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CVE-2026-25580

Pydantic AI Affected by Server-Side Request Forgery (SSRF) in URL Download Handling

8.6 HighFix available

Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 0.0.26 to before 1.56.0, aServer-Side Request Forgery (SSRF) vulnerability exists in Pydantic AI's URL download functionality. When applications accept message history from untrusted sources, attackers can include malicious URLs that cause the server to make HTTP requests to internal network resources, potentially accessing internal services or cloud credentials. This vulnerability only affects applications that accept message history from external users. This vulnerability is fixed in 1.56.0.

Attack profile

How easy it is to exploit

Attack vector
Network
Complexity
Low
Privileges needed
None
User interaction
None

What an attacker can affect

Confidentiality
High
Integrity
None
Availability
None

Exploit likelihood

0.65%Up 0.6 points since Feb 7, 2026
90%50%10%1%

What each source reports

CVE List Score used 8.6

Pydantic AI Affected by Server-Side Request Forgery (SSRF) in URL Download Handling

Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 0.0.26 to before 1.56.0, aServer-Side Request Forgery (SSRF) vulnerability exists in Pydantic AI's URL download functionality. When applications accept message history from untrusted sources, attackers can include malicious URLs that cause the server to make HTTP requests to internal network resources, potentially accessing internal services or cloud credentials. This vulnerability only affects applications that accept message history from external users. This vulnerability is fixed in 1.56.0.

Record
CVE-2026-25580
CVSS 3.1
8.6 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
Weakness
CWE-918, CWE-918
Updated
2026-11-02
EUVDEUVD-2026-5574 8.6

Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 0.0.26 to before 1.56.0, aServer-Side Request Forgery (SSRF) vulnerability exists in Pydantic AI's URL download functionality. When applications accept message history from untrusted sources, attackers can include malicious URLs that cause the server to make HTTP requests to internal network resources, potentially accessing internal services or cloud credentials. This vulnerability only affects applications that accept message history from external users. This vulnerability is fixed in 1.56.0.

Record
EUVD-2026-5574
CVSS 3.1
8.6 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
Updated
2026-11-02
GitHub AdvisoriesGHSA-2jrp-274c-jhv3 8.6

Pydantic AI has Server-Side Request Forgery (SSRF) in URL Download Handling

Summary

A Server-Side Request Forgery (SSRF) vulnerability exists in Pydantic AI's URL download functionality. When applications accept message history from untrusted sources, attackers can include malicious URLs that cause the server to make HTTP requests to internal network resources, potentially accessing internal services or cloud credentials.

This vulnerability only affects applications that accept message history from external users, such as those using:

  • Agent.to_web or clai web to serve a chat interface
  • VercelAIAdapter for Vercel AI SDK integration
  • AGUIAdapter or Agent.to_ag_ui for AG-UI protocol integration
  • Custom APIs that accept message history from user input

Applications that only use hardcoded or developer-controlled URLs are not affected.

Description

The download_item() helper function downloads content from URLs without validating that the target is a public internet address. When user-supplied message history contains URLs, attackers can:

  1. Access internal services: Request http://127.0.0.1, localhost, or private IP ranges (10.x.x.x, 172.16.x.x, 192.168.x.x)
  2. Steal cloud credentials: Access cloud metadata endpoints (AWS IMDSv1 at 169.254.169.254, GCP, Azure, Alibaba Cloud)
  3. Scan internal networks: Enumerate internal hosts and ports

Who Is Affected

You are affected if your application:

  1. Uses Agent.to_web or clai web - The web interface accepts file attachments via the Vercel AI Data Stream Protocol, where users can provide arbitrary URLs through chat messages.

  2. Uses VercelAIAdapter - Chat interfaces built with Vercel AI SDK allow users to submit messages containing URLs that are processed server-side.

  3. Uses AGUIAdapter or Agent.to_ag_ui - The AG-UI protocol allows users to provide file references with URLs as part of agent interactions.

  4. Exposes a custom API accepting message history - Any endpoint that accepts message history or ImageUrl, AudioUrl, VideoUrl, DocumentUrl objects from user input.

