Entries Tagged "China"

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APT10 and Cloud Hopper

There’s a new report of a nation-state attack, presumed to be from China, on a series of managed ISPs. From the executive summary:

Since late 2016, PwC UK and BAE Systems have been assisting victims of a new cyber espionage campaign conducted by a China-based threat actor. We assess this threat actor to almost certainly be the same as the threat actor widely known within the security community as ‘APT10’. The campaign, which we refer to as Operation Cloud Hopper, has targeted managed IT service providers (MSPs), allowing APT10 unprecedented potential access to the intellectual property and sensitive data of those MSPs and their clients globally. A number of Japanese organisations have also been directly targeted in a separate, simultaneous campaign by the same actor.

We have identified a number of key findings that are detailed below.

APT10 has recently unleashed a sustained campaign against MSPs. The compromise of MSP networks has provided broad and unprecedented access to MSP customer networks.

  • Multiple MSPs were almost certainly being targeted from 2016 onwards, and it is likely that APT10 had already begun to do so from as early as 2014.
  • MSP infrastructure has been used as part of a complex web of exfiltration routes spanning multiple victim networks.

[…]

APT10 focuses on espionage activity, targeting intellectual property and other sensitive data.

  • APT10 is known to have exfiltrated a high volume of data from multiple victims, exploiting compromised MSP networks, and those of their customers, to stealthily move this data around the world.
  • The targeted nature of the exfiltration we have observed, along with the volume of the data, is reminiscent of the previous era of APT campaigns pre-2013.

PwC UK and BAE Systems assess APT10 as highly likely to be a China-based threat actor.

  • It is a widely held view within the cyber security community that APT10 is a China-based threat actor.
  • Our analysis of the compile times of malware binaries, the registration times of domains attributed to APT10, and the majority of its intrusion activity indicates a pattern of work in line with China Standard Time (UTC+8).
  • The threat actor’s targeting of diplomatic and political organisations in response to geopolitical tensions, as well as the targeting of specific commercial enterprises, is closely aligned with strategic Chinese interests.

I know nothing more than what’s in this report, but it looks like a big one.

Press release.

Posted on April 5, 2017 at 10:42 AM • View Comments

Analyzing WeChat

Citizen Lab has analyzed how censorship works in the Chinese chat app WeChat:

Key Findings:

  • Keyword filtering on WeChat is only enabled for users with accounts registered to mainland China phone numbers, and persists even if these users later link the account to an International number.
  • Keyword censorship is no longer transparent. In the past, users received notification when their message was blocked; now censorship of chat messages happens without any user notice.
  • More keywords are blocked on group chat, where messages can reach a larger audience, than one-to-one chat.
  • Keyword censorship is dynamic. Some keywords that triggered censorship in our original tests were later found to be permissible in later tests. Some newfound censored keywords appear to have been added in response to current news events.
  • WeChat’s internal browser blocks China-based accounts from accessing a range of websites including gambling, Falun Gong, and media that report critically on China. Websites that are blocked for China accounts were fully accessible for International accounts, but there is intermittent blocking of gambling and pornography websites on International accounts.

Lots more details in the paper.

Posted on December 1, 2016 at 9:29 AM • View Comments

Smartphone Secretly Sends Private Data to China

This is pretty amazing:

International customers and users of disposable or prepaid phones are the people most affected by the software. But the scope is unclear. The Chinese company that wrote the software, Shanghai Adups Technology Company, says its code runs on more than 700 million phones, cars and other smart devices. One American phone manufacturer, BLU Products, said that 120,000 of its phones had been affected and that it had updated the software to eliminate the feature.

Kryptowire, the security firm that discovered the vulnerability, said the Adups software transmitted the full contents of text messages, contact lists, call logs, location information and other data to a Chinese server.

On one hand, the phone secretly sends private user data to China. On the other hand, it only costs $50.

