Summary
Pydantic AI: Concurrency-limited models can keep their slot when a streamed request ends early
This issue was posted by Codex Desktop using gpt-6.1-sol on behalf of David.
Applications that wrap a model with ConcurrencyLimitedModel or limit_model_concurrency can permanently lose shared concurrency capacity when a streamed request releases its slot from a different task than the one that acquired it. This can happen when a stream ends early, and also when a stream is fully consumed using the default stream_text() debouncing.
In an application that exposes an affected streaming endpoint to network clients and shares a long-lived model limiter across requests, a client can repeatedly start a stream and disconnect. The completed requests retain their slots, eventually preventing subsequent requests that share the limiter from proceeding.
Agent-level max_concurrency and non-streaming model requests are not affected by this defect.
Details
The built-in limiter uses anyio.CapacityLimiter, which associates each acquired slot with its borrowing task. Pydantic AI's streaming lifecycle can acquire the slot on the task consuming the stream and run cleanup on another internal task. The limiter rejects that release, so the slot remains occupied even after the request has ended. Cleanup can raise a RuntimeError; a later request on the borrowing task can also fail because that task still holds a slot.
Early termination includes stopping iteration, a consumer exception, and cancellation. Fully consuming stream_text() with its default debounce_by=0.1 can also reach the cross-task release path. Fully consumed streams must therefore not be assumed safe.
Mitigation
Upgrade to a patched release of pydantic-ai or pydantic-ai-slim. If you cannot upgrade yet, use the agent-level max_concurrency setting instead of a concurrency-limited model, or avoid streaming runs through a concurrency-limited model.
Impact
CVE-2026-107286 has a CVSS score of 7.5 (High). The vector is network-reachable, no privileges required, and no user interaction. A CVSS score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether this affects your application depends on whether the vulnerable code is present and reachable in your environment. A fixed version is available (2.53.0); upgrading removes the vulnerable code path.
Affected versions
Security releases
Kodem intelligence
Severity tells you how bad this could be in the worst case. It does not tell you whether you are exposed. Exploitability and impact are functions of runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A vulnerable package can sit in your dependency tree and never run.
Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter. Kodem's runtime-powered SCA identifies whether this CVE is reachable in your applications.
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pydantic-ai to 2.53.0 or later; pydantic-ai-slim to 2.53.0 or later
Kodem Kai can prioritize this vulnerability in your dependency tree and generate a fix recommendation.
Frequently Asked Questions
- What is CVE-2026-107286? CVE-2026-107286 is a high-severity security vulnerability in pydantic-ai (pip), affecting versions >= 2.10.0, < 2.53.0. It is fixed in 2.53.0.
- How severe is CVE-2026-107286? CVE-2026-107286 has a CVSS score of 7.5 (High). This score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether it represents real risk in your environment depends on whether the vulnerable code is present and reachable.
- Which packages are affected by CVE-2026-107286?
pydantic-ai(pip) (versions >= 2.10.0, < 2.53.0)pydantic-ai-slim(pip) (versions >= 2.10.0, < 2.53.0)
- Is there a fix for CVE-2026-107286? Yes. CVE-2026-107286 is fixed in 2.53.0. Upgrade to this version or later.
- Is CVE-2026-107286 exploitable, and should I be worried? Whether CVE-2026-107286 is exploitable in your environment depends on whether the vulnerable code is present and reachable. A CVSS score is a worst-case rating; it does not account for your specific deployment, configuration, or usage patterns. Kodem, an Intelligent Application Security platform, uses runtime intelligence to show which vulnerabilities actually execute in production, so you can focus on the ones that represent real risk. Get a demo
- What actually determines whether CVE-2026-107286 is exploitable, and how bad it is? Exploitability and impact are not fixed properties of a CVE. They depend on runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A high CVSS score on a dependency that never runs is not the same as real risk. Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter.
- How do I fix CVE-2026-107286?
- Upgrade
pydantic-aito 2.53.0 or later - Upgrade
pydantic-ai-slimto 2.53.0 or later
- Upgrade