUrl, DocumentUrl)
    filtered = []
    for msg in messages:
        if isinstance(msg, ModelRequest):
            safe_parts = [
                part for part in msg.parts
                if not (isinstance(part, url_types) and is_private_url(part.url))
            ]
            if safe_parts:
                filtered.append(ModelRequest(parts=safe_parts))
        else:
            filtered.append(msg)
    return filtered

# Apply the filter to your agent
agent = Agent('openai:gpt-5', history_processors=[filter_private_urls])

Technical Details of the Fix

The fix introduces a new _ssrf.py module with comprehensive protection:

  1. Protocol validation: Only http:// and https:// allowed
  2. DNS resolution before request: Prevents DNS rebinding attacks
  3. 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)
  4. Cloud metadata always blocked: 169.254.169.254, fd00:ec2::254, 100.100.100.200
  5. Safe redirect handling: Each redirect validated before following (max 10)

Affected Packages

2 total 2 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIpydantic-ai0.0.26&&< 1.56.01.56.0
🐍PyPIpydantic-ai-slim0.0.26&&< 1.56.01.56.0

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for pydantic-ai. 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.

  2. Fix

    Update pydantic-ai to 1.56.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-2jrp-274c-jhv3 is resolved across your whole dependency graph.

  3. 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.

  4. How O3 protects you

    O3 pinpoints whether GHSA-2jrp-274c-jhv3 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-2jrp-274c-jhv3. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

## 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_web`** or **`clai web`** to serve a chat interface - **`VercelAIAdapter`** for Vercel AI SDK integration - **`AG
O3 Security · Impact-Aware SCA

Is GHSA-2jrp-274c-jhv3 in your dependencies?

O3 detects GHSA-2jrp-274c-jhv3 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.

GHSA-2jrp-274c-jhv3: pydantic-ai Server-Side Request Forgery (H… | O3 Security