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Archivo del Autor: Belen De Leon

Alienware Area-51m review

The Alienware Area-51m is a massive gaming laptop that paves a new path forward for the brand. While it offers many old-school features, it also brings a new look and design philosophy that gamers will love.

The post Alienware Area-51m review appeared first on Digital Trends.


Source: Digital trends

2020 Ford Escape gets streamlined look, two hybrid options – Roadshow

This softer, more modern crossover and a future “Baby Bronco” SUV are Ford’s way of combatting “the dreaded C Word.”
Source: CNET

Densify announces new tool to optimize container management in the cloud

Densify, a Toronto company that helps customers optimize their cloud resources to control usage and spending, announced a new tool today specifically designed to optimize container usage in the cloud.

Company CEO Gerry Smith, says that as containerization proliferates, it’s getting more difficult to track and control cloud infrastructure resource usage as software development and deployment happens with increasing speed.

“The whole basis upon which people buy and use cloud and container resources has become wildly expensive because of the lack of a resource management system,” Smith said.

The Densify solution looks at the consumption and for ways to cut costs and usage. “We have analytics in the cloud, any of various common cloud services that you can connect to, and then we use machine learning to analyze the resources and your cloud and container consumption,” he said.

Densify continuously make recommendations on how to make better use of resources and to find the cheapest computing, whether that’s reserved instances, spot instances or other discounted cloud resources.

What’s more, it can help you identify whether you are providing too few resources to accommodate the number of containers you are deploying, as well as too many.

This may sound a bit like what Spotinst and Cloudyn, the company Microsoft bought a couple of years ago, do in terms of helping control costs in the cloud, but Smith says, for his company it’s more about understanding the resources than pure cost.

“We look at ourselves as a resource management platform. So what we do is characterize the applications, demands of CPU and all the other resources, and use machine learning to predict what it’s going to need at any any given minute, at any given day of a week of the year, so that we can then better predictively match the right supply,” Smith explained.

It’s providing information about each container at a highly detailed level including “what’s running, what resources are being allocated, and the true utilization of an organization’s Kubernetes environment at a cluster, namespace and container level,” according to the company. All of this information should help DevOps teams better understand the resources required by their container deployments.

The company has actually been around since 2006 under the name Cirba. In its early guise it helped companies manage VMware installations. In 2016, it pivoted to cloud resource management and changed the company name to Densify. It has raised around $60 million since inception, with about half of that coming after the company changed to Densify in 2016.

The company is based in Toronto, but has offices in London and Melbourne as well


Source: TechCrunch

See Game of Thrones intro reenacted with 2,750 Oreo cookies – CNET

It’s a Song of Creme and Chocolate.
Source: CNET

Audi teases sharp AI:me design study for Shanghai Motor Show – Roadshow

Audi’s wild design studies all have “AI” somewhere in the name, because it’s the future, duh.
Source: CNET

2020 Ford Escape is a citified slicker SUV video – Roadshow

The Blue Oval’s popular SUV is reborn with sleek new styling, plus key new cabin and engine tech.
Source: CNET

Lego's newest Spike Prime programmable robots aim for the classroom – CNET

Here’s how it’s different from Lego Mindstorms.
Source: CNET

Alcatraz AI is building Face ID for corporate badges

Meet Alcatraz AI a startup that wants to replace all the bade readers in your office with a Face ID-like camera system. Alcatraz has integrated multiple sensors to identify faces and unlock doors effortlessly.

If you think about it, it’s weird that fingerprint sensors took off on mobile but everybody is still using plastic badges for their offices. Sure, high security buildings use fingerprint and iris scanners. But it adds too much friction in too many cases.

First, when everybody gets back from their lunch break, it can create a traffic jam if everybody needs to place their finger on a sensor. Second, onboarding new employees would require you to add their biometric information to the system. It can be cumbersome for big companies.

Alcatraz AI promises a faster badging experience with facial authentication. When you join a company, you also get a physical badge. The first few times you use the badge, Alcatraz AI scans your face to create a model for future uses — after a while, you can leave your badge at the office.

The company has built custom hardware with three different sensors that include both traditional RGB sensors and infrared sensors for 3D mapping. Customers pay Alcatraz AI to install those hybrid badge/face readers. After that, companies pay an annual fee in order to use the platform.

Alcatraz AI customers get analytics, real-time notifications and can detect tailgating. This way, if somebody isn’t supposed to go in the secret lab, Alcatraz AI can detect if they’re trying to sneak in by following someone who is authorized to go in there.

The idea is that the on-going license cost should cover what your company was paying for guards. The startup has raised nearly $6 million from Hardware Club, Ray Stata, JCI Ventures, Ruvento Ventures and Hemi Ventures.


