CVE-2026-107294

Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 1.77.0 until 1.107.2 and 2.24.0, web_fetch_tool, the WebFetch local fallback, and remote FileUrl media downloads buffer the complete HTTP response body before enforcing content-size controls. An attacker-influenced URL can stream an arbitrarily large response that exhausts process memory and crashes the worker; affected media types include ImageUrl, DocumentUrl, VideoUrl, and AudioUrl. SSRF protections remain effective, and the impact is limited to availability. This issue is fixed in versions 1.107.2 and 2.24.0.

Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 1.77.0 until 1.107.2 and 2.24.0, web_fetch_tool, the WebFetch local fallback, and remote FileUrl media downloads buffer the complete HTTP response body before enforcing content-size controls. An attacker-influenced URL can stream an arbitrarily large response that exhausts process memory and crashes the worker; affected media types include ImageUrl, DocumentUrl, VideoUrl, and AudioUrl. SSRF protections remain effective, and the impact is limited to availability. This issue is fixed in versions 1.107.2 and 2.24.0.

Summary

Several remote-content download paths in Pydantic AI buffered the entire HTTP response body into memory before enforcing any size limit. An application that exposes the local web-fetch tool (web_fetch_tool, or the WebFetch capability's local fallback) to untrusted prompts can be driven to fetch an attacker-chosen URL that streams a very large body, exhausting process memory and crashing the worker. The same unbounded buffering applied to FileUrl media downloads (ImageUrl, DocumentUrl, VideoUrl, AudioUrl).

This is an availability issue only. SSRF protections (scheme allowlist, private-IP and cloud-metadata blocking) are unaffected; there is no confidentiality or integrity impact.

Details

The download helpers read the full response body before applying content-size controls, so an existing text-length limit only truncated after the whole body was already in memory, and media downloads had no wire-level cap at all. A single large response could grow process memory without bound .

Who Is Affected

You are affected if your application registers the local web-fetch tool (or relies on the WebFetch capability's local fallback) and exposes the agent to untrusted prompts, or if it downloads large remote FileUrls influenced by untrusted input. Applications that only fetch developer-controlled URLs are not exposed to the model-chosen attack path.

Remediation

Upgrade to 2.24.0 or later (v2) or 1.107.2 or later (v1). Patched versions enforce a default 50 MiB cap on web-fetch and FileUrl downloads while streaming; pass None to the limit to restore the previous unbounded behavior.

Credits

Identified during internal review of media-download hardening.

Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 1.77.0 until 1.107.2 and 2.24.0, web_fetch_tool, the WebFetch local fallback, and remote FileUrl media downloads buffer the complete HTTP response body before enforcing content-size controls. An attacker-influenced URL can stream an arbitrarily large response that exhausts process memory and crashes the worker; affected media types include ImageUrl, DocumentUrl, VideoUrl, and AudioUrl. SSRF protections remain effective, and the impact is limited to availability. This issue is fixed in versions 1.107.2 and 2.24.0.

Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 1.77.0 until 1.107.2 and 2.24.0, web_fetch_tool, the WebFetch local fallback, and remote FileUrl media downloads buffer the complete HTTP response body before enforcing content-size controls. An attacker-influenced URL can stream an arbitrarily large response that exhausts process memory and crashes the worker; affected media types include ImageUrl, DocumentUrl, VideoUrl, and AudioUrl. SSRF protections remain effective, and the impact is limited to availability. This issue is fixed in versions 1.107.2 and 2.24.0.

Summary

Several remote-content download paths in Pydantic AI buffered the entire HTTP response body into memory before enforcing any size limit. An application that exposes the local web-fetch tool (web_fetch_tool, or the WebFetch capability's local fallback) to untrusted prompts can be driven to fetch an attacker-chosen URL that streams a very large body, exhausting process memory and crashing the worker. The same unbounded buffering applied to FileUrl media downloads (ImageUrl, DocumentUrl, VideoUrl, AudioUrl).

This is an availability issue only. SSRF protections (scheme allowlist, private-IP and cloud-metadata blocking) are unaffected; there is no confidentiality or integrity impact.

Details

The download helpers read the full response body before applying content-size controls, so an existing text-length limit only truncated after the whole body was already in memory, and media downloads had no wire-level cap at all. A single large response could grow process memory without bound .

Who Is Affected

You are affected if your application registers the local web-fetch tool (or relies on the WebFetch capability's local fallback) and exposes the agent to untrusted prompts, or if it downloads large remote FileUrls influenced by untrusted input. Applications that only fetch developer-controlled URLs are not exposed to the model-chosen attack path.

Remediation

Upgrade to 2.24.0 or later (v2) or 1.107.2 or later (v1). Patched versions enforce a default 50 MiB cap on web-fetch and FileUrl downloads while streaming; pass None to the limit to restore the previous unbounded behavior.

Credits

Identified during internal review of media-download hardening.

Summary

Several remote-content download paths in Pydantic AI buffered the entire HTTP response body into memory before enforcing any size limit. An application that exposes the local web-fetch tool (web_fetch_tool, or the WebFetch capability's local fallback) to untrusted prompts can be driven to fetch an attacker-chosen URL that streams a very large body, exhausting process memory and crashing the worker. The same unbounded buffering applied to FileUrl media downloads (ImageUrl, DocumentUrl, VideoUrl, AudioUrl).

This is an availability issue only. SSRF protections (scheme allowlist, private-IP and cloud-metadata blocking) are unaffected; there is no confidentiality or integrity impact.

Details

The download helpers read the full response body before applying content-size controls, so an existing text-length limit only truncated after the whole body was already in memory, and media downloads had no wire-level cap at all. A single large response could grow process memory without bound .

Who Is Affected

You are affected if your application registers the local web-fetch tool (or relies on the WebFetch capability's local fallback) and exposes the agent to untrusted prompts, or if it downloads large remote FileUrls influenced by untrusted input. Applications that only fetch developer-controlled URLs are not exposed to the model-chosen attack path.

Remediation

Upgrade to 2.24.0 or later (v2) or 1.107.2 or later (v1). Patched versions enforce a default 50 MiB cap on web-fetch and FileUrl downloads while streaming; pass None to the limit to restore the previous unbounded behavior.

Credits

Identified during internal review of media-download hardening.

Summary

Several remote-content download paths in Pydantic AI buffered the entire HTTP response body into memory before enforcing any size limit. An application that exposes the local web-fetch tool (web_fetch_tool, or the WebFetch capability's local fallback) to untrusted prompts can be driven to fetch an attacker-chosen URL that streams a very large body, exhausting process memory and crashing the worker. The same unbounded buffering applied to FileUrl media downloads (ImageUrl, DocumentUrl, VideoUrl, AudioUrl).

This is an availability issue only. SSRF protections (scheme allowlist, private-IP and cloud-metadata blocking) are unaffected; there is no confidentiality or integrity impact.

Details

The download helpers read the full response body before applying content-size controls, so an existing text-length limit only truncated after the whole body was already in memory, and media downloads had no wire-level cap at all. A single large response could grow process memory without bound .

Who Is Affected

You are affected if your application registers the local web-fetch tool (or relies on the WebFetch capability's local fallback) and exposes the agent to untrusted prompts, or if it downloads large remote FileUrls influenced by untrusted input. Applications that only fetch developer-controlled URLs are not exposed to the model-chosen attack path.

Remediation

Upgrade to 2.24.0 or later (v2) or 1.107.2 or later (v1). Patched versions enforce a default 50 MiB cap on web-fetch and FileUrl downloads while streaming; pass None to the limit to restore the previous unbounded behavior.

Credits

Identified during internal review of media-download hardening.