Category Archives: passwords

EU calls for End to Default Passwords on Internet of Things

A group representing European telecommunications firms last week published technical specifications for securing a wide range of consumer Internet of Things devices including toys, smart cameras and wearable health trackers.

The post EU calls for End to Default Passwords on Internet of Things appeared first on The Security Ledger.

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The Details of Roughly 620 Million Users Are Up for Sale on The Dark Web

Approximately 620 million records stolen from sixteen compromised websites are up for grabs on the Dark Web. According to The Register, the list includes users of the following companies; Dubsmash, MyFitnessPal, MyHeritage, ShareThis, HauteLook, Animoto, EyeEm, 8fit, Whitepages, Fotolog, 500px, Armor Games, BookMate, CoffeeMeetsBagel, Artsy, and DataCamp.

While some of the affected companies such as MyHeritage and MyFitnessPal have already announced that they were hacked last year, the list consists predominantly of newcomers who have just begun notifying their users about the breach. Some of the newcomers include 500px, DataCamp, EyeEm, and 8fit.

The massive database of stolen information is being offered on the Dream Market cyber-souk located in the Tor network for roughly $20,000 in Bitcoin, and according to The Register’s source, the database has been purchased at least once already. However, it is currently unknown how many cybercriminals have bought the list so far.
The database contains personal information such as full names, email addresses, passwords, and other data such as location, and social media authentication tokens. It is currently unknown if the list contains sensitive information such as SSN, DOB, and credit card details. It is assumed that most of the leaks included in the database come from data breaches that have happened over the last two years.

A MyHeritage spokesperson provided with the sample of the list confirmed that the information included in the list is legitimate and contains information illegally obtained from the organization a couple of years ago. EyeEm and 500px have already begun notifying the affected customers forcing them to change their passwords. The majority of the affected companies are still not actively working on forcing password change to the affected users.

This major collection of multiple data breaches is not to be mistaken with the 2.2 billion monster data collection that started circulating the Dark Web and various torrent websites a couple of weeks ago. It is currently unknown if the stolen data is part of the 2.2 billion monster data collection. It is also unknown if the details from the stolen data have been uploaded to Have I Been Pwned.

What should you do?

Hackers will most likely start using the stolen data to get access to other websites where the same login details have been reused. Such leaks make the life of hackers much more comfortable as they can use simple hacking techniques to get access to even more sensitive information for their targets.

The very first thing that you will have to do is to start practicing good password hygiene by changing your passwords regularity – often it takes years for a company to disclose that it has been breached. Changing your password at least once every three months is indeed a good practice.

Don’t be tempted to reuse passwords on different websites. If you are too confused to remember all passwords, it is worth using antivirus software – the best antivirus software solutions not only protect you from hackers but also come with useful features such as password managers.

Download your Antivirus

The post The Details of Roughly 620 Million Users Are Up for Sale on The Dark Web appeared first on Panda Security Mediacenter.

The Race to the Bottom of Credential Stuffing Lists; Collections #2 Through #5 (and More)

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The Race to the Bottom of Credential Stuffing Lists; Collections #2 Through #5 (and More)

A race to the bottom is a market condition in which there is a surplus of a commodity relative to the demand for it. Often the term is used to describe labour conditions (workers versus jobs), and in simple supply and demand terms, once there's so much of something all vying for the attention of those consuming it, the value of it plummets.

On reflecting over the last 3 and a half weeks, this is where we seem to be with credential stuffing lists today and I want to use this blog post to explain the thinking whilst also addressing specific questions I've had regarding Collections #2 through #5.

The 773 Million Record "Collection #1" Data Breach

On Thursday 17 Jan, I loaded 773M records into Have I Been Pwned (HIBP) which I titled "Collection #1". I explained how this data originated from multiple different sources and was likely obtained over a period of many years before being amalgamated together and passed around as one massive stash. There were 2.7B rows of email addresses and passwords in total, but only 1.6B them were unique (my own identical record appeared half a dozen times). In other words, there was a huge amount of redundancy.

I made the call to load the data into HIBP based primarily on 3 facts:

  1. The data was sufficiently unique: more than 18% of the email addresses had not been seen in HIBP before
  2. The data was in broad circulation: multiple parties had contacted me and passed on Collection #1
  3. There was a large number of previously unseen passwords: of the 21M unique ones, half of them weren't already in HIBP's Pwned Passwords

Being conscious that there would be many questions about this data and that the origins and impact of it could be easily misrepresented, I carefully detailed every important fact. I pushed the blog post out on that Thursday morning my time and later that day, hopped on a plane to Europe. As the rest of world woke up to the story, all hell broke loose. I have never, ever received so many emails, tweets, blog comments and every other form of communication you can imagine in such a short period of time. I'd also never seen so much traffic on HIBP:

I spent a significant part of the flight chewing through Emirates' bandwidth just responding to messages. I landed in Oslo, met friends and drove up into the mountains for a snowboarding trip with the flood of communications continuing. Jet lagged, overwhelmed by it all and frankly, just wanting downtime with good company, I turned on the out of office, closed comments on the blog post and almost completely stopped engaging on Twitter. (Side note: Scott Helme and I talked about burnout in my weekly update from London, in part due to the experiences I had dealing with the above.)

If I'm honest, that experience with the flood of communication coupled with disconnecting from life for a few days in a remote cabin with friends had a profound effect on me in many ways. I'm sure I'll talk more about them in future, but one was that I've very consciously reduced my engagement on email and Twitter frankly, to save my sanity. That's a bit tangential here though, back to Collection #1.

I'm frustrated about the hyperbole this incident managed to attract. The mass media picked it up with gusto and it made headlines all around the world in the most mainstream of publications. Inevitably, whether deliberately for the headlines or accidentally because it's simply not the world they live in, the truth was stretched time and time again. Despite my best efforts to report everything I knew with candour, things got out of control. For the most part I ignored this, only occasionally venting my frustration as someone brought it to the fore:

Of course, there was nothing missing from the post and each time I asked the question it was met with silence. (Incidentally, Lorenzo who wrote that Motherboard piece is a top-notch infosec journo I've worked with many times before and he reported accurately in that piece.) I'm sharing this because I want to ensure that those who expressed their dismay at the way this story unfolded understand that it bugged the hell out of me too.

But I will say this: because this incident reached an unprecedented number of people and gained such worldwide traction, the impact of it on normal, everyday people's behaviour was significant. They learned about the phenomenon that is data breaches and credential stuffing lists, they read about password managers and 2FA and inevitably, many of them subsequently made behavioural changes to their security practices. Over-inflated headlines or not, the outcome of this on everyday consumers was positive.

The Other Collections

When I was originally contacted about Collection #1, that was the extent I knew of this series - that there was 1 collection. But very quickly it became apparent that it was merely the first of 5 collections and it was far from the biggest. Collection #1 was 87GB of data but collections #2 through #5 totalled another 845GB on top of that. Instead of the 2.7B rows from the Collection #1, the headlines were now talking about 25B which, admittedly, is quite the catchy title. Dozens of people reached out to me with links to the additional data and indeed, the media lapped up news of the larger collections as well. Inevitably, I got bombarded with questions about the subsequent collections:

The Race to the Bottom of Credential Stuffing Lists; Collections #2 Through #5 (and More)

Keeping in mind my previous comments about overwhelming amounts of communication and workload, the thought of processing a 10x volume of data over Collection #1 wasn't exactly exciting me. Nevertheless, I grabbed the additional collections whilst travelling, flew home just over a week ago and began analysis. Before doing that, I had a working theory that the subsequent collections would be more of the same, but I wanted hard numbers on it so I began running the data against the existing 6.5B records in HIBP.

Spam, Spam, Spam Everywhere

Back when I originally began looking at Collection #1, one of the first things I did was to run a sample selection of email addresses against HIBP to get a sense of how many of them were unique. As mentioned earlier, it turned out to be just over 18% which was quite significant for such a large list. The very first thing I did with collections #2 through #5 was to choose slices of the data and check them against HIBP. This meant choosing a random file from amongst the 85k+ in the data, extracting all the email addresses then grabbing a random 100 sample and looking for uniqueness. After checking hundreds of files, here's when I found:

Tested 457 files, 280 were a 100% match
Tested 44,426 addresses, found 5,282 unique ones not already in HIBP, only 11.89 % unique

For the sake of transparency, I've published the complete output of this process which shows just how much crossover there is with existing data. As you scroll through that list, you'll see that over 61% of the files tested were a 100% much to HIBP; every single one of those random 100 email addresses tested was already in there. (Sidenote: after running the report, I realised that some of the source files didn't contain email addresses and as such reported "Of 0 random email addresses, 0 are already in HIBP". That's fine, but it skewed the 61% number down as the file was counted as not being an exact match.)

