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It seems that someone from a company called Swift Recovery Ltd. is impersonating me—at least on Telegram. The person is using a photo of me, and is using details of my life available on Wikipedia to convince people that they are me.
They are not.
If anyone has any more information—stories, screen shots of chats, etc.—please forward them to me.
In Gmail addresses, the dots don’t matter. The account “bruceschneier@gmail.com” maps to the exact same address as “bruce.schneier@gmail.com” and “b.r.u.c.e.schneier@gmail.com”—and so on. (Note: I own none of those addresses, if they are actually valid.)
This fact can be used to commit fraud:
Recently, we observed a group of BEC actors make extensive use of Gmail dot accounts to commit a large and diverse amount of fraud. Since early 2018, this group has used this fairly simple tactic to facilitate the following fraudulent activities:
- Submit 48 credit card applications at four US-based financial institutions, resulting in the approval of at least $65,000 in fraudulent credit
- Register for 14 trial accounts with a commercial sales leads service to collect targeting data for BEC attacks
- File 13 fraudulent tax returns with an online tax filing service
- Submit 12 change of address requests with the US Postal Service
- Submit 11 fraudulent Social Security benefit applications
- Apply for unemployment benefits under nine identities in a large US state
- Submit applications for FEMA disaster assistance under three identities
In each case, the scammers created multiple accounts on each website within a short period of time, modifying the placement of periods in the email address for each account. Each of these accounts is associated with a different stolen identity, but all email from these services are received by the same Gmail account. Thus, the group is able to centralize and organize their fraudulent activity around a small set of email accounts, thereby increasing productivity and making it easier to continue their fraudulent behavior.
This isn’t a new trick. It has been previously documented as a way to trick Netflix users.
News article.
Slashdot thread.
This is clever:
How the attack works:
- Attacker added tens of malicious servers to the Electrum wallet network.
- Users of legitimate Electrum wallets initiate a Bitcoin transaction.
- If the transaction reaches one of the malicious servers, these servers reply with an error message that urges users to download a wallet app update from a malicious website (GitHub repo).
- User clicks the link and downloads the malicious update.
- When the user opens the malicious Electrum wallet, the app asks the user for a two-factor authentication (2FA) code. This is a red flag, as these 2FA codes are only requested before sending funds, and not at wallet startup.
- The malicious Electrum wallet uses the 2FA code to steal the user’s funds and transfer them to the attacker’s Bitcoin addresses.
The problem here is that Electrum servers are allowed to trigger popups with custom text inside users’ wallets.
This is a really interesting story of an ad fraud scheme that relied on hijacking the Border Gateway Protocol:
Members of 3ve (pronounced “eve”) used their large reservoir of trusted IP addresses to conceal a fraud that otherwise would have been easy for advertisers to detect. The scheme employed a thousand servers hosted inside data centers to impersonate real human beings who purportedly “viewed” ads that were hosted on bogus pages run by the scammers themselves—who then received a check from ad networks for these billions of fake ad impressions. Normally, a scam of this magnitude coming from such a small pool of server-hosted bots would have stuck out to defrauded advertisers. To camouflage the scam, 3ve operators funneled the servers’ fraudulent page requests through millions of compromised IP addresses.
About one million of those IP addresses belonged to computers, primarily based in the US and the UK, that attackers had infected with botnet software strains known as Boaxxe and Kovter. But at the scale employed by 3ve, not even that number of IP addresses was enough. And that’s where the BGP hijacking came in. The hijacking gave 3ve a nearly limitless supply of high-value IP addresses. Combined with the botnets, the ruse made it seem like millions of real people from some of the most affluent parts of the world were viewing the ads.
Lots of details in the article.
An aphorism I often use in my talks is “expertise flows downhill: today’s top-secret NSA programs become tomorrow’s PhD theses and the next day’s hacking tools.” This is an example of that. BGP hacking—known as “traffic shaping” inside the NSA—has long been a tool of national intelligence agencies. Now it is being used by cybercriminals.
EDITED TO ADD (1/2): Classified NSA presentation on “network shaping.” I don’t know if there is a difference inside the NSA between the two terms.
Fascinating article about the many ways Amazon Marketplace sellers sabotage each other and defraud customers. The opening example: framing a seller for false advertising by buying fake five-star reviews for their products.
Defacement: Sellers armed with the accounts of Amazon distributors (sometimes legitimately, sometimes through the black market) can make all manner of changes to a rival’s listings, from changing images to altering text to reclassifying a product into an irrelevant category, like “sex toys.”
Phony fires: Sellers will buy their rival’s product, light it on fire, and post a picture to the reviews, claiming it exploded. Amazon is quick to suspend sellers for safety claims.
