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Search Results (14 CVEs found)
| CVE | Vendors | Products | Updated | CVSS v3.1 |
|---|---|---|---|---|
| CVE-2026-84381 | 1 Pydantic | 2 Httpcore2, Httpx2 | 2026-09-05 | 8.1 High |
| HTTPX2 is a next generation HTTP client for Python. Prior to 2.10.0, httpcore2 fails to start TLS in src/httpcore2/httpcore2/_sync/socks_proxy.py and src/httpcore2/httpcore2/_async/socks_proxy.py when the remote origin uses wss through a SOCKS5 proxy because the TLS upgrade condition only recognizes https. HTTPX2 exposes the flaw through Client.websocket() and AsyncClient.websocket() from 2.6.0 through 2.9.1, so the opening handshake, query parameters, Authorization headers, cookies, and subsequent frames can cross the proxy path in plaintext without certificate verification. An attacker controlling or observing that path can read or modify traffic and impersonate the WebSocket server. This issue is fixed in httpcore2 2.10.0 and HTTPX2 2.10.0. | ||||
| CVE-2026-84378 | 1 Pydantic | 1 Httpx2 | 2026-09-03 | 5.9 Medium |
| HTTPX2 is a next generation HTTP client for Python. From 2.5.0 until 2.10.0, the HTTPX2 Server-Sent Events parser in src/httpx2/httpx2/_sse.py repeatedly copies and rescans buffered text in _SSELineDecoder.decode() when an attacker-controlled or compromised SSE endpoint splits one unterminated line across many response chunks. The behavior affects httpx2.Client.sse() and httpx2.AsyncClient.sse(), and the total processing work grows quadratically with the line length, allowing a crafted stream to consume excessive CPU and block a synchronous worker or asynchronous event loop. This issue is fixed in version 2.10.0. | ||||
| CVE-2026-84379 | 1 Pydantic | 1 Httpx2 | 2026-09-03 | 5.3 Medium |
| HTTPX2 is a next generation HTTP client for Python. Prior to 2.11.0, FileField.render_headers() in src/httpx2/httpx2/_multipart.py directly interpolates attacker-controlled content_type values and custom headers from the files= three-element (filename, content, content_type) tuple and the files= four-element (filename, content, content_type, headers) tuple into multipart/form-data part headers without validating header names or values. CR or LF characters can terminate a part header, inject additional part headers, or end the part header block early, allowing a downstream multipart parser to treat attacker-supplied lines as genuine headers and potentially alter part semantics or bypass header-based checks. This issue is fixed in version 2.11.0. | ||||
| CVE-2026-84380 | 1 Pydantic | 1 Httpx2 | 2026-09-03 | 5.6 Medium |
| HTTPX2 is a next generation HTTP client for Python. Prior to 2.11.0, Request._prepare() in src/httpx2/httpx2/_models.py can add a body-derived Content-Length header to a request that already contains a caller-supplied Transfer-Encoding header because its setdefault() processing checks each default header independently rather than treating the two framing headers as mutually exclusive. Fixed-size byte, JSON, form, and known-length multipart bodies can therefore be serialized over HTTP/1.1 with both headers, allowing request smuggling or connection desynchronization when downstream intermediaries disagree about which framing header takes precedence. This issue is fixed in version 2.11.0. | ||||
| CVE-2026-84382 | 1 Pydantic | 1 Httpx2 | 2026-09-03 | 7.5 High |
| HTTPX2 is a next generation HTTP client for Python. Prior to 2.12.0, the HTTPX2 content decoders in src/httpx2/httpx2/_decoders.py fully inflate each gzip, deflate, br, or zstd network chunk before iter_bytes() or aiter_bytes() yields bounded pieces to the application. A 64 KiB compressed chunk can expand to approximately 64 MiB in one intermediate allocation, so an attacker-controlled or compromised server can cause severe memory pressure or out-of-memory process termination even when the application streams the response. This issue is fixed in version 2.12.0. | ||||
| CVE-2026-46678 | 1 Pydantic | 2 Pydantic-ai, Pydantic Ai | 2026-07-30 | 6.8 Medium |
