CVE-2026-59213

Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform. From 0.6.27 before 0.10.0, get_all_models handlers in routers/openai.py and routers/ollama.py passed a lambda to aiocache key instead of key_builder, causing permission-filtered per-user model lists to share a static cache entry and exposing one user’s model list to another caller during the TTL window. This issue is fixed in version 0.10.0.

Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform. From 0.6.27 before 0.10.0, get_all_models handlers in routers/openai.py and routers/ollama.py passed a lambda to aiocache key instead of key_builder, causing permission-filtered per-user model lists to share a static cache entry and exposing one user’s model list to another caller during the TTL window. This issue is fixed in version 0.10.0.

Summary

The get_all_models handlers in routers/openai.py and routers/ollama.py intended to cache their permission-filtered model lists per user, but the @cached decorator was misconfigured: it passed a key= lambda instead of key_builder=. In aiocache 0.12.3 (the pinned version), key= is a static cache key — a callable passed there is used as a constant object, not invoked per call. As a result the per-user key was never computed, and all callers collided onto a single shared cache entry within the TTL window. During that window, one user's permission-filtered model list could be served to a different authenticated user, crossing the per-user authorization boundary.

Impact

• Boundary crossed: Confidentiality (cross-user). A caller can receive the model list scoped to a different security principal than themselves.
• A user (or admin, or — depending on endpoint reachability — anonymous caller) who populates the cache causes the next caller within the TTL to receive that list rather than their own permission-filtered one.
• What's disclosed is the set of models another principal can access, including potentially the existence and naming of models restricted from the receiving user.
• Exposure is incidental and timing-dependent, not attacker-controlled: the leaked entry is whatever the most recent caller populated within MODELS_CACHE_TTL (default 1 second), and the attacker cannot select the victim or force a target's list into the cache.

Affected component

• backend/open_webui/routers/openai.py — get_all_models (~line 488)
• backend/open_webui/routers/ollama.py — get_all_models (~line 302)

Both decorated with @cached(ttl=MODELS_CACHE_TTL, key=lambda ...). No other @cached(... key=lambda ...) misuse was found elsewhere in the backend.

Root cause

aiocache 0.12's @cached treats key= as a static key; the per-call hook is key_builder= with signature key_builder(func, *args, **kwargs). Passing a callable to key= uses the callable object itself as a constant key, so every invocation resolved to the same entry and the intended per-user.id namespacing never occurred.

Reproduction (default config)

1. On a default deployment, configure at least two users with different model-access permissions (e.g. one model restricted to user A).
2. As user A, request the model list (populates the shared cache entry).
3. Within MODELS_CACHE_TTL (default 1s), as user B, request the model list.
4. User B receives user A's permission-filtered list, including models B is not permitted to see.

Remediation

Replace key= with key_builder= at both call sites and adjust the lambda to take the function as its first argument:

@cached(
    ttl=MODELS_CACHE_TTL,
    key_builder=lambda _func, request, user=None: (
        f'openai_all_models_{user.id}' if user else 'openai_all_models'
    ),
)

Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform. From 0.6.27 before 0.10.0, get_all_models handlers in routers/openai.py and routers/ollama.py passed a lambda to aiocache key instead of key_builder, causing permission-filtered per-user model lists to share a static cache entry and exposing one user’s model list to another caller during the TTL window. This issue is fixed in version 0.10.0.

Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform. From 0.6.27 before 0.10.0, get_all_models handlers in routers/openai.py and routers/ollama.py passed a lambda to aiocache key instead of key_builder, causing permission-filtered per-user model lists to share a static cache entry and exposing one user’s model list to another caller during the TTL window. This issue is fixed in version 0.10.0.

Summary

The get_all_models handlers in routers/openai.py and routers/ollama.py intended to cache their permission-filtered model lists per user, but the @cached decorator was misconfigured: it passed a key= lambda instead of key_builder=. In aiocache 0.12.3 (the pinned version), key= is a static cache key — a callable passed there is used as a constant object, not invoked per call. As a result the per-user key was never computed, and all callers collided onto a single shared cache entry within the TTL window. During that window, one user's permission-filtered model list could be served to a different authenticated user, crossing the per-user authorization boundary.