Some of these were quite predictable:

Collection #5\Collection #5\Dump HASH\
Of 100 random email addresses, 100 are already in HIBP

There's an easy explanation for that:

Then there were files at the other end of the extreme:

Collection #5\Collection #5\EU combos\49.txt
Of 100 random email addresses, 1 are already in HIBP

Curious, I took a closer look and found 100k rows heavily orientated towards Eastern European TLDs; over 20k .ua (Ukraine), another 10k .uz (Uzbekistan), 5k .kz (Kazakhstan) etc. I have no idea how many of these are actual addresses nor which breaches they originated from if they're indeed genuine, obviously there's nothing given away by the file name. The problem with all of this data (as with Collection #1), is that it's just about impossible to establish authenticity and a bunch of it is very likely not what it's represented to be.

Here's a perfect example: when running the check, one of the very first results I saw was this one:

The Race to the Bottom of Credential Stuffing Lists; Collections #2 Through #5 (and More)

It piqued my interest as it's an Aussie TLD for a site I'd never heard of yet apparently, 100% of the email addresses are already in HIBP. So I delved into the file and was immediately struck by the occurrence of a different TLD which, upon counting its occurrences across the 436-line file, showed a strangely high hit rate:

The Race to the Bottom of Credential Stuffing Lists; Collections #2 Through #5 (and More)

The file itself was then a combination of email addresses and SHA-1 hashes along with email addresses and then simply the number 1 after it. This is unusual as not only is there no consistency to the format, but it's also clearly compromised of different types of information.

During the course of the last week, I had a few chats with Vinny Troia of Night Lion Security. Vinny has supported HIBP in the past with data he's located floating around the web and we had a good discussion about the nature of these collections which he was also analysing. He also lamented the volume of garbage in them, pointing to examples such as this (the asterisks all represent the same 4-digit number):


Then there's my own data. I'd already found it in Collection #1 half a dozen times with an old throwaway password I had legitimately used many years ago. I noted it in the original blog post but didn't dig any further. This time, however, I probed deeper; I wanted context for the data.

Here it is in "Collection #2\Collection #2\DUMPS dehashed\"

The Race to the Bottom of Credential Stuffing Lists; Collections #2 Through #5 (and More)

I had to look up in order to work out what it was. Turns out it's a Vietnamese e-commerce site selling phones so yeah, not exactly the sort of place I'd frequent.

And here it is in "Collection #5\DUMP dehashed\  add pass.txt":

The Race to the Bottom of Credential Stuffing Lists; Collections #2 Through #5 (and More)

No, I've not screwed up the image, the file it's in is identical to the Vietnamese phone one. The password is identical too and firstly, under no circumstances did I ever use that password on Dropbox and secondly, the password I had in the Dropbox breach was randomly generated and exposed as a bcrypt hash I shared publicly when reporting on the breach.

So you see my point about "spam, spam, spam" - these collections are absolutely riddled with junk. That's not to say they don't contain legitimate usernames and passwords because quite clearly, some of them are, rather that the actual unique legitimate entries across all the collections is a small subset of what the headlines suggest.

It's a Very Deep Bottom

Following the events above, I received dozens of messages (maybe even hundreds, I honestly lost track) about other collections of credentials. Not collections represented as being part of the same series (i.e. Collection #6), but rather entirely separate sets of data. A few thousand here from a phishing page, a few hundred thousand over there in a public Google Doc, untold numbers more in pastes that HIBP may not have already indexed. I've seen a lot of breached data over a lot of years but even for me, I was honestly left a bit stunned by all of this. It. Just. Never. Ends.

A couple of days ago there was a story going around about yet another collection of data that began as follows:

A massive 600 gigabyte file containing about 2.2 billion compromised usernames and passwords has been spotted floating about the dark web, freely available to anyone who cares to download it via torrent.

As I've lamented before, stories of the dark web are frequently exaggerated and the reality is that huge volumes of data like this are socialised much more broadly "on the clear web" than the headlines suggest. For example:

The Race to the Bottom of Credential Stuffing Lists; Collections #2 Through #5 (and More)

I could go on with literally dozens of similar examples; a billion credentials here, another few billion there, many freely circulating and others costing inconsequential amounts of money:

The Race to the Bottom of Credential Stuffing Lists; Collections #2 Through #5 (and More)

And every time you think you've seen how deep the iceberg goes, you realise it's just another tip floating around a sea of our personal data:

   /$$    /$$$$$$        /$$$$$$$  /$$$$$$ /$$       /$$       /$$$$$$  /$$$$$$  /$$   /$$
 /$$$$   /$$__  $$      | $$__  $$|_  $$_/| $$      | $$      |_  $$_/ /$$__  $$| $$$ | $$
|_  $$  |__/  \ $$      | $$  \ $$  | $$  | $$      | $$        | $$  | $$  \ $$| $$$$| $$
  | $$     /$$$$$/      | $$$$$$$   | $$  | $$      | $$        | $$  | $$  | $$| $$ $$ $$
  | $$    |___  $$      | $$__  $$  | $$  | $$      | $$        | $$  | $$  | $$| $$  $$$$
  | $$   /$$  \ $$      | $$  \ $$  | $$  | $$      | $$        | $$  | $$  | $$| $$\  $$$
 /$$$$$$|  $$$$$$/      | $$$$$$$/ /$$$$$$| $$$$$$$$| $$$$$$$$ /$$$$$$|  $$$$$$/| $$ \  $$
|______/ \______/       |_______/ |______/|________/|________/|______/ \______/ |__/  \__/
             /$$ /$$$$$$$$ /$$      /$$  /$$$$$$  /$$$$$$ /$$        /$$$$$$  /$$         
            /$$/| $$_____/| $$$    /$$$ /$$__  $$|_  $$_/| $$       /$$__  $$|  $$        
           /$$/ | $$      | $$$$  /$$$$| $$  \ $$  | $$  | $$      | $$  \__/ \  $$       
          /$$/  | $$$$$   | $$ $$/$$ $$| $$$$$$$$  | $$  | $$      |  $$$$$$   \  $$      
         /$$/   | $$__/   | $$  $$$| $$| $$__  $$  | $$  | $$       \____  $$   \  $$     
        /$$/    | $$      | $$\  $ | $$| $$  | $$  | $$  | $$       /$$  \ $$    \  $$    
       /$$/     | $$$$$$$$| $$ \/  | $$| $$  | $$ /$$$$$$| $$$$$$$$|  $$$$$$/     \  $$   
      |__/      |________/|__/     |__/|__/  |__/|______/|________/ \______/       \__/   

In case the ASCII art is lost on you, that's "13 BILLION /EMAILS\" in a readme file accompanied by an 88GB file containing that number of email and password pairs. It was about this time that the penny finally dropped in terms of just how comedic it was becoming to have numbers that seemed both artificially large and apparently there for shock value. It's like I'd seen this somewhere before...

The Race to the Bottom of Credential Stuffing Lists; Collections #2 Through #5 (and More)

All of this data in all of these locations has caused me to ask some pretty fundamental questions about the point of these lists as they relate to HIBP:

What's the point of loading billions after billions of email addresses from credential stuffing lists? What makes a new list worth adding to the 6.5B addresses already in HIBP? And if I'm going to be honest with myself, what's changed since I loaded Collection #1 that would cause me not to load subsequent lists?

The answer to the last question is a combination of the frenzy that first list created coupled with the emergence of untold numbers of other lists. What's changed is that there's way more data circulating than I've ever seen before and if I go loading all of that into HIBP, I fear the signal to noise ratio will go through the floor. Some people already felt that was the case with Collection #1 and whilst I still maintain loading that list was the right thing to do in the climate of the time, a constant stream of notifications about old incidents that have merely re-purposed the same data is quickly going to create a groundswell of unhappy subscribers.


Somehow, the Collection #1 incident turned into a feeding frenzy of media, breach traders, security firms and industry voices alike, all vying for a piece of the attention. Whilst there was undoubtedly value in the awareness it created, an increasing infatuation on which list is the largest or who's sitting on the largest stash of data is just downright counterproductive. It becomes a sideshow of superlative news headlines as the discussion turns to "who's is biggest" rather than "what should we actually be doing about this".