Posted on November 18, 2016 at 2:22 PM • View Comments

DDoS Attacks against Dyn

Yesterday’s DDoS attacks against Dyn are being reported everywhere.

I have received a gazillion press requests, but I am traveling in Australia and Asia and have had to decline most of them. That’s okay, really, because we don’t know anything much of anything about the attacks.

If I had to guess, though, I don’t think it’s China. I think it’s more likely related to the DDoS attacks against Brian Krebs than the probing attacks against the Internet infrastructure, despite how prescient that essay seems right now. And, no, I don’t think China is going to launch a preemptive attack on the Internet.

Posted on October 22, 2016 at 8:47 AM • View Comments

Espionage Tactics Against Tibetans

A Citizen Lab research study of Chinese attack and espionage tactics against Tibetan networks and users.

This report describes the latest iteration in a long-running espionage campaign against the Tibetan community. We detail how the attackers continuously adapt their campaigns to their targets, shifting tactics from document-based malware to conventional phishing that draws on “inside” knowledge of community activities. This adaptation appears to track changes in security behaviors within the Tibetan community, which has been promoting a move from sharing attachments via e-mail to using cloud-based file sharing alternatives such as Google Drive.

We connect the attack group’s infrastructure and techniques to a group previously identified by Palo Alto Networks, which they named Scarlet Mimic. We provide further context on Scarlet Mimic’s targeting and tactics, and the intended victims of their attack campaigns. In addition, while Scarlet Mimic may be conducting malware attacks using other infrastructure, we analyze how the attackers re-purposed a cluster of their malware Command and Control (C2) infrastructure to mount the recent phishing campaign.

This move is only the latest development in the ongoing cat and mouse game between attack groups like Scarlet Mimic and the Tibetan community. The speed and ease with which attackers continue to adapt highlights the challenges faced by Tibetans who are trying to remain safe online.

News article.

Posted on March 10, 2016 at 2:16 PM • View Comments

The 2016 National Threat Assessment

It’s National Threat Assessment Day. Published annually by the Director of National Intelligence, the “Worldwide Threat Assessment of the US Intelligence Community” is the US intelligence community’s one time to publicly talk about the threats in general. The document is the results of weeks of work and input from lots of people. For Clapper, it’s his chance to shape the dialog, set up priorities, and prepare Congress for budget requests. The document is an unclassified summary of a much longer classified document. And the day also includes Clapper testifying before the Senate Armed Service Committee. (You’ll remember his now-famous lie to the committee in 2013.)

The document covers a wide variety of threats, from terrorism to organized crime, from energy politics to climate change. Although the document clearly says “The order of the topics presented in this statement does not necessarily indicate the relative importance or magnitude of the threat in the view of the Intelligence Community,” it does. And like 2015 and 2014, cyber threats are #1—although this year it’s called “Cyber and Technology.”

The consequences of innovation and increased reliance on information technology in the next few years on both our society’s way of life in general and how we in the Intelligence Community specifically perform our mission will probably be far greater in scope and impact than ever. Devices, designed and fielded with minimal security requirements and testing, and an ever—increasing complexity of networks could lead to widespread vulnerabilities in civilian infrastructures and US Government systems. These developments will pose challenges to our cyber defenses and operational tradecraft but also create new opportunities for our own intelligence collectors.

Especially note that last clause. The FBI might hate encryption, but the intelligence community is not going dark.

The document then calls out a few specifics like the Internet of Things and Artificial Intelligence—no surprise, considering other recent statements from government officials. This is the “…and Technology” part of the category.

More specifically:

Future cyber operations will almost certainly include an increased emphasis on changing or manipulating data to compromise its integrity (i.e., accuracy and reliability) to affect decisionmaking, reduce trust in systems, or cause adverse physical effects. Broader adoption of IoT devices and AI ­—in settings such as public utilities and health care—will only exacerbate these potential effects. Russian cyber actors, who post disinformation on commercial websites, might seek to alter online media as a means to influence public discourse and create confusion. Chinese military doctrine outlines the use of cyber deception operations to conceal intentions, modify stored data, transmit false data, manipulate the flow of information, or influence public sentiments -­ all to induce errors and miscalculation in decisionmaking.

