CVE-2026-107294: CWE-400: Uncontrolled Resource Consumption in pydantic pydantic-ai

### 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 `FileUrl`s 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.