Source: TechCrunch

We found a massive spam operation — and sunk its server

For ten days in March, millions were caught in the same massive spam campaign.

Each email looked like it came from someone the recipient knew: the spammer took stolen email addresses and passwords, quietly logged into their email account, scraped their recently sent emails and pushed out personalized emails to the recipient of that sent email with a link to a fake site pushing a weight loss pill or a bitcoin scam.

The emails were so convincing more than 100,000 people clicked through.

We know this because a security researcher found the server leaking the entire operation. The spammer had forgotten to set a password.

Security researcher Bob Diachenko found the leaking data and with help from TechCrunch analyzed the server. At the time of the discovery, the spammer’s rig was no longer running. It had done its job, and the spammer had likely moved onto another server — likely in an effort to avoid getting blacklisted by anti-spam providers. But the server was primed to start spamming again.

Given there were more than three million unique exposed credentials sitting on this spammer’s server, we wanted to secure the data as soon as possible. With no contact information for the spammer — surprise, surprise — we asked the hosting provider, Awknet, to pull the server offline. Within a few hours of making contact, the provider nullrouted the server, forcing all its network traffic into a sinkhole.

TechCrunch provided a copy of the database to Troy Hunt. Anyone can now check breach notification site Have I Been Pwned to see if their email was misused.

But the dormant server — while it was still active — offered a rare opportunity to understand how a spam operation works.

The one thing we didn’t have was the spam email itself. We reached out to dozens of people to ask about the email they received. Two replied — but only one still had a copy of the email.

The email sent by the spammer. (Image: supplied)

“The same mail appeared on three occasions,” said one of the recipients in an email to TechCrunch. “The subject was related to an email I had sent previously to that person so the attacker had clearly got access to his mailbox or the mail server,” the victim said.

The email, when clicked, would direct the recipient through several websites in quick succession to determine where they were located, based off their IP address. If the recipient was in the U.S., they’d be pushed to a fake CNN site promoting a bogus health remedy. In this case, the spammer was targeting U.K. residents — and most were directed to a fake BBC page promoting a bitcoin scam.

One of the fake page.s (Screenshot: TechCrunch)

The spammer had other servers that we had no visibility into, but the exposed server revealed many of the cogs and machinery to the operation. The server, running an Elasticsearch database, was well-documented enough that we found one of the three spam emails sent to our recipient.

This entry alone tells us a lot about how the spam operation worked.

A database record of one email sent by the spammer. (Screenshot: TechCrunch)

Here’s how it works. The spammer logs into a victim’s @btinternet.com email account using their stolen email address and password. The scammer pulls a recently sent email from their victim’s email server, which feeds into another server — like inbox87.host and viewmsgcs.live — tasked with generating the personalized spam email. That email incorporates the subject line of the sent email and the target recipient’s email address to make it look like it’s being sent from the real person.

Once the message is ready to send, it’s pushed through a proxy connection, designed to mask where the email has come from. The proxy server is made up of several cell phones, each connecting to the internet over their cellular connection.

Each spam message is routed through one of the phones, which occasionally rotates its IP address to prevent detection or being flagged as a spammer.

Here’s what that proxy server looks like.

The proxy server comprised of several cell phones with rotating IP addresses. (Screenshot: TechCrunch)

Once the spam message leaves the proxy server, the spam message is pushed through the victim’s own email provider using their email address and password, making it look like a genuine email to both the email provider and the recipient.

Now imagine that hundreds of times a second.

Not only was the spammer’s Elasticsearch database leaking, its Kibana user interface was also exposed. That gave the spammer a detailed at-a-glance look at the operation in action. It was so granular that you could see which spam-sending domains were the most efficient in tricking a recipient into clicking the link in the spam email.

The spammer’s Kibana dashboard, displaying the operation at a glance. (Screenshot: TechCrunch)

Each spam email includes a tracker in the link that fed information back to the spammer. In bulk, that allows the spammer to figure out which email domain — like outlook.com or yahoo.com users — is more likely to click on a spam email. That can also indicate how an email provider’s spam filter acts. The greater number of clicks, the more likelihood of its spam going through — allowing the spammer to target specific email domains in the future.

The dashboard also contained other information related to the spam campaign, such as how many emails were successfully sent and how many bounced. That helps the spammer home in on the most valuable logins in the future, allowing them to send more spam for lower bandwidth and server costs.

In all, some 5.1 million emails were sent during the 10-day campaign — between March 8 and March 18, with some 162,980 people clicking on the spam email, according to the data on the dashboard.

It’s not the first time we’ve seen a spam operation in action, but it’s rare to see how successful it is.

