GitHub Advisoryadvisory · PyPI
GHSA-vmxc-h2x2-jmf3 Pydantic AI: SSRF cloud-metadata blocklist bypass via IPv6 zone identifiers
MEDIUM
Official page ↗
- Aliases
- CVE-2026-107289
- Ecosystem
- PyPI
- Packages
- pydantic-ai, pydantic-ai-slim
- Severity
- Moderate
- CVSS vector
- CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:N/A:N
- Weaknesses
- CWE-1289, CWE-918
- Reviewed
- 2026-10-08
Affected packages
• PyPI pydantic-ai: >= 1.56.0, < 1.107.6 → fixed in 1.107.6
• PyPI pydantic-ai: >= 2.0.0b1, < 2.44.0 → fixed in 2.44.0
• PyPI pydantic-ai-slim: >= 1.56.0, < 1.107.6 → fixed in 1.107.6
• PyPI pydantic-ai-slim: >= 2.0.0b1, < 2.44.0 → fixed in 2.44.0
Description
Summary
When an application using Pydantic AI opts a URL into local network access — either a `FileUrl` with `force_download='allow-local'`, or `web_fetch_tool(allow_local_urls=True)` — the cloud-metadata blocklist could be bypassed by appending an IPv6 zone identifier to a metadata address (for example `fd00:ec2::254%251`). The host ignores the zone identifier on a destination that is not link-local and delivers the request to the metadata endpoint anyway, exposing cloud IAM short-term credentials.
This is an incomplete fix of GHSA-cqp8-fcvh-x7r3 / CVE-2026-46678 and GHSA-cg7w-rg45-pc59 / CVE-2026-48782, themselves follow-ups to CVE-2026-25580. The parent advisory's remediation guaranteed that cloud metadata endpoints are always blocked, even with local access allowed. That guarantee did not hold for zone-scoped spellings of the IPv6 metadata endpoints.
Details
The cloud-metadata guard compared IPv6 addresses against its blocklist by set membership. Python includes the zone identifier in `IPv6Address` equality and hashing, so a zone-scoped spelling of a blocked address did not match, while the network stack ignores the zone identifier for a destination that is not link-local. The private-range checks, and the IPv4 and transition-form metadata checks, were already unaffected, because they compare by network containment and by packed bytes respectively.
Only the IPv6 cloud metadata endpoints were reachable this way, so the issue requires an IPv6-enabled environment — for example AWS EC2 or EKS with IPv6, GCP IPv6-only instances, or Scaleway.
Who Is Affected
You are affected only if your application opts a URL that is, or could be, influenced by untrusted input into local network access, through either:
• a `FileUrl` (`ImageUrl`, `AudioUrl`, `VideoUrl`, `DocumentUrl`) with `force_download='allow-local'`; or
• `web_fetch_tool(allow_local_urls=True)`, where the model chooses the URL.
Both are off by default.
You are not affected through the `FileUrl` path if you use any of the bundled integrations to ingest user input, because they do not propagate `force_download` from external data:
• `Agent.to_web` / `clai web`
• `VercelAIAdapter`
• `AGUIAdapter` / `Agent.to_ag_ui`
`web_fetch_tool` is configured by your own application, so a client cannot turn on `allow_local_urls`.
Applications that only download from developer-controlled URLs are not affected.
Remediation
Upgrade to a patched version. The cloud-metadata and private-IP checks now drop an IPv6 zone identifier before evaluating the address, so every blocklist comparison is made on the address itself. A zone identifier is still carried on the connection, so legitimate link-local fetches under local network access continue to work.
Workaround for Unpatched Versions
Avoid opting into local network access — `force_download='allow-local'` or `web_fetch_tool(allow_local_urls=True)` — on any URL that could be influenced by untrusted input. If you must, reject URL hosts containing `%` before constructing the `FileUrl` or configuring the tool.
Credits
Reported by @euriconicacio.
Related
Alias · CVE (1)
- CVE-2026-107289 Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. vulnerability
References
- https://github.com/pydantic/pydantic-ai/security/advisories/GHSA-vmxc-h2x2-jmf3 web
- https://github.com/pydantic/pydantic-ai/pull/8401 web
- https://github.com/pydantic/pydantic-ai/pull/8402 web
- https://github.com/pydantic/pydantic-ai/commit/02157e1b87bd45d3f2e111ce07afdf89f9fb0e5b web
- https://github.com/pydantic/pydantic-ai/commit/4da70591460f51a8c4f128eaeef70a33340dbd55 web
- https://github.com/pydantic/pydantic-ai package
- https://github.com/pydantic/pydantic-ai/releases/tag/v1.107.6 web
- https://github.com/pydantic/pydantic-ai/releases/tag/v2.44.0 web