For now, I don't see subsequent lists like these going into HIBP unless there's something sufficiently unique about them. Users of the service have a pretty good idea by now where they've been exposed and what they should do about it, I want to keep focusing on the discrete incidents that are clearly attributable back to a source. Speaking of which:

Google Launches Password Checkup Extension To Detect Breached Credentials

Breached usernames and passwords have become a pain in the neck with regards to online security. Even if your account

Google Launches Password Checkup Extension To Detect Breached Credentials on Latest Hacking News.

Google’s new Chrome extension flags insecure passwords

As the number of compromised and leaked credentials rises inexorably with each passing day, Google has decided to help users choose safe combinations for all their online accounts. To that end, the company has released a new Chrome extension called Password Checkup. About Password Checkup Once installed, Password Checkup appears in the browser bar. It springs into action when the user uses a username/password combination that is one of over 4 billion that Google knows … More

The post Google’s new Chrome extension flags insecure passwords appeared first on Help Net Security.

CookieMiner Malware Can Steal Crypto Exchange Cookies, Saved Passwords and iPhone SMS Messages

Researchers have discovered a new malware used to steal saved passwords and credit card details from browsers. In addition, it

CookieMiner Malware Can Steal Crypto Exchange Cookies, Saved Passwords and iPhone SMS Messages on Latest Hacking News.

Safer Internet Day: Security vs. Convenience

Safer Internet Day: Security vs. Convenience

It isn’t easy to be secure all the time — this is especially true if you are new to cybersecurity. A well-formed security plan takes deliberate effort at the very least, and constant vigilance at most. Even the top experts have room to improve because cybersecurity is a constantly moving target.

Unfortunately, most internet users aren’t using best practices.

The top two [passwords] have been left unchanged for the fifth year in a row.

Continue reading Safer Internet Day: Security vs. Convenience at Sucuri Blog.

Russian Cyber Criminal Named as Source of Massive Collection 1 Data Dump

A Russian cyber criminal going by the name of "C0rpz" is believed to be the source of a massive trove of over one billion online credentials known as "Collection 1," the firm Recorded Future reports.

The post Russian Cyber Criminal Named as Source of Massive Collection 1 Data Dump appeared first on The Security Ledger.

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Nest Cam Accessed Using Leaked Passwords Left Family Horrified

The dangers of low security on the Internet of Things (IoT) devices once again surfaced last week. A family have

Nest Cam Accessed Using Leaked Passwords Left Family Horrified on Latest Hacking News.

LIFX IoT Smart Light Bulb Hacked in Under an Hour

In under an hour, security researcher, LimitedResults, was able to hack into the smart light bulb LIFX mini white and

LIFX IoT Smart Light Bulb Hacked in Under an Hour on Latest Hacking News.

A Review Of Cyclonis Password Manager – Manages Your Passwords For Free!

Best practice dictates that users should use a different password for every online account they own, for an average internet

A Review Of Cyclonis Password Manager – Manages Your Passwords For Free! on Latest Hacking News.

Four More Collections, 700 Million Stolen Passwords Discovered

Researchers say that four more collections of stolen passwords contain more than 2 billion records and hundreds of millions of unique passwords, according to reports.

The post Four More Collections, 700 Million Stolen Passwords Discovered appeared first on The Security Ledger.

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AI May Soon Defeat Biometric Security, Even Facial Recognition Software

It’s time to face a stark reality: Threat actors will soon gain access to artificial intelligence (AI) tools that will enable them to defeat multiple forms of authentication — from passwords to biometric security systems and even facial recognition software — identify targets on networks and evade detection. And they’ll be able to do all of this on a massive scale.

Sounds far-fetched, right? After all, AI is difficult to use, expensive and can only be produced by deep-pocketed research and development labs. Unfortunately, this just isn’t true anymore; we’re now entering an era in which AI is a commodity. Threat actors will soon be able to simply go shopping on the dark web for the AI tools they need to automate new kinds of attacks at unprecedented scales. As I’ll detail below, researchers are already demonstrating how some of this will work.

When Fake Data Looks Real

Understanding the coming wave of AI-powered cyberattacks requires a shift in thinking and AI-based unified endpoint management (UEM) solutions that can help you think outside the box. Many in the cybersecurity industry assume that AI will be used to simulate human users, and that’s true in some cases. But a better way to understand the AI threat is to realize that security systems are based on data. Passwords are data. Biometrics are data. Photos and videos are data — and new AI is coming online that can generate fake data that passes as the real thing.

One of the most challenging AI technologies for security teams is a very new class of algorithms called generative adversarial networks (GANs). In a nutshell, GANs can imitate or simulate any distribution of data, including biometric data.

To oversimplify how GANs work, they involve pitting one neural network against a second neural network in a kind of game. One neural net, the generator, tries to simulate a specific kind of data and the other, the discriminator, judges the first one’s attempts against real data — then informs the generator about the quality of its simulated data. As this progresses, both neural networks learn. The generator gets better at simulating data, and the discriminator gets better at judging the quality of that data. The product of this “contest” is a large amount of fake data produced by the generator that can pass as the real thing.

GANs are best known as the foundational technology behind those deep fake videos that convincingly show people doing or saying things they never did or said. Applied to hacking consumer security systems, GANs have been demonstrated — at least, in theory — to be keys that can unlock a range of biometric security controls.

Machines That Can Prove They’re Human

CAPTCHAs are a form of lightweight website security you’re likely familiar with. By making visitors “prove” they’re human, CAPTCHAs act as a filter to block automated systems from gaining access. One typical kind of CAPTCHA asks users to identify numbers, letters and characters that have been jumbled, distorted and obfuscated. The idea is that humans can pick out the right symbols, but machines can’t.

However, researchers at Northwest University and Peking University in China and Lancaster University in the U.K. claimed to have developed an algorithm based on a GAN that can break most text-based CAPTCHAs within 0.05 seconds. In other words, they’ve trained a machine that can prove it’s human. The researchers concluded that because their technique uses a small number of data points for training the algorithm — around 500 test CAPTCHAs selected from 11 major CAPTCHA services — and both the machine learning part and the cracking part happen very quickly using a single standard desktop PC, CAPTCHAs should no longer be relied upon for front-line website defense.

Faking Fingerprints

One of the oldest tricks in the book is the brute-force password attack. The most commonly used passwords have been well-known for some time, and many people use passwords that can be found in the dictionary. So if an attacker throws a list of common passwords, or the dictionary, at a large number of accounts, they’re going to gain access to some percentage of those targets.

As you might expect, GANs can produce high-quality password guesses. Thanks to this technology, it’s now also possible to launch a brute-force fingerprint attack. Fingerprint identification — like the kind used by major banks to grant access to customer accounts — is no longer safe, at least in theory.

Researchers at New York University and Michigan State University recently conducted a study in which GANs were used to produce fake-but-functional fingerprints that also look convincing to any human. They said their method worked because of a flaw in the way many fingerprint ID systems work. Instead of matching the full fingerprint, most consumer fingerprint systems only try to match a part of the fingerprint.

The GAN approach enables the creation of thousands of fake fingerprints that have the highest likelihood of being matches for the partial fingerprints the authentication software is looking for. Once a large set of high-quality fake fingerprints is produced, it’s basically a brute-force attack using fingerprint patterns instead of passwords. The good news is that many consumer fingerprint sensors use heat or pressure to detect whether an actual human finger is providing the biometric data.

Is Face ID Next?

One of the most outlandish schemes for fooling biometric security involves tricking facial recognition software with fake faces. This was a trivial task with 2D technologies, in part because the capturing of 2D facial data could be done with an ordinary camera, and at some distance without the knowledge of the target. But with the emergence of high-definition 3D technologies found in many smartphones, the task becomes much harder.

A journalist working at Forbes tested four popular Android phones, plus an iPhone, using 3D-printed heads made by a company called Backface in Birmingham, U.K. The studio used 50 cameras and sophisticated software to scan the “victim.” Once a complete 3D image was created, the life-size head was 3D-printed, colored and, finally, placed in front of the various phones.

The results: All four Android phones unlocked with the phony faces, but the iPhone didn’t.

This method is, of course, difficult to pull off in real life because it requires the target to be scanned using a special array of cameras. Or does it? Constructing a 3D head out of a series of 2D photos of a person — extracted from, say, Facebook or some other social network — is exactly the kind of fake data that GANs are great at producing. It won’t surprise me to hear in the next year or two that this same kind of unlocking is accomplished using GAN-processed 2D photos to produce 3D-printed faces that pass as real.