[…]
Over the following days, Harris came to realize that someone had been targeting him for almost a year, preparing an intricate trap. While he had trademarked his watch and registered his brand, Dead End Survival, with Amazon, Harris hadn’t trademarked the name of his Amazon seller account, SharpSurvival. So the interloper did just that, submitting to the patent office as evidence that he owned the goods a photo taken from Harris’ Amazon listings, including one of Harris’ own hands lighting a fire using the clasp of his survival watch. The hijacker then took that trademark to Amazon and registered it, giving him the power to kick Harris off his own listings and commandeer his name.
[…]
There are more subtle methods of sabotage as well. Sellers will sometimes buy Google ads for their competitors for unrelated products—say, a dog food ad linking to a shampoo listing—so that Amazon’s algorithm sees the rate of clicks converting to sales drop and automatically demotes their product.
What’s also interesting is how Amazon is basically its own government—with its own rules that its suppliers have no choice but to follow. And, of course, increasingly there is no option but to sell your stuff on Amazon.
The FBI announced that it dismantled a large Internet advertising fraud network, and arrested eight people:
A 13-count indictment was unsealed today in federal court in Brooklyn charging Aleksandr Zhukov, Boris Timokhin, Mikhail Andreev, Denis Avdeev, Dmitry Novikov, Sergey Ovsyannikov, Aleksandr Isaev and Yevgeniy Timchenko with criminal violations for their involvement in perpetrating widespread digital advertising fraud. The charges include wire fraud, computer intrusion, aggravated identity theft and money laundering. Ovsyannikov was arrested last month in Malaysia; Zhukov was arrested earlier this month in Bulgaria; and Timchenko was arrested earlier this month in Estonia, all pursuant to provisional arrest warrants issued at the request of the United States. They await extradition. The remaining defendants are at large.
It looks like an impressive piece of police work.
Details of the forensics that led to the arrests.
On November 4, 2016, the hacker “Guccifer 2.0,” a front for Russia’s military intelligence service, claimed in a blogpost that the Democrats were likely to use vulnerabilities to hack the presidential elections. On November 9, 2018, President Donald Trump started tweeting about the senatorial elections in Florida and Arizona. Without any evidence whatsoever, he said that Democrats were trying to steal the election through “FRAUD.”
Cybersecurity experts would say that posts like Guccifer 2.0’s are intended to undermine public confidence in voting: a cyber-attack against the US democratic system. Yet Donald Trump’s actions are doing far more damage to democracy. So far, his tweets on the topic have been retweeted over 270,000 times, eroding confidence far more effectively than any foreign influence campaign.
We need new ideas to explain how public statements on the Internet can weaken American democracy. Cybersecurity today is not only about computer systems. It’s also about the ways attackers can use computer systems to manipulate and undermine public expectations about democracy. Not only do we need to rethink attacks against democracy; we also need to rethink the attackers as well.
This is one key reason why we wrote a new research paper which uses ideas from computer security to understand the relationship between democracy and information. These ideas help us understand attacks which destabilize confidence in democratic institutions or debate.
Our research implies that insider attacks from within American politics can be more pernicious than attacks from other countries. They are more sophisticated, employ tools that are harder to defend against, and lead to harsh political tradeoffs. The US can threaten charges or impose sanctions when Russian trolling agencies attack its democratic system. But what punishments can it use when the attacker is the US president?
People who think about cybersecurity build on ideas about confrontations between states during the Cold War. Intellectuals such as Thomas Schelling developed deterrence theory, which explained how the US and USSR could maneuver to limit each other’s options without ever actually going to war. Deterrence theory, and related concepts about the relative ease of attack and defense, seemed to explain the tradeoffs that the US and rival states faced, as they started to use cyber techniques to probe and compromise each others’ information networks.
However, these ideas fail to acknowledge one key differences between the Cold War and today. Nearly all states—whether democratic or authoritarian—are entangled on the Internet. This creates both new tensions and new opportunities. The US assumed that the internet would help spread American liberal values, and that this was a good and uncontroversial thing. Illiberal states like Russia and China feared that Internet freedom was a direct threat to their own systems of rule. Opponents of the regime might use social media and online communication to coordinate among themselves, and appeal to the broader public, perhaps toppling their governments, as happened in Tunisia during the Arab Spring.
This led illiberal states to develop new domestic defenses against open information flows. As scholars like Molly Roberts have shown, states like China and Russia discovered how they could "flood" internet discussion with online nonsense and distraction, making it impossible for their opponents to talk to each other, or even to distinguish between truth and falsehood. These flooding techniques stabilized authoritarian regimes, because they demoralized and confused the regime’s opponents. Libertarians often argue that the best antidote to bad speech is more speech. What Vladimir Putin discovered was that the best antidote to more speech was bad speech.
