vulnerability / NVI-00012039 / Revision 4
Pydantic AI: Event loop blocked by quadratic title extraction in `web_fetch`
GitHub lists this reviewed advisory for pydantic-ai, pydantic-ai, pydantic-ai-slim, pydantic-ai-slim. Published version ranges and source prerequisites are shown below; this is not an inspection of a visitor’s application.
This report has not inspected your inventory, configuration, deployed build, reachability or evidence. A catalog listing and a severity score do not establish exposure or compromise.
01 / Meaning
Why it matters
Published affected context helps an owner decide what evidence to gather. This report has not examined your application.
6.5 medium
GitHub source severity; exploitability and local consequence require separate evidence.
As of · GitHub Advisory Database
6.5 MEDIUM (3.1)
security-advisories@github.com severity; no combined Null risk score.
0.512%
FIRST EPSS model v2026.06.15; exploitation probability over 30 days, percentile 0.43814. Missing scores are unknown.
As of · FIRST EPSS
02 / Applicability
The affected context
Affected versions, configuration prerequisites and known exclusions are public. Confirm each one against the deployed service.
pydantic-ai
source listed>= 1.77.0, < 1.107.6
### 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
pydantic-ai
source listed>= 2.0.0b1, < 2.44.0
### 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
pydantic-ai-slim
source listed>= 1.77.0, < 1.107.6
### 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
pydantic-ai-slim
source listed>= 2.0.0b1, < 2.44.0
### 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
03 / Response
What to do next
- investigate
Identify the exact component and deployed version, examine the linked publisher’s conditions, and retain evidence of any mitigation.
Confirm current vendor support, compatibility and deployment evidence. This report has not tested a fix in your system. FIRST EPSS
A fixed release is not deployment evidence.
Check current vendor support and compatibility. After making a change, verify the deployed build and relevant runtime conditions. Keep the evidence, owner and time. An updated lockfile alone does not prove what is running.
04 / Limits
What this report cannot establish
- Customer inventory, deployment, reachability and exploitation have not been inspected.
- NVD lastModified does not establish freshness of every associated CPE record.
05 / Provenance
Sources you can inspect
Each assertion retains its source. Mirrored records may repeat one underlying publisher; additional links are not independent corroboration.
- GHSA-fpf4-vwcp-v4hp ↗
GitHub Advisory Database · vendor advisory
Observed . GitHub Advisory Database; CC-BY-4.0. Each advisory links its original attribution. Null normalizes fields.
- CVE-2026-107290 ↗
NIST National Vulnerability Database · official catalog
Observed . This product uses data from the NVD API but is not endorsed or certified by the NVD.
- CVE-2026-107290 ↗
FIRST EPSS · official catalog
Observed . FIRST EPSS; probability of exploitation in the next 30 days, not local compromise. Dataset date/model retained; FIRST services terms apply.
Public revision history
Only published revisions appear here. Routine fetches do not create a material-change event.
- Revision 4 ·
Dated EPSS estimate updated; this is not a new disclosure or proof of exploitation.
- Revision 3 ·
Source facts changed; compare the preserved prior revision.
- Revision 2 ·
Dated EPSS estimate updated; this is not a new disclosure or proof of exploitation.
- Revision 1 ·
First indexed by Null; source disclosure date is shown separately.