| Pydantic AI is a Python agent framework for building Generative AI applications. In versions 1.56.0 through 1.98.0, when an application opts a URL into force_download='allow-local' (disabling the default block on private/internal IPs), the cloud-metadata blocklist could be bypassed by encoding the metadata IP in an IPv6 transition form (IPv4-mapped IPv6, 6to4, or NAT64), exposing cloud IAM short-term credentials on dual-stack or translated networks. This is an incomplete fix of GHSA-2jrp-274c-jhv3 / CVE-2026-25580, whose remediation did not hold for IPv6-encoded forms of the metadata IPs. An application is affected only if it explicitly opts a FileUrl (ImageUrl, AudioUrl, VideoUrl, DocumentUrl) into force_download='allow-local' on a URL influenced by untrusted input; it is not affected when using bundled integrations to ingest user input (Agent.to_web / clai web, VercelAIAdapter, AGUIAdapter / Agent.to_ag_ui), since they do not propagate force_download from external data, nor when downloading only from developer-controlled URLs. This issue has been fixed in version 1.99.0. | ||||
| CVE-2026-65975 | 1 Pydantic | 2 Pydantic-ai, Pydantic Ai | 2026-07-30 | 6.5 Medium |
| Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. In versions 1.88.0 up to but not including 1.107.1 and 2.0.0b1 up to but not including 2.5.0, the UI adapters (AG-UI via Agent.to_ag_ui()/AGUIAdapter, and Vercel AI via VercelAIAdapter) use sanitize_messages to strip unresolved ("dangling") client-submitted tool calls from untrusted message history before it reaches the agent, a defense-in-depth default that prevents the agent from executing tool calls the model never emitted. However, the strip anchored to a message index computed before sanitization ran, so when a trailing client message sanitized to empty and was dropped (for example a client system message under the default manage_system_prompt='server'), a preceding assistant response carrying an unresolved tool call became the new tail and was dispatched without inspection. As a result, a remote client could cause a registered, non-approval server tool to run with client-supplied arguments rather than arguments the model produced. The impact is bounded by what the affected tools do and is most significant for applications that gate tool execution in a model-request hook (before_model_request / after_model_request), since a forged call skips the model turn and bypasses that guardrail; approval-gated tools (requires_approval=True) are not auto-executed by this path. This issue has been fixed in versions 1.107.1 and 2.5.0. | ||||
| CVE-2026-54249 | 1 Pydantic | 2 Pydantic-ai, Pydantic Ai | 2026-07-30 | 6.8 Medium |
| Pydantic AI is a Python agent framework for building Generative AI applications. In versions 1.65.0 through 1.105.0, and 2.0.0b1 through 2.0.0b5, a client that submits message history to a Pydantic AI UI adapter (such as the Vercel AI adapter) can reference arbitrary files in the application's model-provider or cloud-storage account. While file URL parts are validated against a scheme allowlist, UploadedFile references — which point to a file by provider file ID or cloud-storage URI (e.g. s3://…, gs://…) — were forwarded without validation. Because the provider resolves an UploadedFile using the server-side identity (IAM role, service account, or provider API key) rather than the client's, an attacker can craft message history to make the server read objects from its own account or other tenants, given a referenceable identifier. Exploitation requires a valid file identifier, which is not always unguessable depending on how the application names objects. This issue has been fixed in versions 1.106.0 and 2.0.0b6. | ||||
| CVE-2026-58203 | 1 Pydantic | 2 Pydantic-ai, Pydantic-settings | 2026-07-09 | 5.3 Medium |