Stay Ahead of the Unknown

Researchers can only demonstrate the AI-based attacks they can imagine — there are probably hundreds or thousands of ways to use AI for cyberattacks that we haven’t yet considered. For example, McAfee Labs predicted that cybercriminals will increasingly use AI-based evasion techniques during cyberattacks.

What we do know is that as we enter into a new age of artificial intelligence being everywhere, we’re also going to see it deployed creatively for the purpose of cybercrime. It’s a futuristic arms race — and your only choice is to stay ahead with leading-edge security based on AI.

The post AI May Soon Defeat Biometric Security, Even Facial Recognition Software appeared first on Security Intelligence.

Security Analysis of the LIFX Smart Light Bulb

The security is terrible:

In a very short limited amount of time, three vulnerabilities have been discovered:

  • Wifi credentials of the user have been recovered (stored in plaintext into the flash memory).
  • No security settings. The device is completely open (no secure boot, no debug interface disabled, no flash encryption).
  • Root certificate and RSA private key have been extracted.

Boing Boing post.

How privacy and security concerns affect password practices

Yubico announced the results of the company’s 2019 State of Password and Authentication Security Behaviors Report, conducted by the Ponemon Institute, who surveyed 1,761 IT and IT security practitioners in the United States, United Kingdom, Germany and France. Understanding behavior The purpose of this study is to understand the beliefs and behaviors surrounding password management and authentication practices for individuals both in the workplace and at home. The goal was to understand if these beliefs … More

The post How privacy and security concerns affect password practices appeared first on Help Net Security.

Japanese Government Will Hack Citizens’ IoT Devices

The Japanese government is going to run penetration tests against all the IoT devices in their country, in an effort to (1) figure out what's insecure, and (2) help consumers secure them:

The survey is scheduled to kick off next month, when authorities plan to test the password security of over 200 million IoT devices, beginning with routers and web cameras. Devices in people's homes and on enterprise networks will be tested alike.


The Japanese government's decision to log into users' IoT devices has sparked outrage in Japan. Many have argued that this is an unnecessary step, as the same results could be achieved by just sending a security alert to all users, as there's no guarantee that the users found to be using default or easy-to-guess passwords would change their passwords after being notified in private.

However, the government's plan has its technical merits. Many of today's IoT and router botnets are being built by hackers who take over devices with default or easy-to-guess passwords.

Hackers can also build botnets with the help of exploits and vulnerabilities in router firmware, but the easiest way to assemble a botnet is by collecting the ones that users have failed to secure with custom passwords.

Securing these devices is often a pain, as some expose Telnet or SSH ports online without the users' knowledge, and for which very few users know how to change passwords. Further, other devices also come with secret backdoor accounts that in some cases can't be removed without a firmware update.

I am interested in the results of this survey. Japan isn't very different from other industrialized nations in this regard, so their findings will be general. I am less optimistic about the country's ability to secure all of this stuff -- especially before the 2020 Summer Olympics.

Multifactor Authentication Delivers the Convenience and Security Online Shoppers Demand

Another holiday shopping season has ended, and for exhausted online consumers, this alone is good news. The National Retail Federation (NRF), the world’s largest retail trade association, reported that the number of online transactions surpassed that of in-store purchases during Thanksgiving weekend in the U.S. Online shopping is a growing, global trend that is boosted by big retailers and financial institutions.

However, according to a Javelin Strategy & Research study, many consumers remain skeptical about the security of online shopping and mobile banking systems. While 70 percent of those surveyed said they feel secure purchasing items from a physical store, the confidence level dropped to 56 percent for online purchases and 50 percent for mobile banking. How can retailers increase customer trust toward online transactions?

Security Versus Convenience: The Search for Equilibrium Continues

When we register for online services, we implicitly balance security and convenience. When we’re banking and shopping online, the need for security is greater. We are willing to spend more time to complete a transaction — for example, by entering a one-time password (OTP) received via SMS — in exchange for a safer experience. On the other hand, convenience becomes paramount when logging into social networks, often at the expense of security.

App or account types respondents cared most to protect

(Source: IBM Future of Identity Study 2018)

A growing number of users are finding the right balance between convenience and security in biometric authentication capabilities such as fingerprint scanning and facial recognition. Passwords have done the job so far, but they are destined for an inexorable decline due to the insecurity of traditional authentication systems.

According to the “IBM Future of Identity Study 2018,” a fingerprint scan is perceived as the most secure authentication method, while alphanumeric passwords and digital personal identification numbers (PINs) are decidedly inferior. However, even biometrics have their faults; there is already a number of documented break-ins, data breaches, viable attack schemes and limitations. For instance, how would facial recognition behave in front of twins?

The Future of Identity Verification and Multifactor Authentication

Multifactor authentication (MFA) represents a promising alternative. MFA combines multiple authentication factors so that if one is compromised, the overall system can remain secure. The familiar system already in use for many online services — based on the combination of a password and an SMS code to authorize a login or transaction — is a simple example of two-factor authentication (2FA).

Authentication factors that are not visible, such as device fingerprinting, geolocation, IP reputation, device reputation and mobile network operator (MNO) data, can contribute substantially to identity verification. Some threat intelligence platforms can already provide most of this information to third-party applications and solutions. These elements add context to the user and device used for the online transaction and assist in quantifying the risk level of each operation.

The new available features open the way to context-based access, which conditions access to the dynamic assessment of the risk associated with a single transaction, modulating additional verification actions when the risk level becomes too great.

Existing technologies for context-based access allow security teams to:

  • Register the user’s device, silently or subject to consent, and promptly identify any device substitution or attempt to impersonate the legitimate device;
  • Associate biometric credentials to registered devices, thus binding the legitimate device, user and online application;
  • Spot known users accessing data from unregistered devices and require additional authentication steps;
  • Move to passwordless login, based on scanning a time-based QR code without typing a password;
  • Verify the user presence, limiting the effectiveness of reply attacks and other automated attacks;
  • Use an authenticator app to access online services with 2FA that leverages the biometric device on the smartphone, such as the fingerprint reader, and stores biometric data only on the user’s device;
  • Use advanced authentication mechanisms, such as FIDO2, which standardizes the use of authentication devices for access to online services in mobile and desktop environments; and
  • Calculate the risk value for a transaction based on the user’s behavioral patterns.

Combining all these elements, context-based access solutions conduct a dynamic risk assessment of each transaction. The transaction risk score, compared against predefined policies, can allow or block an operation or request additional authentication elements.

Get Your Customers Excited About Security

The aforementioned “IBM Future of Identity Study 2018” revealed clear demographic, geographic and cultural differences regarding the acceptance of authentication methods. It is therefore necessary to favor the adoption of next-generation authentication mechanisms and other emerging alternatives to traditional passwords.

Imposing a particular method of identity verification in the name of improved security can lead to user frustration, missed opportunities and even loss of customers. Instead, you should present new authentication mechanisms as more practical and convenient — that way, your customers will perceive it as a step toward innovation and progress rather than an impediment. If your authentication method feels “cool,” your users will be more excited to show it to colleagues and friends and less frustrated with a clunky login experience. You may even want to consider offering a wide range of authentication options and letting your users choose which they prefer.

Multifactor authentication is here to stay as traditional passwords lose favor with both security professionals and increasingly privacy-aware customers. If retailers can frame these new techniques in a way that gets users excited about security, the future of identity verification in the industry looks bright.

The post Multifactor Authentication Delivers the Convenience and Security Online Shoppers Demand appeared first on Security Intelligence.

Troy Hunt: the largest data leak in history

The Details of at Least 773 Million People Surfaced on a Free Cloud Storage Service

The details of at least 773 million people surfaced on free cloud storage service last week, reported Troy Hunt, Australian web security expert, and administrator of Have I Been Pwned (HIBP) website. As you might already know, Troy has been collecting data from many data breaches over the last five years. He has been compiling it into a single database, so people have the opportunity to search across multiple data breaches and find out if their details have been compromised at some point in the past. The website allows searches by password and email.

When we heard the news about what Gizmodo calls the ‘mother of all breaches,’ we initially thought that Troy Hunt and his database had been hacked. However, this was quickly debunked as Troy himself confirmed that he is the one who actually found the pile of stolen data. He called the breach ‘Collection #1’ and highlighted that this is the ‘single largest breach ever to be loaded into HIBP.’

