Why wouldn’t Reader’s Digest remove malware from its website?

For nigh on a week, the internet hollered at Reader’s Digest to remove malware from its website, to no apparent response . The attack consists of a malicious script injected within compromised WordPress sites that launches another URL whose final purpose is to load the Angler exploit kit. Site owners that have been affected should keep in mind that those injected scripts/URLs will vary over time, although they are all using the same pattern (see IOCs below for some examples). The website of popular magazine Reader’s Digest is one of the victims of this campaign and people who have visited the portal recently should make sure they have not been infected. The payload we observed at the time of capture was Bedep which loaded Necurs a backdoor Trojan, but that of course can change from day to day. Dan Goodin got exasperated: Hey Reader’s Digest: Your site has been attacking visitors for days . Reader’s Digest has been infected since last week with code originating with Angler, an off-the-shelf hack-by-numbers exploit kit that saves professional criminals the hassle of developing their own attack scripts, researchers from antivirus provider Malwarebytes told Ars. People who visit the site with outdated versions of Adobe Flash, Internet Explorer, and other browsing software are silently infected with malware that gains control over their computers. Malwarebytes researchers said they sent Reader’s Digest operators e-mails and social media alerts last week warning the site was infected but never got a response. The researchers estimate that thousands of other sites have been similarly attacked in recent weeks and that the number continues to grow. 1. If you would like an ill-informed passive-aggressive quip, go to 2 . If you would like earnest outrage, go to 3 . If you would like to hear the voice of reason that really isn’t, go to 4 . 2. What give$, Readers Digest? 3. They’re probably being paid to do it, isn’t that disgusting? 4. Guys, it’s Readers’ Digest. They’re all 120 years old and have no idea what a website is or why they have one.

View original post here:
Why wouldn’t Reader’s Digest remove malware from its website?

An Army colonel is in trouble for complaining that a $500k gas station cost $43 million to build

Army Col. John Hope blew the whistle on a task force that spent $43 million to build a useless gas station in Afghanistan. The Special Inspector General for Afghanistan Reconstruction says the useless gas station should have cost about $500,000. As a result of pointing out the doubly wasteful project, Hope has “been singled out for retaliation and retribution” for “speaking truth,” said Sen. Chuck Grassley (R-Iowa) in a letter to Defense Secretary Ashton Carter. The gas station is useless because it supplies natural gas to cars that have been converted to run on natural gas. But there are hardly any cars that run on natural gas in Afghanistan, and the cost to convert a car to run on natural gas is $700. The average annual income in Afghanistan is $690, according to the Washington Post . More from the Washington Post : The high cost of the gas station has angered many in Congress. Sen. Kelly Ayotte (R-N.H.) has scheduled a hearing on it for next month. And Sen. Claire McCaskill (D-Mo.) said it was one of the worst cases of wasteful spending that she has ever seen. “There are few things in this job that literally make my jaw drop,” she said in a statement. “But of all the examples of wasteful projects in Iraq and Afghanistan that the Pentagon began prior to our wartime contracting reforms, this genuinely shocked me.” The contractor, Central Asian Engineering Construction Company, originally bid $3 million to build the gas station, which is already an order of magnitude too much to charge. How they ended up charging $43 million is a mystery. I wonder who owns Central Asian Engineering Construction Company?

Read the original:
An Army colonel is in trouble for complaining that a $500k gas station cost $43 million to build

277 bodies found under UK tram line

Experts knew there was a graveyard under Manchester’s Metrolink tramline, but the sheer scale of the excavation— 277 unearthed bodies —has made news worldwide. The archeological dig is a prelude to development work to Manchester’s transit system, and covers generations of burials in England’s third-largest city . Church officials say they are pleased with the sensitivity shown by the project, and that the remains will be relocated. Even so, the bone haul is nothing on the 3,000-corpse plague pit excavated during similar work in London earlier this year.

More:
277 bodies found under UK tram line

Massive hack of 70 million prisoner phone calls may be biggest attorney-client privilege breach in U.S. history

A big story out today confirms that SecureDrop, the anonymizing whistleblower leak service created by Aaron Swartz and made real by Freedom of the Press Foundation, works. (more…)

View the original here:
Massive hack of 70 million prisoner phone calls may be biggest attorney-client privilege breach in U.S. history

Magic cards generated by neural networks

@RoboRosewater is a twitter account that posts, once a day, a Magic: The Gathering card generated by a recurrent neural network. [via Ditto ] This is an implementation of the science described by Vice’s Brian Merchant in this article . Reed Morgan Milewicz, a programmer and computer science researcher, may be the first person to teach an AI to do Magic, literally. Milewicz wowed a popular online MTG forum—as well as hacker forums like Y Combinator’s Hacker News and Reddit—when he posted the results of an experiment to “teach” a weak AI to auto-generate Magic cards. He shared a number of the bizarre “cards” his program had come up with, replete with their properly fantastical names (“Shring the Artist,” “Mided Hied Parira’s Scepter”) and freshly invented abilities (“fuseback”). Players devoured the results. Here’s the code , and here’s a simple text-only generator . Magic: The Gathering is Turing-complete .

View original post here:
Magic cards generated by neural networks