Skip to main content
  1. Home
  2. Computing
  3. Web
  4. Legacy Archives

Spanish Police Bust Mariposa Botnet Bosses

Add as a preferred source on Google
Image used with permission by copyright holder

Authorities in Spain have arrested three men they suspect were the masterminds and herders behind the Mariposa botnet, a worm that infected more than 13 million PCs around the world and attempted to steal credit card numbers and other personal information. The botnet was largely shut down in December of 2009 after an investigation by the FBI and Spanish Civil Guard found a way to separate the network from its command-and-control servers. Authorities managed to arrest one botnet-runner when he attempted to log into the network without obfuscating his network address; two other suspects were subsequently identified and arrested.

Authorities haven’t released the names of the suspects, but say all are Spanish citizens and none of them have criminal records. They’re also described as having limited technical knowledge: the Mariposa botnet isn’t something they developed themselves, but rather malware from other sources that the individuals leveraged to steal personal information such as passwords, usernames, credit card information. Mariposa particularly focused on social networking sites and online email services. The botnet runners earned money by selling stolen credentials, but also by renting out the Mariposa botnet to other cybercriminals. The Spanish Civil Guard says more arrests may be forthcoming.

Recommended Videos

One of the suspects arrested was found to have some 800,000 pieces of personal data on his machine; the Mariposa botnet infected PCs are more than half of Fortune 1000 companies and at least 40 banks.

Geoff Duncan
Former Contributor
Geoff Duncan writes, programs, edits, plays music, and delights in making software misbehave. He's probably the only member…
Topics
AI image generators have escaped nightmare fingers and entered the fake premium era
Meta Muse, Gemini, and ChatGPT can now make clean, usable images. They also keep making reality look like a product render with feelings.
Terminal, Railway, Train

I expected this comparison to be uglier. Meta Muse, Gemini Nano Banana 2, and ChatGPT Images 2.0 sounded like a perfect setup for plastic faces, mangled hands, fake products, and posters written in haunted alphabet soup. Instead, they were mostly competent, which somehow made the whole thing more suspicious.

These aren’t identical tools wearing different logos. Meta pitches Muse Image as a social image model living inside Meta AI and its apps. Google frames Nano Banana 2 around speed, editing, and Gemini’s broader knowledge. OpenAI sells ChatGPT Images 2.0 on text rendering, visual control, and stronger prompt handling. Different ambitions, same polished little showroom.

Read more
DuckDuckGo’s browser now blocks the YouTube ads everyone hates
DuckDuckGo adds a Brave-like YouTube ad blocking feature
Text, Aircraft, Airplane

DuckDuckGo has spent the past few months gaining fresh attention as more users look for alternatives to Google’s increasingly AI-heavy Search experience. Now, the privacy-focused company is adding a feature that could make its browser even more tempting for everyday use. DuckDuckGo says its browser can now block most video ads, including those on YouTube, when a video is playing inside the browser.

What’s happening?

Read more
ChatGPT Live could make talking to AI feel straight out of the movies
We might finally get the AI sidekick sci-fi movies promised
Elderly women using ChatGPT live on a smartphone

AI voice assistants have been chasing the sci-fi dream for years, but they still have a hard time holding a conversation with humans. Most voice systems still need clear turns, clean pauses, and a few seconds before they respond. OpenAI is now rolling out GPT-Live, a new voice model for ChatGPT Voice that is designed to make those exchanges feel faster and less scripted.

The main upgrade is what OpenAI calls a full-duplex architecture. In simpler terms, GPT-Live can listen and speak at the same time. It continuously processes what the user is saying while also generating its own response, allowing it to decide when to talk, when to pause, when to keep listening, and when to use a tool.

Read more