This incident shows that Troy Hunt was not the only one who has been piling up information from past data breaches. An anonymous hacker uploaded approximately 12,000 files containing 772,904,99 emails and 21,222,975 unique passwords into a single large database. Troy reported that the 87GB worth of stolen data was published on a free cloud service called MEGA. What makes this breach particularly interesting is that this is the first part of a much bigger database of stolen data. Troy Hunt reported that he is in possession of four more collections, and he is currently reviewing them. He will be making a call on what to do with them after investigating them further. MEGA has since deleted the database.

While most of the data included in ‘Collection #1’ was already in HIBP, the data in collections #2 through #5 may end up making this one of the biggest data breaches ever seen. It is currently unknown if collections #2 to #5 are as big as ‘Collection #1’. If the remaining four collections are as significant as the first one, this may end up exposing details of billions of people.

What should you do?

The database is compiled of old data breaches, so if the data comes from known breaches, you most likely have been notified either by the service or by HIBP to change your password a long time ago. However, quite often data breaches sometimes take years to be discovered, so regular password changes are strongly recommended. Avoid using the same password on multiple platforms. The cybersecurity budgets of some companies are significantly lower when compared to others – we are confident JP Morgan Chase spends more on developing stronger security when compared to a t-shirt store. But if the passwords you use at both organizations are the same, hackers can steal your details from the weak organization and use the login credentials to get unauthorized access to services such as your internet banking.

You can easily check if your passwords or email addresses have been part of ‘Collection #1’ or if they have been pwned in the pat. You can search if your emails have been pwned here, and learn if your passwords are part of the breach by testing them here

Last but not least, have anti-virus software installed on all your connected devices. Most of the times high-quality anti-virus software comes with a password manager that will help you always know your password. Apart from the password management options, such software could also prevent hackers from stealing the missing piece from the puzzle that would allow them to make you a victim of cybercrime.

Download your Antivirus

The post Troy Hunt: the largest data leak in history appeared first on Panda Security Mediacenter.

Collection 1 data breach: what you need to know

Yesterday, news broke that the largest data dump in history had been discovered, with more than 770 million people’s Personally Identifiable Information (PII) decrypted, catalogued, and up for grabs on the Internet. The files, which are being dubbed Collection 1, were originally found on cloud service MEGA, and later posted to a popular hacking forum.

The Collection 1 folder contains more than 12,000 files and is a whopping 87 gigabytes large.

While on paper this sounds beyond alarming, the truth is much more nuanced. The collection is composed of data pulled together from multiple breaches and leaks, many of which contain email addresses and passwords that are at least two to three years old. Security researcher Brian Krebs cautioned folks on assigning too much significance to the find because the data is rather stale, and not particularly useful for threat actors.

However, as we saw in summer 2018, stale data can be used successfully in phishing and extortion campaigns. The mere mention of a correct password, even if it’s outdated, could coax unsuspecting users into giving up fresh PII or paying ransoms.

Every time an organization announces that it’s been breached, customers wait with bated breath to see if they’ve been impacted. But after a time, if an identity theft crisis, credit card tampering, or straight-up hack doesn’t take place, many users breathe a sigh of relief and imagine they’ve weathered the storm. Yet, as evidenced by Collection 1 and other such treasure troves of data that are offered for sale online, that may not be the end of it. If users don’t take steps to protect or change their credentials after a breach, they are at risk of being targeted again and again.

Our advice to users: Take a look to see if your information is caught up in this latest data dump. You can easily check to see if you’ve been compromised by using researcher Troy Hunt’s website Have I Been Pwned. Once there, enter your email address and scroll to the bottom of the page to see if you are part of Collection 1 or any other breaches. In addition, you can check if your password was compromised using a new feature of Hunt’s site called Pwned Passwords.

If you are on any of these lists, go forth and change your passwords immediately. We also recommend using a password manager and following other password best practices, such as avoiding using the same password across multiple sites and using long phrases that do not contain obvious dates, names, or other easily identifiable (and thus crackable) information.

No, this may not have been the breach to end all breaches. But that doesn’t mean it should be taken lightly. In fact, this is an opportunity for 770 million people to shore up their defenses by making a simple, yet effective, change.

As always: Stay safe, everyone!

The post Collection 1 data breach: what you need to know appeared first on Malwarebytes Labs.

The 773 Million Record “Collection #1” Data Breach

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The 773 Million Record

Many people will land on this page after learning that their email address has appeared in a data breach I've called "Collection #1". Most of them won't have a tech background or be familiar with the concept of credential stuffing so I'm going to write this post for the masses and link out to more detailed material for those who want to go deeper.

Let's start with the raw numbers because that's the headline, then I'll drill down into where it's from and what it's composed of. Collection #1 is a set of email addresses and passwords totalling 2,692,818,238 rows. It's made up of many different individual data breaches from literally thousands of different sources. (And yes, fellow techies, that's a sizeable amount more than a 32-bit integer can hold.)

In total, there are 1,160,253,228 unique combinations of email addresses and passwords. This is when treating the password as case sensitive but the email address as not case sensitive. This also includes some junk because hackers being hackers, they don't always neatly format their data dumps into an easily consumable fashion. (I found a combination of different delimiter types including colons, semicolons, spaces and indeed a combination of different file types such as delimited text files, files containing SQL statements and other compressed archives.)

The unique email addresses totalled 772,904,991. This is the headline you're seeing as this is the volume of data that has now been loaded into Have I Been Pwned (HIBP). It's after as much clean-up as I could reasonably do and per the previous paragraph, the source data was presented in a variety of different formats and levels of "cleanliness". This number makes it the single largest breach ever to be loaded into HIBP.

There are 21,222,975 unique passwords. As with the email addresses, this was after implementing a bunch of rules to do as much clean-up as I could including stripping out passwords that were still in hashed form, ignoring strings that contained control characters and those that were obviously fragments of SQL statements. Regardless of best efforts, the end result is not perfect nor does it need to be. It'll be 99.x% perfect though and that x% has very little bearing on the practical use of this data. And yes, they're all now in Pwned Passwords, more on that soon.

That's the numbers, let's move onto where the data has actually come from.

Data Origins

Last week, multiple people reached out and directed me to a large collection of files on the popular cloud service, MEGA (the data has since been removed from the service). The collection totalled over 12,000 separate files and more than 87GB of data. One of my contacts pointed me to a popular hacking forum where the data was being socialised, complete with the following image:

The 773 Million Record

As you can see at the top left of the image, the root folder is called "Collection #1" hence the name I've given this breach. The expanded folders and file listing give you a bit of a sense of the nature of the data (I'll come back to the word "combo" later), and as you can see, it's (allegedly) from many different sources. The post on the forum referenced "a collection of 2000+ dehashed databases and Combos stored by topic" and provided a directory listing of 2,890 of the files which I've reproduced here. This gives you a sense of the origins of the data but again, I need to stress "allegedly". I've written before about what's involved in verifying data breaches and it's often a non-trivial exercise. Whilst there are many legitimate breaches that I recognise in that list, that's the extent of my verification efforts and it's entirely possible that some of them refer to services that haven't actually been involved in a data breach at all.

However, what I can say is that my own personal data is in there and it's accurate; right email address and a password I used many years ago. Like many of you reading this, I've been in multiple data breaches before which have resulted in my email addresses and yes, my passwords, circulating in public. Fortunately, only passwords that are no longer in use, but I still feel the same sense of dismay that many people reading this will when I see them pop up again. They're also ones that were stored as cryptographic hashes in the source data breaches (at least the ones that I've personally seen and verified), but per the quoted sentence above, the data contains "dehashed" passwords which have been cracked and converted back to plain text. (There's an entirely different technical discussion about what makes a good hashing algorithm and why the likes of salted SHA1 is as good as useless.) In short, if you're in this breach, one or more passwords you've previously used are floating around for others to see.

So that's where the data has come from, let me talk about how to assess your own personal exposure.

Checking Email Addresses and Passwords in HIBP

There'll be a significant number of people that'll land here after receiving a notification from HIBP; about 2.2M people presently use the free notification service and 768k of them are in this breach. Many others, over the years to come, will check their address on the site and land on this blog post when clicking in the breach description for more information. These people all know they were in Collection #1 and if they've read this far, hopefully they have a sense of what it is and why they're in there. If you've come here via another channel, checking your email address on HIBP is as simple as going to the site, entering it in then looking at the results (scrolling further down lists the specific data breaches the address was found in):

The 773 Million Record

But what many people will want to know is what password was exposed. HIBP never stores passwords next to email addresses and there are many very good reasons for this. That link explains it in more detail but in short, it poses too big a risk for individuals, too big a risk for me personally and frankly, can't be done without taking the sorts of shortcuts that nobody should be taking with passwords in the first place! But there is another way and that's by using Pwned Passwords.