| pydantic-settings provides settings management using Pydantic. From 2.12.0 until 2.14.2, NestedSecretsSettingsSource reads secret values from files in a configured secrets_dir. When secrets_nested_subdir=True, a directory entry inside secrets_dir that is a symbolic link pointing outside secrets_dir is followed, so files outside the configured directory are read into settings values. The same code path bypasses the documented secrets_dir_max_size protection. An attacker or lower-privileged component able to influence entries in the configured secrets directory (for example, a writable or shared secrets mount) can turn this into an unintended local file read into settings and can defeat the advertised loading-size cap. This vulnerability is fixed in 2.14.2. | ||||
| CVE-2026-48782 | 1 Pydantic | 2 Pydantic-ai, Pydantic Ai | 2026-06-17 | 6.8 Medium |
| Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. In versions 1.56.0 through 1.101.0, 2.0.0b1, and 2.0.0b2, the cloud-metadata blocklist could be bypassed by encoding the metadata IP in an IPv6 transition form that the previous fix, CVE-2026-46678, did not decode, exposing cloud IAM short-term credentials. The previous remediation decoded only IPv4-mapped IPv6, 6to4, and the NAT64 well-known prefix, so the metadata guarantee did not hold for the remaining transition forms: IPv4-compatible IPv6 (::a.b.c.d), the NAT64 RFC 8215 local-use prefix (64:ff9b:1::/48), operator-chosen NAT64 prefixes, and ISATAP. The IPv6 wrapper is then delivered to the underlying IPv4 metadata endpoint. This occurs when an application using Pydantic AI opts a URL into force_download='allow-local' (which disables the default block on private/internal IPs) and runs on a network that actually routes the affected IPv6 transition forms: NAT64-configured networks (IPv6-only or dual-stack-with-NAT64 deployments, including some Kubernetes setups) for the NAT64 variants, or networks with an ISATAP tunnel for ISATAP. A standard dual-stack cloud VM or container does not route these forms and is not affected in practice. The IPv4-compatible and Teredo variants are deprecated and addressed as defense-in-depth. This is an incomplete fix of GHSA-cqp8-fcvh-x7r3 / CVE-2026-46678 (itself a follow-up to CVE-2026-25580). This issue has been fixed in version 2.0.0b3. | ||||
| CVE-2026-25640 | 1 Pydantic | 2 Pydantic-ai, Pydantic Ai | 2026-04-17 | 7.1 High |
| Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 1.34.0 to before 1.51.0, a path traversal vulnerability in the Pydantic AI web UI allows an attacker to serve arbitrary JavaScript in the context of the application by crafting a malicious URL. In affected versions, the CDN URL is constructed using a version query parameter from the request URL. This parameter is not validated, allowing path traversal sequences that cause the server to fetch and serve attacker-controlled HTML/JavaScript from an arbitrary source on the same CDN, instead of the legitimate chat UI package. If a victim clicks the link or visits it via an iframe, attacker-controlled code executes in their browser, enabling theft of chat history and other client-side data. This vulnerability only affects applications that use Agent.to_web to serve a chat interface and clai web to serve a chat interface from the CLI. These are typically run locally (on localhost), but may also be deployed on a remote server. This vulnerability is fixed in 1.51.0. | ||||
| CVE-2026-25580 | 1 Pydantic | 2 Pydantic-ai, Pydantic Ai | 2026-04-17 | 8.6 High |
| 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. | ||||
| CVE-2024-3772 | 4 Fedoraproject, Pydantic, Pydantic Project and 1 more | 4 Fedora, Pydantic, Pydantic and 1 more | 2025-12-09 | 5.9 Medium |
| Regular expression denial of service in Pydanic < 2.4.0, < 1.10.13 allows remote attackers to cause denial of service via a crafted email string. | ||||
| CVE-2021-29510 | 2 Fedoraproject, Pydantic | 2 Fedora, Pydantic | 2025-12-08 | 3.3 Low |
| Pydantic is a data validation and settings management using Python type hinting. In affected versions passing either `'infinity'`, `'inf'` or `float('inf')` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can't upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you'll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic. | ||||
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