PatchSiren cyber security CVE debrief
CVE-2026-107290 pydantic CVE debrief
Pydantic AI's `web_fetch` tool is vulnerable to a denial-of-service (DoS) attack due to quadratic title extraction. An attacker-controlled page can block the event loop, stalling other agent runs and requests. This issue affects versions 1.77.0 to 1.107.6 and 2.44.0. Defenders should assess exposure and prioritize patching to prevent potential DoS attacks. The vulnerability has a medium severity and is fixed in versions 1.107.6 and 2.44.0. The CVE record and source item provide details on the vulnerability, including affected versions and fixed versions.
- Vendor
- pydantic
- Product
- pydantic-ai
- CVSS
- MEDIUM 6.5
- CISA KEV
- Not listed in stored evidence
- Original CVE published
- 2026-10-08
- Original CVE updated
- 2026-10-08
- Advisory published
- 2026-10-08
- Advisory updated
- 2026-10-08
Who should care
Defenders responsible for Pydantic AI installations, specifically those using versions 1.77.0 to 1.107.6 and 2.44.0, should assess exposure and prioritize patching to prevent potential DoS attacks.
Why it matters
CVE-2026-107290 is a medium-severity vulnerability in Pydantic AI's `web_fetch` tool that can lead to denial-of-service (DoS) attacks. Defenders should prioritize patching vulnerable versions to prevent potential attacks.
- Potential denial-of-service (DoS) attacks against Pydantic AI installations
- Stalling of other agent runs and requests due to blocked event loop
- Verification of inventory and patching of vulnerable versions required
Technical summary
Pydantic AI's `web_fetch` tool is vulnerable to quadratic title extraction, which can cause the event loop to block, stalling other agent runs and requests. This issue affects versions 1.77.0 to 1.107.6 and 2.44.0, and is fixed in versions 1.107.6 and 2.44.0. The vulnerability has a medium severity and can lead to denial-of-service (DoS) attacks. Defenders should prioritize patching vulnerable versions to prevent potential attacks. The CVE record and source item provide details on the vulnerability, including affected versions and fixed versions.
Defensive priority
Defenders should prioritize patching vulnerable versions of Pydantic AI, specifically versions 1.77.0 to 1.107.6 and 2.44.0, to prevent potential DoS attacks.
Recommended defensive actions
- Patch vulnerable versions of Pydantic AI to prevent potential DoS attacks
- Verify inventory of Pydantic AI installations to identify potential exposure
- Monitor for suspicious activity related to `web_fetch` tool usage
- Review compensating controls for exposed systems while remediation is scheduled and verified
- Check relevant monitoring, detection, and logs for exposed assets that need extra review
- Track exceptions, retest remediated assets, and close the item only after evidence is documented
- Confirm whether affected product deployments exist in managed environments and assign an owner for follow-up
Evidence notes
The CVE record and source item provide details on the vulnerability, including affected versions (1.77.0 to 1.107.6 and 2.44.0) and fixed versions (1.107.6 and 2.44.0). However, there is limited information on potential exploitation or victim impact. Defenders should verify inventory and patch vulnerable versions to prevent potential DoS attacks. The vulnerability has a medium severity and can lead to denial-of-service (DoS) attacks. There is no evidence of exploitation in the wild, but defenders should monitor for suspicious activity
Sources and references
Verified primary and authoritative sources
-
CVE-2026-107290 CVE Program record
Publisher, destination, and source semantics verified
URL: https://www.cve.org/CVERecord?id=CVE-2026-107290
CVE Program - Official CVE Program record with source-provided CVE metadata.
-
CVE-2026-107290 NVD vulnerability detail
Publisher, destination, and source semantics verified
URL: https://nvd.nist.gov/vuln/detail/CVE-2026-107290
NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.
Supplemental references
-
Pydantic AI: Event loop blocked by quadratic title extraction in `web_fetch`
Unverified legacy reference
URL: https://raw.githubusercontent.com/CVEProject/cvelistV5/main/cves/2026/107xxx/CVE-2026-107290.json
cve_program_cvelist_v5
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Source reference
Unverified legacy reference
URL: https://github.com/pydantic/pydantic-ai/security/advisories/GHSA-fpf4-vwcp-v4hp
Supplemental source - x_refsource_CONFIRM
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Source reference
Unverified legacy reference
URL: https://github.com/pydantic/pydantic-ai/pull/8397
Supplemental source - x_refsource_MISC
-
Source reference
Unverified legacy reference
URL: https://github.com/pydantic/pydantic-ai/pull/8399
Supplemental source - x_refsource_MISC
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Source reference
Unverified legacy reference
URL: https://github.com/pydantic/pydantic-ai/pull/8418
Supplemental source - x_refsource_MISC
-
Source reference
Unverified legacy reference
URL: https://github.com/pydantic/pydantic-ai/pull/84332
Supplemental source - x_refsource_MISC
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Source reference
Unverified legacy reference
URL: https://github.com/pydantic/pydantic-ai/pull/8434
Supplemental source - x_refsource_MISC
-
Source reference
Unverified legacy reference
URL: https://github.com/pydantic/pydantic-ai/commit/2faa6181d8a17d83bc9516d035c5270db8730fa0
Supplemental source - x_refsource_MISC
Methodology and review provenance
AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.