Pydantic Ai
Monthly
Pydantic AI versions 0.0.26 through 1.55.x contain a server-side request forgery vulnerability in URL download functionality that allows remote attackers to make arbitrary HTTP requests to internal network resources when applications process untrusted message history. Public exploit code exists for this vulnerability, which could enable attackers to access internal services or cloud credentials. Applications must upgrade to version 1.56.0 or later to remediate the issue.
Server-Side Request Forgery in Pydantic AI's UI adapter layer (versions 1.65.0-1.105.0 and 2.0.0b1-2.0.0b5) allows unauthenticated network clients to redirect the application server into fetching arbitrary cloud-storage objects using the server's own credentials. UploadedFile references - carrying provider file IDs or cloud-storage URIs such as s3:// or gs:// - submitted via client message history bypass the scheme allowlist applied to ordinary file URLs and are resolved server-side using the application's IAM role, service account, or API key. No public exploit has been identified at time of analysis, and no CISA KEV listing exists, but the scope-changing confidentiality impact (CVSS S:C/C:H) warrants prompt patching for any deployment exposing the Vercel AI adapter or similar UI adapters to untrusted clients.
Tool call injection in Pydantic AI's UI adapters (AG-UI via Agent.to_ag_ui()/AGUIAdapter, and Vercel AI via VercelAIAdapter) enables remote unauthenticated clients to force execution of registered server-side tools with attacker-supplied arguments, bypassing the framework's message-sanitization defense. The flaw affects pydantic-ai and pydantic-ai-slim versions 1.88.0-1.107.0 and 2.0.0b1-2.4.x. No public exploit code or CISA KEV listing exists at time of analysis, but the attack is low-complexity and exploitable against default configurations of applications using either UI adapter.
Server-Side Request Forgery in Pydantic AI (versions 1.56.0-1.101.0, 2.0.0b1, 2.0.0b2) allows unauthenticated network attackers to bypass the cloud-metadata IP blocklist by encoding metadata service addresses (e.g., 169.254.169.254) in IPv6 transition forms - specifically IPv4-compatible IPv6, NAT64 RFC 8215 local-use prefixes, operator-chosen NAT64 prefixes, and ISATAP - that the prior remediation (CVE-2026-46678) failed to decode, enabling retrieval of cloud IAM short-term credentials. Exploitation is constrained by two simultaneous prerequisites: the application must use the non-default `force_download='allow-local'` mode and must operate on a network that routes the affected IPv6 transition forms (e.g., IPv6-only or dual-stack-with-NAT64 Kubernetes clusters). This is the third iteration in an escalating bypass chain (CVE-2026-25580 → CVE-2026-46678 → CVE-2026-48782), and no public exploit has been identified at time of analysis.
Pydantic AI versions 1.34.0 through 1.50.x contain a path traversal vulnerability in the web UI that allows unauthenticated attackers to inject arbitrary JavaScript by manipulating the CDN version parameter in a malicious URL. When a victim visits the crafted link, attacker-controlled code executes in their browser, enabling theft of chat history and other sensitive client-side data. No patch is currently available.
Pydantic AI versions 0.0.26 through 1.55.x contain a server-side request forgery vulnerability in URL download functionality that allows remote attackers to make arbitrary HTTP requests to internal network resources when applications process untrusted message history. Public exploit code exists for this vulnerability, which could enable attackers to access internal services or cloud credentials. Applications must upgrade to version 1.56.0 or later to remediate the issue.
Server-Side Request Forgery in Pydantic AI's UI adapter layer (versions 1.65.0-1.105.0 and 2.0.0b1-2.0.0b5) allows unauthenticated network clients to redirect the application server into fetching arbitrary cloud-storage objects using the server's own credentials. UploadedFile references - carrying provider file IDs or cloud-storage URIs such as s3:// or gs:// - submitted via client message history bypass the scheme allowlist applied to ordinary file URLs and are resolved server-side using the application's IAM role, service account, or API key. No public exploit has been identified at time of analysis, and no CISA KEV listing exists, but the scope-changing confidentiality impact (CVSS S:C/C:H) warrants prompt patching for any deployment exposing the Vercel AI adapter or similar UI adapters to untrusted clients.
Tool call injection in Pydantic AI's UI adapters (AG-UI via Agent.to_ag_ui()/AGUIAdapter, and Vercel AI via VercelAIAdapter) enables remote unauthenticated clients to force execution of registered server-side tools with attacker-supplied arguments, bypassing the framework's message-sanitization defense. The flaw affects pydantic-ai and pydantic-ai-slim versions 1.88.0-1.107.0 and 2.0.0b1-2.4.x. No public exploit code or CISA KEV listing exists at time of analysis, but the attack is low-complexity and exploitable against default configurations of applications using either UI adapter.
Server-Side Request Forgery in Pydantic AI (versions 1.56.0-1.101.0, 2.0.0b1, 2.0.0b2) allows unauthenticated network attackers to bypass the cloud-metadata IP blocklist by encoding metadata service addresses (e.g., 169.254.169.254) in IPv6 transition forms - specifically IPv4-compatible IPv6, NAT64 RFC 8215 local-use prefixes, operator-chosen NAT64 prefixes, and ISATAP - that the prior remediation (CVE-2026-46678) failed to decode, enabling retrieval of cloud IAM short-term credentials. Exploitation is constrained by two simultaneous prerequisites: the application must use the non-default `force_download='allow-local'` mode and must operate on a network that routes the affected IPv6 transition forms (e.g., IPv6-only or dual-stack-with-NAT64 Kubernetes clusters). This is the third iteration in an escalating bypass chain (CVE-2026-25580 → CVE-2026-46678 → CVE-2026-48782), and no public exploit has been identified at time of analysis.
Pydantic AI versions 1.34.0 through 1.50.x contain a path traversal vulnerability in the web UI that allows unauthenticated attackers to inject arbitrary JavaScript by manipulating the CDN version parameter in a malicious URL. When a victim visits the crafted link, attacker-controlled code executes in their browser, enabling theft of chat history and other sensitive client-side data. No patch is currently available.