This is a password search feature I built into HIBP about 18 months ago. The original intention of it was to provide a data set to people building systems so that they could refer to a list of known breached passwords in order to stop people from using them again (or at least advise them of the risk). This provided a means of implementing guidance from government and industry bodies alike, but it also provided individuals with a repository they could check their own passwords against. If you're inclined to lose your mind over that last statement, read about the k-anonymity implementation then continue below.

Here's how it works: let's do a search for the word "P@ssw0rd" which incidentally, meets most password strength criteria (upper case, lower case, number and 8 characters long):

The 773 Million Record

Obviously, any password that's been seen over 51k times is terrible and you'd be ill-advised to use it anywhere. When I searched for that password, the data was anonymised first and HIBP never received the actual value of it. Yes, I'm still conscious of the messaging when suggesting to people that they enter their password on another site but in the broader scheme of things, if someone is actually using the same one all over the place (as the vast majority of people still do), then the wakeup call this provides is worth it.

As of now, all 21,222,975 passwords from Collection #1 have been added to Pwned Passwords bringing the total number of unique values in the list to 551,509,767.

Whilst I can't tell you precisely what password was against your own record in the breach, I can tell you if any password you're interested in has appeared in previous breaches Pwned Passwords has indexed. If one of yours shows up there, you really want to stop using it on any service you care about. If you have a bunch of passwords and manually checking them all would be painful, give this a go:

This is 1Password's Watchtower feature and it can take all your stored passwords and check them against Pwned Passwords in one go. The same anonymity model is used (neither 1Password nor HIBP ever see your actual password) and it enables bulk checking all in one go. I'm conscious that many people reading this won't be using a password manager of any kind in the first place and that's an absolutely pivotal part of how to deal with this incident so I'll come back to that a little later. Apparently, this feature along with integrated HIBP searches and notifications when new breaches pop up is one of the most-loved features of 1Password which is pretty cool! For some background on that, without me knowing in advance, they launched an early version of this only a day after I released V2 with the anonymity model (incidentally, that was a key motivator for later partnering with them):

For those using Pwned Passwords in their own systems (EVE Online, GitHub, Okta et al),  the API is now returning the new data set and all cache has now been flushed (you should see a very recent "last-modified" response header). All the downloadable files have also been revised up to version 4 and are available on the Pwned Passwords page via download courtesy of Cloudflare or via torrents. They're in both SHA1 and NTLM formats with each ordered both alphabetically by hash and by prevalence (most common passwords first).

Why Load This Into HIBP?

Every single time I came across a data set that's not clearly a breach of a single, easily identifiable service, I ask the question - should this go into HIBP?  There are a number of factors that influence that decision and one of them is uniqueness; is this a sufficiently new set of data with a large volume of records I haven't seen before? In determining that, I take a slice of the email addresses and ran them against HIBP to see how many of them had been seen before. Here's what it looked like after a few hundred thousand checks:

The 773 Million Record

In other words, there's somewhere in the order of 140M email addresses in this breach that HIBP has never seen before.

The data was also in broad circulation based on the number of people that contacted me privately about it and the fact that it was published to a well-known public forum. In terms of the risk this presents, more people with the data obviously increases the likelihood that it'll be used for malicious purposes.

Then there's the passwords themselves and of the 21M+ unique ones, about half of them weren't already in Pwned Passwords. Keeping in mind how this service is predominantly used, that's a significant number that I want to make sure are available to the organisations that rely on this data to help steer their customers away from using higher-risk passwords.

And finally, every time I've asked the question "should I load data I can't emphatically identify the source of?", the response has always been overwhelmingly "yes":

People will receive notifications or browse to the site and find themselves there and it will be one more little reminder about how our personal data is misused. If - like me - you're in that list, people who are intent on breaking into your online accounts are circulating it between themselves and looking to take advantage of any shortcuts you may be taking with your online security. My hope is that for many, this will be the prompt they need to make an important change to their online security posture. And if you find yourself in this data and don't feel there's any value in knowing about it, ignore it. For everyone else, let's move on and establish the risk this presents then talk about fixes.

What's the Risk If My Data Is in There?

I referred to the word "combos" earlier on and simply put, this is just a combination of usernames (usually email addresses) and passwords. In this case, it's almost 2.7 billion of them compiled into lists which can be used for credential stuffing:

Credential stuffing is the automated injection of breached username/password pairs in order to fraudulently gain access to user accounts.

In other words, people take lists like these that contain our email addresses and passwords then they attempt to see where else they work. The success of this approach is predicated on the fact that people reuse the same credentials on multiple services. Perhaps your personal data is on this list because you signed up to a forum many years ago you've long since forgotten about, but because its subsequently been breached and you've been using that same password all over the place, you've got a serious problem.

By pure coincidence, just last week I wrote about credential stuffing attacks and how they led many people to believe that Spotify had suffered a data breach. In that post, I embedded a short video that shows how easily these attacks are automated and I want to include it again here:

Within the first 20 seconds, the author of the video has chosen a combo list just like the one three quarters of a billion people are in via this Combination #1 breach. Another 20 seconds and the software is testing those accounts against Spotify and reporting back with email addresses and passwords that can logon to accounts there. That's how easy it is and also how indiscriminate it is; it's not personal, you're just on the list! (For people wanting to go deeper, check out Shape Security's video on credential stuffing.)

To be clear too, this is not just a Spotify problem. Automated tools exist to leverage these combo lists against all sorts of other online services including ones you shop at, socialise at and bank at. If you found your password in Pwned Passwords and you're using that same one anywhere else, you want to change each and every one of those locations to something completely unique, which brings us to password managers.

Get a Password Manager

You have too many passwords to remember, you know they're not meant to be predictable and you also know they're not meant to be reused across different services. If you're in this breach and not already using a dedicated password manager, the best thing you can do right now is go out and get one. I did that many years ago now and wrote about how the only secure password is the one you can't remember. A password manager provides you with a secure vault for all your secrets to be stored in (not just passwords, I store things like credit card and banking info in mine too), and its sole purpose is to focus on keeping them safe and secure.

A password manager is also a rare exception to the rule that adding security means making your life harder. For example, logging on to a mobile app is dead easy:

I chose the password manager 1Password all those years ago and have stuck with it ever it since. As I mentioned earlier, they partnered with HIBP to help drive people interested in personal security towards better personal security practices and obviously there's some neat integration with the data in HIBP too (there's also a dedicated page explaining why I chose them).

If a digital password manager is too big a leap to take, go old school and get an analogue one (AKA, a notebook). Seriously, the lesson I'm trying to drive home here is that the real risk posed by incidents like this is password reuse and you need to avoid that to the fullest extent possible. It might be contrary to traditional thinking, but writing unique passwords down in a book and keeping them inside your physically locked house is a damn sight better than reusing the same one all over the web. Just think about it - you go from your "threat actors" (people wanting to get their hands on your accounts) being anyone with an internet connection and the ability to download a broadly circulating list Collection #1, to people who can break into your house - and they want your TV, not your notebook!


Because an incident of this size will inevitably result in a heap of questions, I'm going to list the ones I suspect I'll get here then add to it as others come up. It'll help me handle the volume of queries I expect to get and will hopefully make things a little clearer for everyone.

Q. Can you send me the password for my account?
I know I touched on it above but it's always the single biggest request I get so I'm repeating it here. No, I can't send you your password but I can give you a facility to search for it via Pwned Passwords.

Q. How long ago were these sites breached?
It varies. The first site on the list I shared was 000webhost who was breached in 2015, but there's also a file in there which suggests 2008. These are lots of different incidents from lots of different time frames.

Q. What can I do if I'm in the data?
If you're reusing the same password(s) across services, go and get a password manager and start using strong, unique ones across all accounts. Also turn on 2-factor authentication wherever it's available.

Q. I'm responsible for managing a website, how do I defend against credential stuffing attacks?
The fast, easy, free approach is using the Pwned Passwords list to block known vulnerable passwords (read about how other large orgs have used this service). There are services out there with more sophisticated commercial approaches, for example Shape Security's Blackfish (no affiliation with myself or HIBP).

Q. How can I check if people in my organisation are using passwords in this breach?
The entire Pwned Passwords corpus is also published as NTLM hashes. When I originally released these in August last year, I referenced code samples that will help you check this list against the passwords of accounts in an Active Directory environment.