Attack Scenario

Via chat interface, an attacker submits a message with a file attachment pointing to an internal resource:

{
  "role": "user",
  "parts": [
    {"type": "file", "mediaType": "image/png", "url": "http://169.254.169.254/latest/meta-data/iam/security-credentials/"}
  ]
}

Affected Model Integrations

Multiple model integrations download URL content in certain conditions:

| Provider | Downloaded Types | |----------|------------------| | OpenAIChatModel | AudioUrl, DocumentUrl | | AnthropicModel | DocumentUrl (text/plain) | | GoogleModel (GLA) | All URL types (except YouTube and Files API URLs) | | XaiModel | DocumentUrl | | BedrockConverseModel | ImageUrl, DocumentUrl, VideoUrl (non-S3 URLs) | | OpenRouterModel | AudioUrl |

Remediation

Upgrade to Patched Version

Upgrade to the patched version or later. The fix adds comprehensive SSRF protection:

  • Blocks private/internal IP addresses by default
  • Always blocks cloud metadata endpoints (even with allow-local)
  • Only allows http:// and https:// protocols
  • Resolves hostnames before requests to prevent DNS rebinding
  • Validates each redirect target

New force_download='allow-local' Option

If an application legitimately needs to access local/private network resources (e.g., in a fully trusted internal environment), it can explicitly opt in:

from pydantic_ai import ImageUrl

# Default behavior: private IPs are blocked
ImageUrl(url="http://internal-service/image.png")  # Raises ValueError

# Opt-in to allow local access (use with caution)
ImageUrl(url="http://internal-service/image.png", force_download='allow-local')

Important: Cloud metadata endpoints (169.254.169.254, fd00:ec2::254, 100.100.100.200) are always blocked, even with allow-local.

Workaround for Older Versions

If a project cannot upgrade…

Record
GHSA-2jrp-274c-jhv3
CVSS 3.1
8.6 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
Weakness
CWE-918
Updated
2026-11-02
NVD 8.6

Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 0.0.26 to before 1.56.0, aServer-Side Request Forgery (SSRF) vulnerability exists in Pydantic AI's URL download functionality. When applications accept message history from untrusted sources, attackers can include malicious URLs that cause the server to make HTTP requests to internal network resources, potentially accessing internal services or cloud credentials. This vulnerability only affects applications that accept message history from external users. This vulnerability is fixed in 1.56.0.

Record
CVE-2026-25580
CVSS 3.1
8.6 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
Weakness
CWE-918
Updated
2026-11-02
OSV 8.6

Pydantic AI Affected by Server-Side Request Forgery (SSRF) in URL Download Handling

Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 0.0.26 to before 1.56.0, aServer-Side Request Forgery (SSRF) vulnerability exists in Pydantic AI's URL download functionality. When applications accept message history from untrusted sources, attackers can include malicious URLs that cause the server to make HTTP requests to internal network resources, potentially accessing internal services or cloud credentials. This vulnerability only affects applications that accept message history from external users. This vulnerability is fixed in 1.56.0.

Record
CVE-2026-25580
CVSS 3.1
8.6 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
Weakness
CWE-918
Updated
2026-11-02
OSVGHSA-2jrp-274c-jhv3 8.6

Pydantic AI has Server-Side Request Forgery (SSRF) in URL Download Handling

Summary

A Server-Side Request Forgery (SSRF) vulnerability exists in Pydantic AI's URL download functionality. When applications accept message history from untrusted sources, attackers can include malicious URLs that cause the server to make HTTP requests to internal network resources, potentially accessing internal services or cloud credentials.

This vulnerability only affects applications that accept message history from external users, such as those using:

  • Agent.to_web or clai web to serve a chat interface
  • VercelAIAdapter for Vercel AI SDK integration
  • AGUIAdapter or Agent.to_ag_ui for AG-UI protocol integration
  • Custom APIs that accept message history from user input

Applications that only use hardcoded or developer-controlled URLs are not affected.

