I made a free log anonymizer in the browser
Hi HN, I'm the creator of LogLens. Like many of you, I spend a lot of time digging through massive structured (mostly JSON) log files. I've always relied on grep for its speed and then piped to jq for the actual filtering, but I find this workflow gets slow and complicated, especially with multi-GB files or complex queries. LogLens is my attempt to fix this. It's a single, fast CLI tool written in Rust that's designed specifically for structured logs. It combines a simple SQL-like query language (e.g., loglens query './logs' 'level == "error" && status >= 500') with parallel,…
I made a free log anonymizer in the browser launched on November 29, 2025 with 6 votes, #2,995 of 9,796 launches that month and more than 75% of that year's launches.
What it does
Safely remove PII (IPs, Emails, Secrets) from your logs. Client-side only log anonymizer. Your data never leaves your browser.
Safely scrub PII (IPs, Emails, Tokens) from your logs before sharing them in Jira, Slack, or GitHub Issues. LogLens Pro runs locally on your machine, so you never have to copy-paste dirty logs into a browser to clean them. Automate sanitization in your CI/CDfrom getloglens.com
In the maker’s words, at launch
Hi HN, I'm the creator of LogLens. Like many of you, I spend a lot of time digging through massive structured (mostly JSON) log files. I've always relied on grep for its speed and then piped to jq for the actual filtering, but I find this workflow gets slow and complicated, especially with multi-GB files or complex…
Does a similar job
all alternatives →
Local Privacy Firewall-blocks PII and secrets before ChatGPT sees themDec 2025 · github.com · ▲111OP here. I built this because I recently caught myself almost pasting a block of logs containing AWS keys into Claude. The Problem: I need the reasoning capabilities of cloud models (GPT/Claude/Gemini), but I can't trust myself not to accidentally leak PII or secrets. The Solution: A Chrome extension that acts as a local middleware. It intercepts the prompt and runs a local BERT model (via a Python FastAPI backend) to scrub names, emails, and keys before the request leaves the browser. A few notes up front (to set expectations clearly): Everything runs 100% locally. Regex detection…
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Jlq – A CLI to easily tail+query JSON log files using Rust+SQLite2023 · github.com · ▲10Hi all! It's been a while since I posted something. Wrote this back in November to scratch an itch regarding tailing logs locally for multiple services. I know we all love jq...but I'm quite comfortable with SQLite and SQL so just wanted to use that instead. Published my first Rust crate today! My first public Rust project so be gentle :) . Hope you enjoy it! https://crates.io/crates/jlq https://github.com/hamin/jlq
Rust based AWS Lambda Logs Viewer (TUI)2024 · github.com · ▲57My first Rust program with support from Cursor :)). few days for idea. 1 night for "talk and fight" with Cursor
prettylog.netJan 2026 · prettylog.net · ▲22Hey HN, I often check raw logs - out/error.log, nginx's access.log, etc, but they're hard to read So I built beautiful parser & formatter with filtering and syntax highlighting PrettyLog supports many common log formats out of the box: - nginx access logs - Apache error logs - Syslog (RFC 5424) - Logfmt (Heroku/Go style) - Docker logs - standard/node.js logs - Spring Boot logs - AWS VPC Flow logs - Kubernetes kubectl get events If you need something specific, you can use custom regex parser. Processing is 100% local. Your data never leaves the browser. I hope you find it as…
A Mutating Webhook to automatically strip PII from K8s logsMay 2026 · github.com · ▲25What PII-Shield does: It's a K8s sidecar (or CLI tool) that pipes application logs, detects secrets using Shannon entropy (catching unknown keys like "sk-live-..." without predefined patterns), and redacts them deterministically using HMAC. Why deterministic? So that "pass123" always hashes to the same "[HIDDEN:a1b2c]", allowing QA/Devs to correlate errors without seeing the raw data. Key features: 1. JSON Integrity: It parses JSON, sanitizes values, and rebuilds it. It guarantees valid JSON output for your SIEM (ELK/Datadog). 2. Entropy Detection: Uses context-aware entropy…
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