“This case reminds me on several other occasions I reported at some points in the past — when malicious actors create a sophisticated system of proxying and logging, leaving so much tracks to identify their patterns for authorities in the investigations to come,” Diachenko told TechCrunch. “This shows us — again! — how important a proper cyber hygiene should be.”

What’s clear is that the spammer knows how to cover their tracks.

The language settings in the Kibana instance suggested the spammer may be based in Belgium. We found several other associated spamming domains using data collected by RiskIQ, a cyberthreat intelligence firm, which scours the web for information. Of the domains we found, all were registered with fake names and addresses.

As for the server itself, the provider said it was possibly hacked.

“This was a resold box and the customer already responded to the abuse forward saying it was supposed to have been terminated long ago,” said Awknet’s Justin Robertson in an email to TechCrunch.

Since the hosting provider pulled the spammer’s server offline, several of their fake sites and domains associated with the spam campaign no longer load.

But given the spread of domains and servers propping up the campaign, we suspect the sunken server is only a single casualty in an otherwise ongoing spam campaign.


Got a tip? You can send tips securely over Signal and WhatsApp to +1 646-755–8849. You can also send PGP email with the fingerprint: 4D0E 92F2 E36A EC51 DAAE 5D97 CB8C 15FA EB6C EEA5.


Source: TechCrunch

Search giant Baidu has driven the most autonomous miles in Beijing

While the public is asking, “When are we going to ride in autonomous cars?” Technology companies have been moving apace to test them on designated roads. In China’s capital city Beijing, eight firms drove a total of 153,600 kilometers (95442.6 miles) through their autonomous fleets in 2018, and Baidu, the country’s largest search engine service seen as a local answer to Google, has built a big lead.

That’s according to new data released by Beijing’s transportation regulators in their first report on the city’s licensed self-driving cars. While the authority did not specify conditions of the road tests, say, the number of instances when a human driver had to intervene to prevent an accident, namely the level of “disengagement” that California’s counterpart report asked for, Beijing’s data offers the public an early glimpse into a fledgling field.

Baidu registered nearly 140,000 kilometers in Beijing last year, representing about 91 percent of total self-driving distances traveled by the eight licensed transportation companies in the city. The firm’s leading position is closely linked to its pledge to go all out for artificial intelligence. When it comes to AI’s application in mobility, Baidu stays clear of making hardware and runs an open platform called Apollo that lets third-party developers tap its autonomous tech.

Apollo has joined hands with 135 car manufacturers, parts suppliers and other car allies at last count. Its partners range from international automakers Volvo and Ford, to local electric vehicle startups Byton and Nasdaq-listed NIO.

Baidu was also the first to nab a batch of L3 licenses to trial self-driving cars in Beijing, where Baidu is headquartered and is the country’s first city to allow such road tests. Robocars are now testing in more than ten Chinese cities, including first-tier Beijing and Shanghai as well as smaller urban centers like Changsha, where Baidu is working with the municipal government to bring 100 automated cabs to the city by end of this year.



The runner-up on Beijing’s road-test list, Pony.ai, lagged behind Baidu by a large margin at 10132.9 kilometers. But the three-year-old company has attracted large sums of investor money, in part thanks to the resume of co-founder James Peng, who was the former chief architect of Baidu’s autonomous driving unit. The southern China-based startup counts Sequoia Capital China as one of its seed investors and nearly reached $1 billion in valuation after raising $102 million in funding last July.

Other self-driving companies testing in Beijing included social and gaming giant Tencent, ride-hailing platform Didi Chuxing, and carmakers NIO, Audi AG, Daimler AG and Beijing’s state-owned BAIC Group. Didi, which made safety a priority across company divisions following two passenger murders last year, ran the least self-driving miles in Beijing last year but the company holds great potential to unlock mountains of car-hailing data that could help autonomous vehicles predict road conditions.

Notably missing from the list is Roadstar.ai, a self-driving startup that once rivaled Pony.ai and secured a record $128 million Series A round less than a year ago. Chinese tech news blog Liangziwei reported this week that shareholders are asking to dissolve and liquidate the Shenzhen and Silicon Valley-based firm following months of infighting among its senior executives.

Also unmentioned is Huawei, a potentially formidable player in autonomous driving. The telecom equipment maker’s foray into self-driving predates many other familiar names. Back in 2016, Huawei was among a group of tech firms and carmakers to form the Global Cross-industry 5G Automotive Association aimed at developing communications technology and commercial solutions for automated driving. Members of the alliance included Audi, BMW, Daimler, Ericsson, Intel, Nokia and Qualcomm. More recently, Huawei’s partnership with Audi brought more light to its ambition in autonomous tech, as it provided chipsets to power Audi’s L4 (which is more autonomous than L3) self-driving sedans.


Source: TechCrunch

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