Description

The download_item() helper function downloads content from URLs without validating that the target is a public internet address. When user-supplied message history contains URLs, attackers can:

  1. Access internal services: Request http://127.0.0.1, localhost, or private IP ranges (10.x.x.x, 172.16.x.x, 192.168.x.x)
  2. Steal cloud credentials: Access cloud metadata endpoints (AWS IMDSv1 at 169.254.169.254, GCP, Azure, Alibaba Cloud)
  3. Scan internal networks: Enumerate internal hosts and ports

Who Is Affected

You are affected if your application:

  1. Uses Agent.to_web or clai web - The web interface accepts file attachments via the Vercel AI Data Stream Protocol, where users can provide arbitrary URLs through chat messages.

  2. Uses VercelAIAdapter - Chat interfaces built with Vercel AI SDK allow users to submit messages containing URLs that are processed server-side.

  3. Uses AGUIAdapter or Agent.to_ag_ui - The AG-UI protocol allows users to provide file references with URLs as part of agent interactions.

  4. Exposes a custom API accepting message history - Any endpoint that accepts message history or ImageUrl, AudioUrl, VideoUrl, DocumentUrl objects from user input.

Attack Scenario

Via chat interface, an attacker submits a message with a file attachment pointing to an internal resource:

{
  "role": "user",
  "parts": [
    {"type": "file", "mediaType": "image/png", "url": "http://169.254.169.254/latest/meta-data/iam/security-credentials/"}
  ]
}

Affected Model Integrations

Multiple model integrations download URL content in certain conditions:

| Provider | Downloaded Types | |----------|------------------| | OpenAIChatModel | AudioUrl, DocumentUrl | | AnthropicModel | DocumentUrl (text/plain) | | GoogleModel (GLA) | All URL types (except YouTube and Files API URLs) | | XaiModel | DocumentUrl | | BedrockConverseModel | ImageUrl, DocumentUrl, VideoUrl (non-S3 URLs) | | OpenRouterModel | AudioUrl |

Remediation

Upgrade to Patched Version

Upgrade to the patched version or later. The fix adds comprehensive SSRF protection:

  • Blocks private/internal IP addresses by default
  • Always blocks cloud metadata endpoints (even with allow-local)
  • Only allows http:// and https:// protocols
  • Resolves hostnames before requests to prevent DNS rebinding
  • Validates each redirect target

New force_download='allow-local' Option

If an application legitimately needs to access local/private network resources (e.g., in a fully trusted internal environment), it can explicitly opt in:

from pydantic_ai import ImageUrl

# Default behavior: private IPs are blocked
ImageUrl(url="http://internal-service/image.png")  # Raises ValueError

# Opt-in to allow local access (use with caution)
ImageUrl(url="http://internal-service/image.png", force_download='allow-local')

Important: Cloud metadata endpoints (169.254.169.254, fd00:ec2::254, 100.100.100.200) are always blocked, even with allow-local.

Workaround for Older Versions

If a project cannot upgrade…

Record
GHSA-2jrp-274c-jhv3
CVSS 3.1
8.6 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
Weakness
CWE-918
Updated
2026-11-02
OSVPYSEC-2026-2976 8.6

Pydantic AI has Server-Side Request Forgery (SSRF) in URL Download Handling

Summary

A Server-Side Request Forgery (SSRF) vulnerability exists in Pydantic AI's URL download functionality. When applications accept message history from untrusted sources, attackers can include malicious URLs that cause the server to make HTTP requests to internal network resources, potentially accessing internal services or cloud credentials.

This vulnerability only affects applications that accept message history from external users, such as those using:

  • Agent.to_web or clai web to serve a chat interface
  • VercelAIAdapter for Vercel AI SDK integration
  • AGUIAdapter or Agent.to_ag_ui for AG-UI protocol integration
  • Custom APIs that accept message history from user input

Applications that only use hardcoded or developer-controlled URLs are not affected.

Description

The download_item() helper function downloads content from URLs without validating that the target is a public internet address. When user-supplied message history contains URLs, attackers can:

  1. Access internal services: Request http://127.0.0.1, localhost, or private IP ranges (10.x.x.x, 172.16.x.x, 192.168.x.x)
  2. Steal cloud credentials: Access cloud metadata endpoints (AWS IMDSv1 at 169.254.169.254, GCP, Azure, Alibaba Cloud)
  3. Scan internal networks: Enumerate internal hosts and ports

Who Is Affected

You are affected if your application:

  1. Uses Agent.to_web or clai web - The web interface accepts file attachments via the Vercel AI Data Stream Protocol, where users can provide arbitrary URLs through chat messages.

