CVE-2026-11922 zenml-io CVE debrief

Who should care

Security teams and administrators responsible for systems using zenml-io/zenml versions 0.57.0 through 0.94.2 should be aware of this vulnerability and take steps to mitigate the risk. This includes applying patches or updates, implementing compensating controls, and monitoring for potential credential guessing attacks.

Technical summary

A vulnerability in zenml-io/zenml versions 0.57.0 through 0.94.2 allows an attacker to bypass rate-limiting on the `POST /api/v1/login` and self password-change endpoints by rotating the `X-Forwarded-For` header. The rate limiter keys requests by `request.client.host`, which is derived from the `X-Forwarded-For` header when Uvicorn is launched with `--proxy-headers --forwarded-allow-ips *`. This configuration allows clients to control the value of `request.client.host`, effectively bypassing rate-limiting protections.

Defensive priority

This vulnerability has a CVSS score of 6.5 and is classified as MEDIUM severity, indicating a moderate level of risk. Affected systems should prioritize patching to prevent potential credential guessing attacks.

Recommended defensive actions

• Inventory and verify the version of zenml-io/zenml in use.
• Apply patches or updates to zenml-io/zenml versions 0.57.0 through 0.94.2.
• Implement compensating controls, such as monitoring and rate-limiting on affected endpoints.
• Consider exception tracking for systems that cannot be patched immediately.
• Review relevant monitoring, detection, and logs for exposed assets that need extra review.
• Track exceptions, retest remediated assets, and close the item only after evidence is documented.
• Confirm whether affected product deployments exist in managed environments and assign an owner for follow-up.

Evidence notes

Evidence is limited; primary official records indicate a vulnerability in zenml-io/zenml versions 0.57.0 through 0.94.2 that allows bypassing rate-limiting on certain endpoints. Further verification is needed to determine the full scope of affected systems and potential impact.

Sources and references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.