Russia is the number one threat, followed by China, Iran, North Korea, and non-state actors:

Russia is assuming a more assertive cyber posture based on its willingness to target critical infrastructure systems and conduct espionage operations even when detected and under increased public scrutiny. Russian cyber operations are likely to target US interests to support several strategic objectives: intelligence gathering to support Russian decisionmaking in the Ukraine and Syrian crises, influence operations to support military and political objectives, and continuing preparation of the cyber environment for future contingencies.

Comments on China refer to the cybersecurity agreement from last September:

China continues to have success in cyber espionage against the US Government, our allies, and US companies. Beijing also selectively uses cyberattacks against targets it believes threaten Chinese domestic stability or regime legitimacy. We will monitor compliance with China’s September 2015 commitment to refrain from conducting or knowingly supporting cyber—enabled theft of intellectual property with the intent of providing competitive advantage to companies or commercial sectors. Private—sector security experts have identified limited ongoing cyber activity from China but have not verified state sponsorship or the use of exfiltrated data for commercial gain.

Also interesting are the comments on non-state actors, which discuss both propaganda campaigns from ISIL, criminal ransomware, and hacker tools.

Posted on February 9, 2016 at 3:25 PM • View Comments

Replacing Judgment with Algorithms

China is considering a new “social credit” system, designed to rate everyone’s trustworthiness. Many fear that it will become a tool of social control—but in reality it has a lot in common with the algorithms and systems that score and classify us all every day.

Human judgment is being replaced by automatic algorithms, and that brings with it both enormous benefits and risks. The technology is enabling a new form of social control, sometimes deliberately and sometimes as a side effect. And as the Internet of Things ushers in an era of more sensors and more data—and more algorithms—we need to ensure that we reap the benefits while avoiding the harms.

Right now, the Chinese government is watching how companies use “social credit” scores in state-approved pilot projects. The most prominent one is Sesame Credit, and it’s much more than a financial scoring system.

Citizens are judged not only by conventional financial criteria, but by their actions and associations. Rumors abound about how this system works. Various news sites are speculating that your score will go up if you share a link from a state-sponsored news agency and go down if you post pictures of Tiananmen Square. Similarly, your score will go up if you purchase local agricultural products and down if you purchase Japanese anime. Right now the worst fears seem overblown, but could certainly come to pass in the future.

This story has spread because it’s just the sort of behavior you’d expect from the authoritarian government in China. But there’s little about the scoring systems used by Sesame Credit that’s unique to China. All of us are being categorized and judged by similar algorithms, both by companies and by governments. While the aim of these systems might not be social control, it’s often the byproduct. And if we’re not careful, the creepy results we imagine for the Chinese will be our lot as well.

Sesame Credit is largely based on a US system called FICO. That’s the system that determines your credit score. You actually have a few dozen different ones, and they determine whether you can get a mortgage, car loan or credit card, and what sorts of interest rates you’re offered. The exact algorithm is secret, but we know in general what goes into a FICO score: how much debt you have, how good you’ve been at repaying your debt, how long your credit history is and so on.

There’s nothing about your social network, but that might change. In August, Facebook was awarded a patent on using a borrower’s social network to help determine if he or she is a good credit risk. Basically, your creditworthiness becomes dependent on the creditworthiness of your friends. Associate with deadbeats, and you’re more likely to be judged as one.

Your associations can be used to judge you in other ways as well. It’s now common for employers to use social media sites to screen job applicants. This manual process is increasingly being outsourced and automated; companies like Social Intelligence, Evolv and First Advantage automatically process your social networking activity and provide hiring recommendations for employers. The dangers of this type of system—from discriminatory biases resulting from the data to an obsession with scores over more social measures—are too many.