  2. Uses VercelAIAdapter - Chat interfaces built with Vercel AI SDK allow users to submit messages containing URLs that are processed server-side.

  3. Uses AGUIAdapter or Agent.to_ag_ui - The AG-UI protocol allows users to provide file references with URLs as part of agent interactions.

  4. Exposes a custom API accepting message history - Any endpoint that accepts message history or ImageUrl, AudioUrl, VideoUrl, DocumentUrl objects from user input.

Attack Scenario

Via chat interface, an attacker submits a message with a file attachment pointing to an internal resource:

{
  "role": "user",
  "parts": [
    {"type": "file", "mediaType": "image/png", "url": "http://169.254.169.254/latest/meta-data/iam/security-credentials/"}
  ]
}

Affected Model Integrations

Multiple model integrations download URL content in certain conditions:

| Provider | Downloaded Types | |----------|------------------| | OpenAIChatModel | AudioUrl, DocumentUrl | | AnthropicModel | DocumentUrl (text/plain) | | GoogleModel (GLA) | All URL types (except YouTube and Files API URLs) | | XaiModel | DocumentUrl | | BedrockConverseModel | ImageUrl, DocumentUrl, VideoUrl (non-S3 URLs) | | OpenRouterModel | AudioUrl |

Remediation

Upgrade to Patched Version

Upgrade to the patched version or later. The fix adds comprehensive SSRF protection:

  • Blocks private/internal IP addresses by default
  • Always blocks cloud metadata endpoints (even with allow-local)
  • Only allows http:// and https:// protocols
  • Resolves hostnames before requests to prevent DNS rebinding
  • Validates each redirect target

New force_download='allow-local' Option

If an application legitimately needs to access local/private network resources (e.g., in a fully trusted internal environment), it can explicitly opt in:

from pydantic_ai import ImageUrl

# Default behavior: private IPs are blocked
ImageUrl(url="http://internal-service/image.png")  # Raises ValueError

# Opt-in to allow local access (use with caution)
ImageUrl(url="http://internal-service/image.png", force_download='allow-local')

Important: Cloud metadata endpoints (169.254.169.254, fd00:ec2::254, 100.100.100.200) are always blocked, even with allow-local.

Workaround for Older Versions

If a project cannot upgrade…

Record
PYSEC-2026-2976
CVSS 3.1
8.6 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
Updated
2026-11-02
OSVPYSEC-2026-2980 8.6

Pydantic AI has Server-Side Request Forgery (SSRF) in URL Download Handling

Summary

A Server-Side Request Forgery (SSRF) vulnerability exists in Pydantic AI's URL download functionality. When applications accept message history from untrusted sources, attackers can include malicious URLs that cause the server to make HTTP requests to internal network resources, potentially accessing internal services or cloud credentials.

This vulnerability only affects applications that accept message history from external users, such as those using:

  • Agent.to_web or clai web to serve a chat interface
  • VercelAIAdapter for Vercel AI SDK integration
  • AGUIAdapter or Agent.to_ag_ui for AG-UI protocol integration
  • Custom APIs that accept message history from user input

Applications that only use hardcoded or developer-controlled URLs are not affected.

Description

The download_item() helper function downloads content from URLs without validating that the target is a public internet address. When user-supplied message history contains URLs, attackers can:

  1. Access internal services: Request http://127.0.0.1, localhost, or private IP ranges (10.x.x.x, 172.16.x.x, 192.168.x.x)
  2. Steal cloud credentials: Access cloud metadata endpoints (AWS IMDSv1 at 169.254.169.254, GCP, Azure, Alibaba Cloud)
  3. Scan internal networks: Enumerate internal hosts and ports

Who Is Affected

You are affected if your application:

  1. Uses Agent.to_web or clai web - The web interface accepts file attachments via the Vercel AI Data Stream Protocol, where users can provide arbitrary URLs through chat messages.

  2. Uses VercelAIAdapter - Chat interfaces built with Vercel AI SDK allow users to submit messages containing URLs that are processed server-side.

