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b821420dee
* scrub genai API keys and onvif credentials from config endpoint
* enforce camera access in thumbnail tracked-object fallback
The /events/{id}/thumbnail endpoint called require_camera_access when
loading persisted events but skipped the check in the tracked-object
fallback path for in-progress events. A restricted viewer could
retrieve thumbnails from cameras they should not have access to.
* block filter and attach flags in custom ffmpeg export args
The ffmpeg argument blocklist missed -filter_complex, -lavfi, -vf,
-af, -filter, and -attach. These flags can read arbitrary files via
source filters like movie= and amovie=, bypassing the existing -i
block. A user with camera access could exploit this through the
custom export endpoint.
* enforce camera access on VLM monitor endpoint
POST /vlm/monitor allowed any authenticated user to start VLM
monitoring on any camera without checking camera access. A viewer
restricted to specific cameras could monitor cameras they should
not have access to.
* enforce camera access in chat start_camera_watch tool
The start_camera_watch tool called via POST /chat/completion did not
validate camera access, allowing a restricted viewer to start VLM
monitoring on cameras outside their allowed set through the chat
interface.
* restrict review summary endpoint to admin role
* fix require_role call passing string instead of list
* fix section config uiSchema merge replacing base entries
mergeSectionConfig was replacing the entire base uiSchema when a
level override (global/camera) also defined one, causing base-level
ui:after/ui:before directives to be silently dropped. This broke
the SemanticSearchReindex button which was defined in base uiSchema.
Frigate NVR™ - Realtime Object Detection for IP Cameras
[English] | 简体中文
A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras.
Use of a GPU or AI accelerator is highly recommended. AI accelerators will outperform even the best CPUs with very little overhead. See Frigate's supported object detectors.
- Tight integration with Home Assistant via a custom component
- Designed to minimize resource use and maximize performance by only looking for objects when and where it is necessary
- Leverages multiprocessing heavily with an emphasis on realtime over processing every frame
- Uses a very low overhead motion detection to determine where to run object detection
- Object detection with TensorFlow runs in separate processes for maximum FPS
- Communicates over MQTT for easy integration into other systems
- Records video with retention settings based on detected objects
- 24/7 recording
- Re-streaming via RTSP to reduce the number of connections to your camera
- WebRTC & MSE support for low-latency live view
Documentation
View the documentation at https://docs.frigate.video
Donations
If you would like to make a donation to support development, please use Github Sponsors.
License
This project is licensed under the MIT License.
- Code: The source code, configuration files, and documentation in this repository are available under the MIT License. You are free to use, modify, and distribute the code as long as you include the original copyright notice.
- Trademarks: The "Frigate" name, the "Frigate NVR" brand, and the Frigate logo are trademarks of Frigate, Inc. and are not covered by the MIT License.
Please see our Trademark Policy for details on acceptable use of our brand assets.
Screenshots
Live dashboard
Streamlined review workflow
Multi-camera scrubbing
Built-in mask and zone editor
Translations
We use Weblate to support language translations. Contributions are always welcome.
Copyright © 2026 Frigate, Inc.