Impact

• Boundary crossed: Confidentiality (cross-user). A caller can receive the model list scoped to a different security principal than themselves.
• A user (or admin, or — depending on endpoint reachability — anonymous caller) who populates the cache causes the next caller within the TTL to receive that list rather than their own permission-filtered one.
• What's disclosed is the set of models another principal can access, including potentially the existence and naming of models restricted from the receiving user.
• Exposure is incidental and timing-dependent, not attacker-controlled: the leaked entry is whatever the most recent caller populated within MODELS_CACHE_TTL (default 1 second), and the attacker cannot select the victim or force a target's list into the cache.

Affected component

• backend/open_webui/routers/openai.py — get_all_models (~line 488)
• backend/open_webui/routers/ollama.py — get_all_models (~line 302)

Both decorated with @cached(ttl=MODELS_CACHE_TTL, key=lambda ...). No other @cached(... key=lambda ...) misuse was found elsewhere in the backend.

Root cause

aiocache 0.12's @cached treats key= as a static key; the per-call hook is key_builder= with signature key_builder(func, *args, **kwargs). Passing a callable to key= uses the callable object itself as a constant key, so every invocation resolved to the same entry and the intended per-user.id namespacing never occurred.

Reproduction (default config)

1. On a default deployment, configure at least two users with different model-access permissions (e.g. one model restricted to user A).
2. As user A, request the model list (populates the shared cache entry).
3. Within MODELS_CACHE_TTL (default 1s), as user B, request the model list.
4. User B receives user A's permission-filtered list, including models B is not permitted to see.

Remediation

Replace key= with key_builder= at both call sites and adjust the lambda to take the function as its first argument:

@cached(
    ttl=MODELS_CACHE_TTL,
    key_builder=lambda _func, request, user=None: (
        f'openai_all_models_{user.id}' if user else 'openai_all_models'
    ),
)

Summary

The get_all_models handlers in routers/openai.py and routers/ollama.py intended to cache their permission-filtered model lists per user, but the @cached decorator was misconfigured: it passed a key= lambda instead of key_builder=. In aiocache 0.12.3 (the pinned version), key= is a static cache key — a callable passed there is used as a constant object, not invoked per call. As a result the per-user key was never computed, and all callers collided onto a single shared cache entry within the TTL window. During that window, one user's permission-filtered model list could be served to a different authenticated user, crossing the per-user authorization boundary.

Impact

• Boundary crossed: Confidentiality (cross-user). A caller can receive the model list scoped to a different security principal than themselves.
• A user (or admin, or — depending on endpoint reachability — anonymous caller) who populates the cache causes the next caller within the TTL to receive that list rather than their own permission-filtered one.
• What's disclosed is the set of models another principal can access, including potentially the existence and naming of models restricted from the receiving user.
• Exposure is incidental and timing-dependent, not attacker-controlled: the leaked entry is whatever the most recent caller populated within MODELS_CACHE_TTL (default 1 second), and the attacker cannot select the victim or force a target's list into the cache.

Affected component

• backend/open_webui/routers/openai.py — get_all_models (~line 488)
• backend/open_webui/routers/ollama.py — get_all_models (~line 302)

Both decorated with @cached(ttl=MODELS_CACHE_TTL, key=lambda ...). No other @cached(... key=lambda ...) misuse was found elsewhere in the backend.

Root cause

aiocache 0.12's @cached treats key= as a static key; the per-call hook is key_builder= with signature key_builder(func, *args, **kwargs). Passing a callable to key= uses the callable object itself as a constant key, so every invocation resolved to the same entry and the intended per-user.id namespacing never occurred.

Reproduction (default config)

1. On a default deployment, configure at least two users with different model-access permissions (e.g. one model restricted to user A).
2. As user A, request the model list (populates the shared cache entry).
3. Within MODELS_CACHE_TTL (default 1s), as user B, request the model list.
4. User B receives user A's permission-filtered list, including models B is not permitted to see.

Remediation

Replace key= with key_builder= at both call sites and adjust the lambda to take the function as its first argument:

@cached(
    ttl=MODELS_CACHE_TTL,
    key_builder=lambda _func, request, user=None: (
        f'openai_all_models_{user.id}' if user else 'openai_all_models'
    ),
)