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Full vulnerability report · 2026
CVE-2026-107294High confidence

Pydantic AI: Unbounded memory use when downloading remote content via web_fetch or FileUrl

pydantic · pydantic-ai

Official source article: GitHub GHSA-V2XH-2VP8-57H8 ↗. Check the applicable product and release in the original source.

6.5MediumCVSS 3.1
Recommended action
Scheduled

Medium technical severity with no CISA KEV confirmation; remediate through the normal risk-based patch cycle unless local exposure raises the priority.

Fix not verified
R
Operational reassessment

Published severity in operational context

Open reassessment dashboard →
Published severityMediumOperational priority:Medium, unchanged from published severity.unchanged

Evidence used

  • No CISA KEV confirmation is currently recorded.

Compensating controls

  • Restrict the affected network interface to trusted sources where business-safe.
  • Monitor vendor guidance and exploitation sources for a material change.

Verification

  1. Confirm that the asset runs pydantic pydantic-ai and falls inside the recorded affected range.
  2. Recheck the vendor advisory before scheduling a change because no verified fixed version is currently retained.
  3. Validate exposure, authentication requirements and compensating controls in the actual environment.
  4. Reopen this reassessment when CVSS, KEV, EPSS, exploit evidence or remediation changes.
Mitigation target: As exposure requiresRemediation target: Within 365 days

This automated reassessment organises public evidence. It does not know asset exposure, business impact or control effectiveness and does not replace CVSS or a human risk decision.

Open-source package ranges8 source-attributed ranges

These OSV and GitHub advisory ranges apply only to the named package and ecosystem. A listed fixed version is not a universal product patch or proof that an update is installed.

Ecosystem and packageAffected rangeFirst fixed versionEvidence
PyPIpydantic-aiECOSYSTEM: introduced 1.77.0; fixed 1.107.21.107.2OSV record ↗aggregator derived · 8 Oct 2026
PyPIpydantic-aiECOSYSTEM: introduced 2.0.0b1; fixed 2.24.02.24.0OSV record ↗aggregator derived · 8 Oct 2026
PyPIpydantic-ai-slimECOSYSTEM: introduced 1.77.0; fixed 1.107.21.107.2OSV record ↗aggregator derived · 8 Oct 2026
PyPIpydantic-ai-slimECOSYSTEM: introduced 2.0.0b1; fixed 2.24.02.24.0OSV record ↗aggregator derived · 8 Oct 2026
pippydantic-ai>= 1.77.0, < 1.107.21.107.2GitHub advisory ↗upstream repository advisory · 8 Oct 2026
pippydantic-ai>= 2.0.0b1, <= 2.23.02.24.0GitHub advisory ↗upstream repository advisory · 8 Oct 2026
pippydantic-ai-slim>= 1.77.0, < 1.107.21.107.2GitHub advisory ↗upstream repository advisory · 8 Oct 2026
pippydantic-ai-slim>= 2.0.0b1, <= 2.23.02.24.0GitHub advisory ↗upstream repository advisory · 8 Oct 2026
Direct vendor intelligence

Authoritative vendor CSAF and VEX advisories

Structured product status and remediation from the issuing vendor. Product-state explanations are always visible; large lists can be searched or downloaded.

1 current
CVE-2026-107294 · CSAF 2.0 · revision 3 · finalRed Hat Product Securitypydantic-ai: pydantic-ai: Denial of Service via unbounded HTTP response buffering
5 known affected

The vendor explicitly identifies these products as affected by this CVE.

  • lightspeed-core/lightspeed-stack-rhel9 as a component of Lightspeed Core
  • rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
  • rhelai3/bootc-gaudi-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
  • rhelai3/bootc-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
  • rhelai3/disk-image-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
Summary
A flaw was found in Pydantic AI. When fetching remote web content or media files, the framework buffers the entire response in memory before enforcing content-size limits. A remote attacker can exploit this issue by supplying a link that streams an excessively large response, exhausting memory and crashing the application worker, resulting in a Denial of Service (DoS).
Remediation
Fix deferred
Optional official sources

National CERT insights
?CERT means Computer Emergency Response Team; CSIRT is the closely related term Computer Security Incident Response Team.

Choose official national sources for this report. Each advisory shows its original language. Your selection is remembered on this device and included in shared links.

Official European source

ENISA European Vulnerability Database

Official EUVD identifiers, advisory evidence and known-exploited context. Missing fields are not treated as evidence of low risk.

1 current
ENISA EUVD identifier

EUVD-2026-95104

No EUVD known-exploited evidence

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.

EUVD state
Present in the current official mapping
Known exploitation
Not present in the current ENISA EUVD known-exploited dataset. This is not proof of no exploitation.
ENISA score
6.5 · CVSS 3.1
Advisory evidence
No linked advisory details stored yet
Recommended actionScheduled

Medium technical severity with no CISA KEV confirmation; remediate through the normal risk-based patch cycle unless local exposure raises the priority.

Fix not verified
01

What, why and how

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.

What

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.

Why

The product does not properly control the allocation and maintenance of a limited resource.

How

An attacker operating through a network path may attempt exploitation with low privileges. If successful, the issue may disrupt the affected service.

What

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.

Why

The product does not properly control the allocation and maintenance of a limited resource.

How

An attacker operating through a network path may attempt exploitation with low privileges. If successful, the issue may disrupt the affected service.

