SShortSingh.
Back to feed

1,897,463 MongoDB services: how unauthenticated data stores became routine

0
·1 views

1,897,463 MongoDB services: how unauthenticated data stores became routine The problem MongoDB and Redis share a pattern: both were designed to run inside a trusted network, both became a common backend for quickly written applications, and both continue to appear at scale in exposure data. When authentication is optional in practice, it is often absent in production. On 2026-09-30 (UTC) we queried ZoomEye for the MongoDB service fingerprint: Query: service="mongodb" Scope: all asset types, global Matching assets: 1,897,463 Search link: https://www.zoomeye.ai/searchResult?q=c2VydmljZT0ibW9uZ29

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Log in to join the discussion and vote.

Log in

Related stories

0
ProgrammingDEV Community ·

Poverty Inspired Me to Fix a 'Wine Can't Do This' Timeout

A wise man once said, “if the young man is hungry, he should go to the forest and hunt the elephant. If he kills the elephant, the hunger ends, and if the elephant kills him, the hunger ends.” My Monday poverty motivation led me to brave the waters of quantitative trading using algorithmic bots. As a Nigerian, familiar with unsteady power supply, I asked early: “how can I achieve 100% runtime even if I don’t get light for a week?” The answer led me to a VPS (Virtual Private Server). Ladies and gentlemen, tell me why the cheapest monthly subscription for a Windows OS is $50. My entire trading e

0
ProgrammingDEV Community ·

React Native OTA Is a Release Pipeline, Not a Download Feature

“Download a new JavaScript bundle and run it” describes transport. It does not describe a production release system. A real React Native OTA implementation has to preserve compatibility with installed binaries, identify immutable artifacts, decide which release each device should receive, verify downloads, control activation, observe adoption, and recover when an update fails. Those are separate boundaries. Treating them as one download call is how a convenient feature becomes an operational risk.

0
ProgrammingDEV Community ·

Native Quantization: Let OpenSearch Service Compress Your Vectors

Send FP32, get 2x to 32x compression, and leave your ingestion pipeline untouched. The engine does the work. The previous article in this series put the quantization work on you. You convert vectors to a reduced precision before indexing, and Amazon OpenSearch Service stores exactly what you send. That gives you full control, and it gives you a standing job: pick a method, run the conversion in your pipeline, and re-check accuracy every time your embedding model changes.