Browser-Side Background Removal Now Rivals Server APIs at Under 300ms

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By 2026, background removal can run entirely within the browser in under 300 milliseconds, eliminating the need to upload images to third-party servers. Client-side libraries like bg-remove-sdk use WebGPU or WASM to run AI models locally, with model weights cached after the first load for offline use. A hybrid approach — previewing locally and only sending edge-case images to paid APIs — allows teams to keep 80–90% of processing entirely on the client side. For delivery, WebP with alpha transparency outperforms PNG, with real-world file sizes roughly 28% smaller, a meaningful saving across large product catalogs. Editors are advised to inspect cutouts at full resolution on both light and dark backgrounds to catch fringe artifacts before resizing or publishing.

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New Cyber-OSINT model released

Article URL: https://twitter.com/0x0SojalSec/status/2104736980768866439 Comments URL: https://news.ycombinator.com/item?id=49890829 Points: 4 # Comments: 0

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ProgrammingDEV Community ·

Webhook Signature Verification Alone Does Not Guarantee Request Authorization

Verifying an HMAC webhook signature only confirms that a payload originated from a vendor, not that the request is authorized to modify specific resources in your system. Developers must separately map incoming events to internal subjects and apply proper authorization checks — covering tenant, user, and resource — before executing any side effects. A correctly signed payload can still contain a spoofed tenant ID or an action the customer never permitted. Network trust and cryptographic authenticity do not substitute for a defined authorization policy. Experts recommend evaluating subject, action, and resource before mutating any system state.

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ProgrammingDEV Community ·

Developer Splits 2,000-Line Home Assistant Config into 8 Organised Files Using Python

A Home Assistant user refactored a bloated 2,144-line automations.yaml file — spanning 63 automations across heating, alarms, cameras, and more — into eight separate, topic-specific files. The main concern was silently breaking critical automations, such as heating controls managing 11 thermostats, during the refactor. To address this, the developer wrote a 40-line Python script to split the file and a separate verification script to confirm no automations were lost in the process. Classification was handled through substring matching on German-language automation aliases, routing each entry into a named bucket like 'heating' or 'alarm', with unmatched entries falling into a miscellaneous file. The project highlights a practical approach to managing growing smart-home configuration files without relying on metadata tags or manual reorganisation.

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ProgrammingDEV Community ·

How to Build Identity-Aware AI Agents Using Microsoft Agent Framework and Auth0

A developer built a four-part tutorial series demonstrating how to add proper identity and authorization controls to AI agents using Microsoft Agent Framework and Auth0. The project centers on a fictional expense-approval agent where a manager interacts with an AI that retrieves reports, sends emails, and approves or rejects expenses on their behalf. Each agent capability — from reading expense data to taking actions — required its own distinct identity and authorization decision, rather than a single blanket permission. Auth0's Fine-Grained Authorization was used to filter accessible data before vector search runs, ensuring the underlying language model never processes information a user is not permitted to see. The series, published on the Auth0 blog, aims to address the identity and accountability gaps that most AI agent tutorials overlook entirely.

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