02

Exploit reality and attack path

CVSS severity, EPSS forecast probability, public exploit material and CISA-confirmed exploitation are separate signals.

Observed exploitation
?Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.
No confirmed evidence

No CISA KEV match was present at the last successful refresh. This means no confirmation from that source, not proof of no exploitation.

Public PoC / exploit material
?Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.
None recorded

No exploit-tagged reference or CISA SSVC proof-of-concept state is currently recorded. Research may still exist outside the structured feeds.

Likely attack path
a network path → Uncontrolled Resource Consumption → disrupt the affected service
Attack surface
Network
Privileges required
Low: a basic authenticated account is required
User interaction
None
Attack complexity
Low: no specialised conditions are recorded
Security boundary
Unchanged: impact remains within the vulnerable component's security authority
Weakness
?CWE means Common Weakness Enumeration: a standard category for the underlying weakness.
CWE-400 ↗

CWE-400: Uncontrolled Resource Consumption. The product does not properly control the allocation and maintenance of a limited resource.

CVSS vector
?CVSS means Common Vulnerability Scoring System. The vector records the metric values used to calculate technical severity.
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Common Vulnerability Scoring System 3.1: the compact vector below is decoded into plain language.

AVNetworkAttack vector: The vulnerable component can be reached over a network.ACLowAttack complexity: No specialised conditions are required beyond attacker-controlled input.PRLowPrivileges required: The attacker needs basic user-level privileges.UINoneUser interaction: No action by another user is required.SUnchangedScope: The security impact remains within the vulnerable component's authority.CNoneConfidentiality impact: No direct loss is represented by this metric.INoneIntegrity impact: No direct loss is represented by this metric.AHighAvailability impact: A successful attack can cause a major loss.
Post-exploitation / living off the land
No specific living-off-the-land technique is confirmed in the structured sources. Monitor normal administration tools for activity inconsistent with the affected service's baseline.
NetworkDenial of serviceCWE-400
A

Official authority intelligence

Only matched European and national findings are included. Language selectors and unavailable sources are omitted.

ENISA EUVD · EUVD-2026-95104Official EUVD mapping

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.

Official EUVD record ↗
03

Patch and workaround

Operational remediation based on structured source evidence.

Status
?Patch availability is based on structured fixed-version fields and authoritative update references. If no fix is verified, check the vendor advisory before making a change.
Fix not verified
Affected
  • lightspeed-core/lightspeed-stack-rhel9 as a component of Lightspeed Core
  • rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
  • rhelai3/bootc-gaudi-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
  • rhelai3/bootc-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
  • rhelai3/disk-image-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
Fixed
No fixed version is explicitly recorded in the structured CVE data.
Action
No verified patch reference is present in the current structured sources. Check the vendor advisory before making a change.
Workaround
No verified workaround is recorded. If business-safe, reduce exposure to the affected interface and allow only trusted sources until authoritative guidance is available.
04

Evidence and provenance

Published 8 Oct 2026 · Last source change 8 Oct 2026, 16:59 UTC · CWE-400 · Uncontrolled Resource Consumption

CVE recordCVE.org · 5.2
CVSS sourceCNA
EPSS source
?The date BlackTree first stored a score for this CVE from the daily FIRST EPSS feed.
Unavailable
European sourceENISA EUVD · EUVD-2026-95104
Product sourceVendor CSAF · Red Hat Product Security
Remediation sourceVendor CSAF · Red Hat Product Security
CWE sourceCNA
NVD statusNVD awaiting enrichment

Core structured fields are present and their contributing authorities are shown above.

Material change intelligence

What changed after publication

View recent updates ↗
  1. ENISA EUVD mappingEUVD-2026-95104 was added to the official ENISA EUVD mapping for this CVE.
    Before
    not recorded
    After
    {"euvdId":"EUVD-2026-95104"}
    ENISA EUVD ↗
  2. Catalogue recordCVE added to the BlackTree catalogue.
    CNA ↗
Material fields only · duplicate refreshes suppressed · history retained for the configured operational retention period
CVE published
ENISA EUVD · EUVD-2026-95104↗Vendor CSAF · Red Hat Product Security↗CVE authority or vendor reference · GitHub GHSA-V2XH-2VP8-57H8↗Official CVE record (CNA and ADP data)↗NVD record↗
Technical terms and abbreviations used in this report
CVE
Common Vulnerabilities and Exposures: the public identifier for one disclosed vulnerability.
CVSS
Common Vulnerability Scoring System: a technical severity framework; it is not patching priority by itself.
EPSS
Exploit Prediction Scoring System: FIRST's estimate of the probability that exploitation activity will be observed in the next 30 days; it is a forecast, not confirmation.
CWE
Common Weakness Enumeration: the standard category describing the underlying software or hardware weakness.
CNA
CVE Numbering Authority: an organisation authorised to assign and publish CVE records.
CISA ADP
Cybersecurity and Infrastructure Security Agency Authorized Data Publisher: structured enrichment added to a CVE record.
NVD
National Vulnerability Database: NIST's enrichment service for CVE records.
CERT / CSIRT
A computer security incident response team that publishes warnings or coordinates incident response.
PoC
Proof of concept: public material that demonstrates or helps reproduce exploitation.
CSAF
Common Security Advisory Framework: a machine-readable format for security advisories.
LoTL
Living off the land: abuse of legitimate tools or system functions during an attack.
Free version - for non-commercial use only.CVE-2026-107294 · cve.blacktree.nl