Sign in Sign up
JA · EN · FR
SecPulse
Categories
CVE-2026-107290 medium CVSS 6.5

Vulnerability in pydantic-ai (CVE-2026-107290)

Summary

Vulnerability in pydantic-ai (CVE-2026-107290). Risk of unauthorized operations or information disclosure. Exploitable via web_fetch_tool. Mitigation: upgrade to 2.44.0 or later.

Original description

The description as published by the source.

Summary

The local web-fetch tool (web_fetch_tool, also used as the WebFetch capability's local fallback) processed responses with several steps whose running time grows quadratically with the size of certain server-controlled inputs, and ran them on the event loop: decoding the body with whichever charset the server declared, extracting the page title with a backtracking regular expression, and converting the HTML to markdown. An application that exposes this tool to untrusted prompts can be steered to fetch an attacker-controlled page of a megabyte or two that blocks the event loop for minutes, stalling every other coroutine in the process — other agent runs, other requests being served — for the duration.

This is an availability issue only. SSRF protections and the download size limit introduced in GHSA-v2xh-2vp8-57h8 are unaffected; that limit bounds how much is downloaded, not how long the response takes to process.

Details

Title extraction used a backtracking pattern over the raw response body, so a body made of repeated unterminated tag openings cost time proportional to the square of its size. The HTML-to-markdown conversion had the same shape in three of its steps: normalizing whitespace, stripping preformatted blocks, and numbering ordered lists all took time proportional to the square of a run of spaces or a list's length. All of it ran on the event loop, and the regex steps hold the interpreter lock even when moved off it, so the whole process p…

Source: GitHub Security Advisories (Global) NVD GitHub Advisory

Auto-generated summary

Assembled by SecPulse from the source data (CVSS, CWE, affected versions) using templates — no AI involved. Check the original description and references below for exact details.

A vulnerability tracked as CVE-2026-107290 has been found in pydantic-ai.
Attackers can target a specific entry point like web_fetch_tool over the network to misuse the product.
Risk of unauthorized operations or information disclosure. CVSS score: 6.5/10.
What to do: upgrade pydantic-ai to 2.44.0 or later.
If unsure, ask your IT team or search "pydantic-ai CVE-2026-107290" on the vendor's site.

CVE-2026-107290 (pydantic-ai) — CWE-1333 / CVSS v3 6.5
Attack vector: remote (network-reachable) / no user interaction
Attack surface: web_fetch_tool / WebFetch / charset / punycode
Patched: 2.44.0 — apply immediately
Plan: 1) Audit SBOM/dependencies, 2) Stage→prod upgrade, 3) Add WAF/proxy monitoring on affected endpoints, 4) Hunt IOCs in logs.
Refs: see the GHSA / vendor advisory / patched release linked on this page.

❓ What is the problem

A vulnerability (CWE-1333) exists in pydantic-ai. Attackers reach the vulnerable code path via web_fetch_tool.

📍 Affected scope

Check the vendor advisory for the affected versions of pydantic-ai. Attack surface: web_fetch_tool / WebFetch / charset / punycode.

🔥 Severity

Severity: Medium (CVSS 6.5/10). Risk of unauthorized operations or information disclosure.

🔧 How to fix

Update to 2.44.0.

🛡️ Workaround

Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.

🔍 Detection

Search webserver/proxy logs for unusual request patterns matching this CVE's known IOCs. Run grep -r 'pydantic-ai' . against your dependency files (package-lock.json, requirements.txt, go.sum) to find affected services.

Response actions

Concrete steps and command examples for SOC/SRE teams to execute in order

  1. 1
    Identify exposure identify 
    grep -r 'pydantic-ai' . | grep -v node_modules

    リポジトリと本番環境の依存ファイル (package-lock.json / requirements.txt / go.sum / Gemfile.lock 等) で pydantic-ai を grep し、稼働しているサービス・バージョンを把握する。

  2. 2
    Apply patch patch 
    Upgrade pydantic-ai to 2.44.0

    ステージング環境で 2.44.0 に上げて回帰テスト → 本番反映。回帰テストはアプリの主要ハッピーパスを含めること。

  3. 3
    Post-deployment verification verify 
    Confirm patched version is live in production

    パッチ適用後、ステージングで PoC または同等の悪用パターンを再現して脆弱性が閉じたことを確認。本番ではアクセスログ・WAF でアラート再発が無いか継続監視。

Affected packages

pip pydantic-ai
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.44.0"}]}]
pip pydantic-ai-slim
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.44.0"}]}]

References

We use cookies for analytics and ad measurement. This setting applies to all Game co., Ltd. sites. Details