Russia saw the Arab Spring and efforts to encourage democracy in its neighborhood as direct threats, and began experimenting with counter-offensive techniques. When a Russia-friendly government in Ukraine collapsed due to popular protests, Russia tried to destabilize new, democratic elections by hacking the system through which the election results would be announced. The clear intention was to discredit the election results by announcing fake voting numbers that would throw public discussion into disarray.
This attack on public confidence in election results was thwarted at the last moment. Even so, it provided the model for a new kind of attack. Hackers don’t have to secretly alter people’s votes to affect elections. All they need to do is to damage public confidence that the votes were counted fairly. As researchers have argued, “simply put, the attacker might not care who wins; the losing side believing that the election was stolen from them may be equally, if not more, valuable.”
These two kinds of attacks—”flooding” attacks aimed at destabilizing public discourse, and “confidence” attacks aimed at undermining public belief in elections—were weaponized against the US in 2016. Russian social media trolls, hired by the “Internet Research Agency,” flooded online political discussions with rumors and counter-rumors in order to create confusion and political division. Peter Pomerantsev describes how in Russia, “one moment [Putin’s media wizard] Surkov would fund civic forums and human rights NGOs, the next he would quietly support nationalist movements that accuse the NGOs of being tools of the West.” Similarly, Russian trolls tried to get Black Lives Matter protesters and anti-Black Lives Matter protesters to march at the same time and place, to create conflict and the appearance of chaos. Guccifer 2.0’s blog post was surely intended to undermine confidence in the vote, preparing the ground for a wider destabilization campaign after Hillary Clinton won the election. Neither Putin nor anyone else anticipated that Trump would win, ushering in chaos on a vastly greater scale.
We do not know how successful these attacks were. A new book by John Sides, Michael Tesler and Lynn Vavreck suggests that Russian efforts had no measurable long-term consequences. Detailed research on the flow of news articles through social media by Yochai Benker, Robert Farris, and Hal Roberts agrees, showing that Fox News was far more influential in the spread of false news stories than any Russian effort.
However, global adversaries like the Russians aren’t the only actors who can use flooding and confidence attacks. US actors can use just the same techniques. Indeed, they can arguably use them better, since they have a better understanding of US politics, more resources, and are far more difficult for the government to counter without raising First Amendment issues.
For example, when the Federal Communication Commission asked for comments on its proposal to get rid of “net neutrality,” it was flooded by fake comments supporting the proposal. Nearly every real person who commented was in favor of net neutrality, but their arguments were drowned out by a flood of spurious comments purportedly made by identities stolen from porn sites, by people whose names and email addresses had been harvested without their permission, and, in some cases, from dead people. This was done not just to generate fake support for the FCC’s controversial proposal. It was to devalue public comments in general, making the general public’s support for net neutrality politically irrelevant. FCC decision making on issues like net neutrality used to be dominated by industry insiders, and many would like to go back to the old regime.
Trump’s efforts to undermine confidence in the Florida and Arizona votes work on a much larger scale. There are clear short-term benefits to asserting fraud where no fraud exists. This may sway judges or other public officials to make concessions to the Republicans to preserve their legitimacy. Yet they also destabilize American democracy in the long term. If Republicans are convinced that Democrats win by cheating, they will feel that their own manipulation of the system (by purging voter rolls, making voting more difficult and so on) are legitimate, and very probably cheat even more flagrantly in the future. This will trash collective institutions and leave everyone worse off.
It is notable that some Arizonan Republicans—including Martha McSally—have so far stayed firm against pressure from the White House and the Republican National Committee to claim that cheating is happening. They presumably see more long term value from preserving existing institutions than undermining them. Very plausibly, Donald Trump has exactly the opposite incentives. By weakening public confidence in the vote today, he makes it easier to claim fraud and perhaps plunge American politics into chaos if he is defeated in 2020.
If experts who see Russian flooding and confidence measures as cyberattacks on US democracy are right, then these attacks are just as dangerous—and perhaps more dangerous—when they are used by domestic actors. The risk is that over time they will destabilize American democracy so that it comes closer to Russia’s managed democracy—where nothing is real any more, and ordinary people feel a mixture of paranoia, helplessness and disgust when they think about politics. Paradoxically, Russian interference is far too ineffectual to get us there—but domestically mounted attacks by all-American political actors might.
To protect against that possibility, we need to start thinking more systematically about the relationship between democracy and information. Our paper provides one way to do this, highlighting the vulnerabilities of democracy against certain kinds of information attack. More generally, we need to build levees against flooding while shoring up public confidence in voting and other public information systems that are necessary to democracy.