Q. I'm using a unique password on each site already, how do I know which one to change?
You've got 2 options if you want to check your existing passwords against this list: The first is to use 1Password's Watch Tower feature described above. If you're using another password manager already, it's easy to migrate over (you can get a free 1Password trial). The second is to check all your existing passwords directly against the k-anonymity API. It'll require some coding, but's its straightforward and fully documented.

Q. Is there a list of which sites are included in this breach?
I've reproduced a list that was published to the hacking forum I mentioned and that contains 2,890 file names. This is not necessarily complete (nor can I easily verify it), but it may help some people understand the origin of their data a little better.

Q. Will you publish the data in collections #2 through #5?
Until this blog post went out, I wasn't even aware there were subsequent collections. I do have those now and I need to make a call on what to do with them after investigating them further.

Q. Where can I download the source data from?
Given the data contains a huge volume of personal information that can be used to access other people's accounts, I'm not going to direct people to it. I'd also ask that people don't do that in the comments section.

Comments Are Now Closed

After several hundred comments in a very short period of time, I'm closing this post for further contributions. Moderating them has consumed a significant amount of time that I've mostly dealt with whilst flying from Australia to Europe. I now need to focus on a short period of downtime followed by a couple of weeks of conference talks. Thank you all for your engagement, I'll talk more about this post in the next weekly update video I'll post on Friday 25.

A week in security (January 7 – 13)

Last week on the Malwarebytes Labs blog, we took a look at the Ryuk ransomware attack causing trouble over the holidays, as well as a ransom threat for an Irish transportation company. We explored the realm of SSN scams, and looked at what happens when an early warning system is attacked.

Other cybersecurity news

  • Password reuse problems. Multiple Reddit accounts reported being locked out after site admins blamed “password reuse” for the issue. (Source: The Register)
  • 85 rogue apps pulled from Play Store. Sadly, not before some 9 million downloads had already taken place. (Source: Trend Micro)
  • Home router risk. It seems many home routers aren’t doing enough in the fight against hackers. (Source: Help Net Security)
  • Deletion not allowed. Some people aren’t happy they can’t remove Facebook from their Samsung phones. (Source: Bloomberg)
  • Takedown: How a system admin brought down the notorious “El Chapo.” (Source: USA Today)
  • 2FA under fire. A new pentest tool called Mantis can be used to assist in the phishing of OTP (one time password) codes. (Source: Naked Security) 
  • Facebook falls foul of new security laws in Vietnam. New rules have brought a spot of bother for Facebook, accused of not removing certain types of content and handing over data related to “fraudulent accounts.” (source: Vietnam News)
  • Trading site has leak issue. A user on the newly set up trading platform was able to grab a lot of potentially problematic snippets, including authentication tokens and password reset links. (source: Ars Technica)
  • Local risk to card details. A researcher discovered payment info was being stored locally on machines, potentially exposing them to anyone with physical access. (Source: Hacker One) 
  • Facebook exec swatted. The dangerous “gag” of sending armed law enforcement to an address ends up causing problems for a “cybersecurity executive,” after bogus calls claimed they had “pipe bombs all over the place.” (source: PA Daily post)

Stay safe, everyone!

The post A week in security (January 7 – 13) appeared first on Malwarebytes Labs.

No, Spotify Wasn’t Hacked

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No, Spotify Wasn't Hacked

Time and time again, I get emails and DMs from people that effectively boil down to this:

Hey, that paste that just appeared in Have I Been Pwned is from Spotify, looks like they've had a data breach

Many years ago, I introduced the concept of pastes to HIBP and what they essentially boil down to is monitoring Pastebin and a bunch of other services for when a trove of email addresses is dumped online. Very often, those addresses are accompanied by other personal information such as passwords. When an HIBP subscriber's address appears in one of these incidents, they get an automated notification and often, it seems, they then reach out to me.

Here's a perfect example of what I'm talking about, this one eventually triggering an email to me just last week:

No, Spotify Wasn't Hacked

Let's imagine you're the first person on the list; you get a notification from HIBP, you check out the paste and see your Hotmail account listed there alongside your Spotify password and the plan you're subscribed to. Clearly a Spotify breach, right?

No, and the passwords are the very first thing that starts to give it all away. Just looking at them, they're obviously terrible, but plugging the first one into Pwned Passwords give you a sense of just how terrible it is:

No, Spotify Wasn't Hacked

They may not all be that bad (the next one in the list has only been seen twice), but the point is that it's a password that's clearly been seen before and were I to dig back into the source data, there's a good chance it's been seen in a breach alongside that email address too. Then there's the fact that the password is in plain text and I don't know precisely how Spotify store their passwords, but it'd be a very safe bet that by now it's a decent modern-day hashing algorithm. If they had a breach then yes, hashes may be cracked, but that's not what's happening here.

We're simply seeing the successful result of credential stuffing attacks. Regular readers will appreciate the mechanics of this already but all those who I point here for whom this is new, this attack simply takes exposed credentials from a data breach and tries them on another site. The attack is simple but effective due to the prevalence of password reuse. If you were using the same password on LinkedIn when they had their data breach as you are on Spotify today and someone grabbed that password from the breach and tried it on Spotify, you can see the problem. That's it, job done, they're into your account.

Spotify "breaches" like this are enormously common. I just went and looked at the pastes HIBP has collected since the clock ticked over to 2019 and found 20 of them already:

No, Spotify Wasn't Hacked

Digging further, I found over a thousand pastes with "Spotify" in the title. These are often removed by Pastebin pretty quickly but looking through some that remain, it's precisely the same pattern as the earlier example. I grabbed a random email address out of one of them and checked it on HIBP:

No, Spotify Wasn't Hacked

The same address appears over and over in pastes and each time, the same password appears alongside it. Picking one from the list above that hasn't yet been removed shows a page full of examples like this (with a password Pwned Passwords has seen 4 times before):

No, Spotify Wasn't Hacked

This one is interesting for a couple of reasons and the first is the use of the term "combo". I've written about combo lists before and they're essentially combinations of email addresses and passwords used to test against services in credential stuffing attacks. Thousands. Millions. Billions of them, in some cases. The second interesting observation in that image is the "Spotify Cracker" reference. The first Google result for the term shows a popular cracking forum with the following image (password seen 447 times in Pwned Passwords):

No, Spotify Wasn't Hacked

This is a tool for breaking into Spotify accounts I wouldn't normally link through to content of that type, but context is important. For people wondering why they're getting alerts from HIBP because their Spotify account is in a paste somewhere, have a flick through some of those pages. 61 of them at the time of writing, each with 20 posts thanking the OP for their work in order to get access to the tool. So what does it do? Have a quick watch of this:

It's a slightly different piece of software based on what's visible, but the objective is the same and the premise is simple: download the tool, pass in the combo list then let it run. Credentials from the list are then tested against Spotify (yes, security friends, there's a very good question to be asked here as to why this is still possible...) and results appear on the screen.

Now, this isn't to say that someone who finds their Spotify account on one of these lists shouldn't worry because it wasn't a breach per se. Instead, they need to look inwardly and adjust their own security practices instead. Get a password manager (8 years on and I still use 1Password every day), create strong and unique passwords on every account and enable 2-factor authentication where available. Well, except that there's still no 2FA support on Spotify so just enable it on every other service that supports it (and most big ones do these days).

And why would someone "hack" (I use the term loosely because they literally logged in with the correct username and password) Spotify accounts? The obvious answer is that they have a monetary value, but I also posit that it's very often just curiosity driving this behaviour. Take a look at a video such as this SQL injection tutorial; I've used it in talks before to illustrate the randomness of attacks as well as the sophistication of those behind many of them. Is the person in this video an evil cyber hacker hell-bent on causing chaos, or just a curious kid whose moral compass is yet to be properly calibrated? That may not make Spotify users feel any better about the end result, but it's important context for this post.

In doing a bit of searching for this piece I found heaps of results for "spotify data breach" that led to discussions highlighting what I've covered above. For example, this one from August on the Spotify community site where the original post begins with:

Someone had access to my pasword [sic] (which is totally unbreakable and diferent [sic] from the one i use in other accounts)

I don't know what their password was, but I do know that I've had dozens of discussions with people making precisely the same claims only to discover "their" password is in Pwned Passwords a few hundred times! Or they entered it into a phishing site somewhere. If we apply Occam's Razor to this (the simplest solution is the most likely one), the password was compromised. I want to illustrate this point via the following Tweet:

This is Scott Helme, a world-renowned security researcher who understands these concepts as well as anyone I can imagine. This tweet is part of a broader discussion where his Pinterest account was logged into by an unknown party and per the image above, Scott was convinced his password was both strong and unique. A couple of hours later, Scott's view is, well, somewhat "different":

I spoke to Scott about this incident again whilst writing this post and we both reflected on just how easy it is to have issues like this, even you're convinced your security is spot on. It's precedents like this which cause me to pause and question every strongly made claim of personal security prowess in the wake of examples such as the Spotify community one above.