The company Klout tried to make a business of measuring your online influence, hoping its proprietary system would become an industry standard used for things like hiring and giving out free product samples.

The US government is judging you as well. Your social media postings could get you on the terrorist watch list, affecting your ability to fly on an airplane and even get a job. In 2012, a British tourist’s tweet caused the US to deny him entry into the country. We know that the National Security Agency uses complex computer algorithms to sift through the Internet data it collects on both Americans and foreigners.

All of these systems, from Sesame Credit to the NSA’s secret algorithms, are made possible by computers and data. A couple of generations ago, you would apply for a home mortgage at a bank that knew you, and a bank manager would make a determination of your creditworthiness. Yes, the system was prone to all sorts of abuses, ranging from discrimination to an old-boy network of friends helping friends. But the system also couldn’t scale. It made no sense for a bank across the state to give you a loan, because they didn’t know you. Loans stayed local.

FICO scores changed that. Now, a computer crunches your credit history and produces a number. And you can take that number to any mortgage lender in the country. They don’t need to know you; your score is all they need to decide whether you’re trustworthy.

This score enabled the home mortgage, car loan, credit card and other lending industries to explode, but it brought with it other problems. People who don’t conform to the financial norm—having and using credit cards, for example—can have trouble getting loans when they need them. The automatic nature of the system enforces conformity.

The secrecy of the algorithms further pushes people toward conformity. If you are worried that the US government will classify you as a potential terrorist, you’re less likely to friend Muslims on Facebook. If you know that your Sesame Credit score is partly based on your not buying “subversive” products or being friends with dissidents, you’re more likely to overcompensate by not buying anything but the most innocuous books or corresponding with the most boring people.

Uber is an example of how this works. Passengers rate drivers and drivers rate passengers; both risk getting booted out of the system if their rankings get too low. This weeds out bad drivers and passengers, but also results in marginal people being blocked from the system, and everyone else trying to not make any special requests, avoid controversial conversation topics, and generally behave like good corporate citizens.

Many have documented a chilling effect among American Muslims, with them avoiding certain discussion topics lest they be taken the wrong way. Even if nothing would happen because of it, their free speech has been curtailed because of the secrecy surrounding government surveillance. How many of you are reluctant to Google “pressure cooker bomb”? How many are a bit worried that I used it in this essay?

This is what social control looks like in the Internet age. The Cold-War-era methods of undercover agents, informants living in your neighborhood, and agents provocateur is too labor-intensive and inefficient. These automatic algorithms make possible a wholly new way to enforce conformity. And by accepting algorithmic classification into our lives, we’re paving the way for the same sort of thing China plans to put into place.

It doesn’t have to be this way. We can get the benefits of automatic algorithmic systems while avoiding the dangers. It’s not even hard.

The first step is to make these algorithms public. Companies and governments both balk at this, fearing that people will deliberately try to game them, but the alternative is much worse.

The second step is for these systems to be subject to oversight and accountability. It’s already illegal for these algorithms to have discriminatory outcomes, even if they’re not deliberately designed in. This concept needs to be expanded. We as a society need to understand what we expect out of the algorithms that automatically judge us and ensure that those expectations are met.

We also need to provide manual systems for people to challenge their classifications. Automatic algorithms are going to make mistakes, whether it’s by giving us bad credit scores or flagging us as terrorists. We need the ability to clear our names if this happens, through a process that restores human judgment.

Sesame Credit sounds like a dystopia because we can easily imagine how the Chinese government can use a system like this to enforce conformity and stifle dissent. Our own systems seem safer, because we don’t believe the corporations and governments that run them are malevolent. But the dangers are inherent in the technologies. As we move into a world where we are increasingly judged by algorithms, we need to ensure that they do so fairly and properly.

This essay previously appeared on CNN.com.

Posted on January 8, 2016 at 5:21 AM • View Comments

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Sidebar photo of Bruce Schneier by Joe MacInnis.