The first may require radical changes in how we regulate social media companies. Modernization of government commenting platforms to make them robust against flooding is only a very minimal first step. Up until very recently, companies like Twitter have won market advantage from bot infestations—even when it couldn’t make a profit, it seemed that user numbers were growing. CEOs like Mark Zuckerberg have begun to worry about democracy, but their worries will likely only go so far. It is difficult to get a man to understand something when his business model depends on not understanding it. Sharp—and legally enforceable—limits on automated accounts are a first step. Radical redesign of networks and of trending indicators so that flooding attacks are less effective may be a second.
The second requires general standards for voting at the federal level, and a constitutional guarantee of the right to vote. Technical experts nearly universally favor robust voting systems that would combine paper records with random post-election auditing, to prevent fraud and secure public confidence in voting. Other steps to ensure proper ballot design, and standardize vote counting and reporting will take more time and discussion—yet the record of other countries show that they are not impossible.
The US is nearly unique among major democracies in the persistent flaws of its election machinery. Yet voting is not the only important form of democratic information. Apparent efforts to deliberately skew the US census against counting undocumented immigrants show the need for a more general audit of the political information systems that we need if democracy is to function properly.
It’s easier to respond to Russian hackers through sanctions, counter-attacks and the like than to domestic political attacks that undermine US democracy. To preserve the basic political freedoms of democracy requires recognizing that these freedoms are sometimes going to be abused by politicians such as Donald Trump. The best that we can do is to minimize the possibilities of abuse up to the point where they encroach on basic freedoms and harden the general institutions that secure democratic information against attacks intended to undermine them.
This essay was co-authored with Henry Farrell, and previously appeared on Motherboard, with a terrible headline that I was unable to get changed.
A new study finds that credit card fraud has not declined since the introduction of chip cards in the US. The majority of stolen card information comes from hacked point-of-sale terminals.
The reasons seem to be twofold. One, the US uses chip-and-signature instead of chip-and-PIN, obviating the most critical security benefit of the chip. And two, US merchants still accept magnetic stripe cards, meaning that thieves can steal credentials from a chip card and create a working cloned mag stripe card.
Boing Boing post.
This story nicely illustrates the arms race between technologies to create fake videos and technologies to detect fake videos:
These fakes, while convincing if you watch a few seconds on a phone screen, aren’t perfect (yet). They contain tells, like creepily ever-open eyes, from flaws in their creation process. In looking into DeepFake’s guts, Lyu realized that the images that the program learned from didn’t include many with closed eyes (after all, you wouldn’t keep a selfie where you were blinking, would you?). “This becomes a bias,” he says. The neural network doesn’t get blinking. Programs also might miss other “physiological signals intrinsic to human beings,” says Lyu’s paper on the phenomenon, such as breathing at a normal rate, or having a pulse. (Autonomic signs of constant existential distress are not listed.) While this research focused specifically on videos created with this particular software, it is a truth universally acknowledged that even a large set of snapshots might not adequately capture the physical human experience, and so any software trained on those images may be found lacking.
Lyu’s blinking revelation revealed a lot of fakes. But a few weeks after his team put a draft of their paper online, they got anonymous emails with links to deeply faked YouTube videos whose stars opened and closed their eyes more normally. The fake content creators had evolved.
I don’t know who will win this arms race, if there ever will be a winner. But the problem with fake videos goes deeper: they affect people even if they are later told that they are fake, and there always will be people that will believe they are real, despite any evidence to the contrary.
BuzzFeed is reporting on a scheme where fraudsters buy legitimate Android apps, track users’ behavior in order to mimic it in a way that evades bot detectors, and then uses bots to perpetuate an ad-fraud scheme.
After being provided with a list of the apps and websites connected to the scheme, Google investigated and found that dozens of the apps used its mobile advertising network. Its independent analysis confirmed the presence of a botnet driving traffic to websites and apps in the scheme. Google has removed more than 30 apps from the Play store, and terminated multiple publisher accounts with its ad networks. Google said that prior to being contacted by BuzzFeed News it had previously removed 10 apps in the scheme and blocked many of the websites. It continues to investigate, and published a blog post to detail its findings.
The company estimates this operation stole close to $10 million from advertisers who used Google’s ad network to place ads in the affected websites and apps. It said the vast majority of ads being placed in these apps and websites came via other major ad networks.
Lots of details in both the BuzzFeed and the Google links.
The Internet advertising industry is rife with fraud, at all levels. This is just one scheme among many.
Sidebar photo of Bruce Schneier by Joe MacInnis.