Reading through that thread only reinforces the view that this was a simple account takeover issue and not a sophisticated hack. For example, this comment:

It's such a shame to see Spotify blaming its users for getting hacked instead of fixing the problem. Got my playlists deleted and the hacker created a playlist called "Get Hacked".

Imagine you're a hacker - a real one with the capabilities to break into a company with hundreds of millions of users and worth billions of dollars - what are you going to do? Are you just going to mess with people's playlists "for the lulz"? No, at the very least you're going to cash in on their public bug bounty or if you're really the malicious type, you're going to monetise their users in a much more surreptitious fashion.

Scroll down a little further and someone is referencing HIBP as "proof" of a hack. Here's what happened to the guy's account:

I got a notification from and did nothing about it until some random kept playing weird music on a device I did not recognize while I was trying to listen on my normal device. It was annoying, I kept getting pulled out of my song because we started battling for control of what device and what song the audio was to be heard on. I started playing really loud and obnoxious noise music for the hacker while I changed my password.

Now again, let's apply Occam's Razor: is this an elite hacker who's discovered some previously unknown zero-day vulnerability, or someone who's exploited the victim's password and then simply has a different taste in music?

The community thread references a paste titled "Más de 300 cuentas premium de Spotify" ("More than 300 Spotify premium accounts") which has since been deleted from Pastebin (and HIBP doesn't save the contents beyond just the email addresses). But 4 days earlier there was a paste titled "Más de 50 cuentas premium de spotify" which still stands today and its content lines up very closely with the others discussed above; it's simply the output of another automated tool exploiting weak credentials.

I'll end on one final point because if I don't, it'll come through in the comments anyway: online security is a shared responsibility. Some people are quick to play the "victim blaming" card when I write about incidents that can be traced back to weak security practices. Clearly, that's not causing me to sugar-coat the root cause of these incidents but that said (and I touched on this earlier), this is prevalent enough that Spotify also needs to look internally at why this is still occurring. Their job is to stop this form of attack at the platform level and our job as users of the service is to protect our accounts via some basic security practices.

So no, Spotify wasn't hacked, they just allowed malicious parties to log in with other people's poor passwords.

Abine says Blur Password Manager User Information Exposed

Customers who use the Blur secure password manager by Abine may have had sensitive information leaked, according to a statement by Abine, the company that makes the product. 

The post Abine says Blur Password Manager User Information Exposed appeared first on The Security Ledger.

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Twelve Commandments that will never fail to Keep You Cyber Safe Online

As the digital world explodes with a variety of new online services, cyber threats have become more ingenuous, dangerous, and spawned multiple variants and types. As each new threat makes the headline, the accompanying set of threat specific security recommendations confuses cybercitizens. Cybercitizens want a comprehensive list of recommendations that do not change frequently.

There are twelve foundational security practices that will help keep you and your family safe. Practicing them will harden your defenses against cybercrime and also reduce the negative effects of social media use.

1)    Thou shalt not use a device with pirated software
Pirated software is not patched as it is unlicensed. Unpatched software have security vulnerabilities which can be easily exploited to steal data and credentials

2)    Thou shalt not use a device which is not set for automatic updates of Operating System patches
Automatic patching for personal devices is the best way to ensure that the latest security patches are applied and security loopholes closed before cybercriminals can get to them

3)    Thou shalt not use a device without updated antimalware (antivirus) software installed
Antimalware software reduces the probability of a malware infection (e.g. ransomware) on your device. For it to be effective to catch the latest malware variants, it has to be automatically updated with the latest updates.

4)    Thou shall not download pirated movies, games and other such material
Something free may turn out to be expensive, both financially and to your reputation. Malware is usually bundled with pirated content or applications

5)    Thou shall not use a site without trying to verify its authenticity
Authenticity of a site can be verified by the Lock Icon and accompanying digital certificate. While not fool proof, it reduces the possibility of spoofed lookalike sites designed to steal your credentials

6)    Thou shall not ignore inappropriate content on social networks, always report or dislike it
Inappropriate content influences the minds of our children as they stumble upon it online. Hate content in particular may induce biases which take a long time to reverse.

7)    Thou shalt not indulge or encourage cyber bullying online
A parent or teacher has the additional responsibility of guiding children on the right online behavior. You do not want your children to bully or be bullied

8)    Thou shalt not use passwords that can be easily guessed and promise to  keep the password a secret
Try to choose complex passwords, do not reuse them on multiple sites and always store them securely. The easiest way to get into your online accounts is by stealing your passwords

9)    Thou shalt not fall be tempted by fraudulent emails promising financial windfalls or miracle cures or cheap medicines
Try to check the authenticity of the email. Electronic communication is easily manipulated, as it is difficult to verify the authenticity of the sender. Scams like these can cost you money and affect your health.

10) Thou shall not forsake your responsibility of helping your older parents or young kids to be safe as they use the internet
Be a guide and easily available as both old and young learn to use the internet and face cyber risks. Being available, requires that you can be reached for instant advice on problems they encounter

11) Thou shalt never trust a stranger blindly online
Always be suspicious when dealing with online strangers. At any point during the relationship never let down your guard. The identity of an online person cannot be easily verified. It can however be easily manipulated. Online friends sometimes have the vilest of intention which can lead to all forms of blackmail, particularly if they have incriminating pictures and videos. Besides adults, young children are potential victims

12) Thou shalt not set a weak password for your mobile phone or keep it unlocked
A stolen phone with an easy to guess password or if unlocked, is a sure invitation into all your signed in accounts and personal data. A large number of phones are left unattended or lost each year.

Call for help: researching the recent gmail password leak

Hey folks,

You probably heard this week about 5 million accounts posted. I've been researching it independently, and was hoping for some community help (this is completely unrelated to the fact that I work at Google - I just like passwords).

I'm reasonably sure that the released list is an amalgamation of a bunch of other lists and breaches. But I don't know what ones - that's what I'm trying to find out!

Which brings me to how you can help: people who can recognize which site their password came from. I'm trying to build a list of which breaches were aggregated to create this list, in the hopes that I can find breaches that were previously unreported!

If you want to help:

      1. Check your email address on
      2. If you're in the list, email from the associated account
      3. I'll tell you the password that was associated with that account
      4. And, most importantly, you tell me which site you used that password on!

In a couple days/weeks (depending on how many responses I get), I'll release the list of providers!

Thanks! And, as a special 'thank you' to all of you, here are the aggregated passwords from the breach! And no, I'm not going to release (or keep) the email list. :)

Security: Hard to Get Right!

Couple of interesting articles doing the rounds this week, which are worthy of a quick comment!

Heartbleed: the bug that keeps on giving
Reports suggest that the Heartbleed vulnerability was involved in a breach of over 4 million records from a health provider in the US — we won't see many of these, as identifying the culprit as Heartbleed is really difficult in most cases. That instances like this are still cropping up reminds us of the need to ensure we're patched, and not just in the obvious places like a web server. This time it seems to have been SSL VPN at the heart of the issue, so to speak.

Passwords: why are we still so rubbish at this?
Apparently 51% of people share a password. This is properly daft. Really, crazier than a box of weasels. Even if you trust the other person, there's no telling what accidents might occur, or where they may re-use that password themselves. I always get gyp from my wife that I won't tell her my passwords, but I won't — and believe me, I do pretty much everything else she tells me!

EU "right to be forgotten" rule still here, still a waste of time?!
Internet numptys are still asking Google to remove them from searches in their droves. Happily the BBC is kind enough to reveal who they are by linking us to the relevant articles. When will people realise that once you publish something on the Internet, it is there forever. Unless it's that really useful document you bookmarked last week, which now 404s and was never in the Internet archive. Yes, that one.

More on the Avast breach and the hash used

My understanding is that the hash formula used by Avast to store its forum users’ passwords was $hash = sha1(strtolower($username) . $password); This is the formula built into the SMF open source forum software used by Avast. It is both good and bad. It confirms that the hash was salted (with the user’s username); but […]