  3. Uses AGUIAdapter or Agent.to_ag_ui - The AG-UI protocol allows users to provide file references with URLs as part of agent interactions.

  4. Exposes a custom API accepting message history - Any endpoint that accepts message history or ImageUrl, AudioUrl, VideoUrl, DocumentUrl objects from user input.

Attack Scenario

Via chat interface, an attacker submits a message with a file attachment pointing to an internal resource:

{
  "role": "user",
  "parts": [
    {"type": "file", "mediaType": "image/png", "url": "http://169.254.169.254/latest/meta-data/iam/security-credentials/"}
  ]
}

Affected Model Integrations

Multiple model integrations download URL content in certain conditions:

| Provider | Downloaded Types | |----------|------------------| | OpenAIChatModel | AudioUrl, DocumentUrl | | AnthropicModel | DocumentUrl (text/plain) | | GoogleModel (GLA) | All URL types (except YouTube and Files API URLs) | | XaiModel | DocumentUrl | | BedrockConverseModel | ImageUrl, DocumentUrl, VideoUrl (non-S3 URLs) | | OpenRouterModel | AudioUrl |

Remediation

Upgrade to Patched Version

Upgrade to the patched version or later. The fix adds comprehensive SSRF protection:

  • Blocks private/internal IP addresses by default
  • Always blocks cloud metadata endpoints (even with allow-local)
  • Only allows http:// and https:// protocols
  • Resolves hostnames before requests to prevent DNS rebinding
  • Validates each redirect target

New force_download='allow-local' Option

If an application legitimately needs to access local/private network resources (e.g., in a fully trusted internal environment), it can explicitly opt in:

from pydantic_ai import ImageUrl

# Default behavior: private IPs are blocked
ImageUrl(url="http://internal-service/image.png")  # Raises ValueError

# Opt-in to allow local access (use with caution)
ImageUrl(url="http://internal-service/image.png", force_download='allow-local')

Important: Cloud metadata endpoints (169.254.169.254, fd00:ec2::254, 100.100.100.200) are always blocked, even with allow-local.

Workaround for Older Versions

If a project cannot upgrade…

Record
PYSEC-2026-2980
CVSS 3.1
8.6 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
Updated
2026-11-02

Affected products

Affected packages

Affected packages
PackageAffectedFixed
pydantic-ai
PyPI
0.0.26 up to 1.56.0
1.56.0
pydantic-ai-slim
PyPI
0.0.26 up to 1.56.0
1.56.0
pydantic-ai
PyPI
0.0.26 up to 1.56.0, plus listed versions
0.0.270.0.280.0.290.0.300.0.31
Show 45 moreShow less
0.0.320.0.330.0.340.0.350.0.360.0.370.0.380.0.390.0.400.0.410.0.420.0.430.0.440.0.450.0.460.0.470.0.480.0.490.0.500.0.510.0.520.0.530.0.540.0.550.1.00.1.10.1.100.1.110.1.120.1.20.1.30.1.40.1.50.1.60.1.70.1.80.1.90.2.00.2.10.2.100.2.110.2.120.2.130.2.140.2.15
1.56.0
pydantic-ai-slim
PyPI
0.0.26 up to 1.56.0, plus listed versions
0.0.270.0.280.0.290.0.300.0.31
Show 45 moreShow less
0.0.320.0.330.0.340.0.350.0.360.0.370.0.380.0.390.0.400.0.410.0.420.0.430.0.440.0.450.0.460.0.470.0.480.0.490.0.500.0.510.0.520.0.530.0.540.0.550.1.00.1.10.1.100.1.110.1.120.1.20.1.30.1.40.1.50.1.60.1.70.1.80.1.90.2.00.2.10.2.100.2.110.2.120.2.130.2.140.2.15
1.56.0

History

History
RecordedChangedSources
first indexedCVE List, EUVD, GitHub Advisories, NVD, OSV

Dates are when Every CVE recorded each change. Upstream dates may differ.

In short

CVE-2026-25580 is a high vulnerability (CVSS 8.6) in Pydantic Ai, published February 6, 2026. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.65%, the 51st percentile. Fixed in pydantic-ai 1.56.0.

References

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