Why deleting a file in Linux may not free disk space immediately

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On Linux, running the rm command only removes a file's directory entry, not its underlying data blocks. If a running process still holds an open file descriptor to that file, the operating system retains the data on disk until that reference is released. This means disk space is not reclaimed even after a file appears deleted, which can catch administrators off guard during storage emergencies. The lsof utility can identify which process is keeping a deleted file alive by listing open file descriptors marked as deleted. To reclaim space without restarting a service, administrators can truncate the file descriptor to zero bytes via the /proc filesystem or gracefully reload the offending process.

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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

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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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