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The Supreme Court Narrowed the CFAA

In a 6-3 ruling, the Supreme Court just narrowed the scope of the Computer Fraud and Abuse Act:

In a ruling delivered today, the court sided with Van Buren and overturned his 18-month conviction.

In a 37-page opinion written and delivered by Justice Amy Coney Barrett, the court explained that the “exceeds authorized access” language was, indeed, too broad.

Justice Barrett said the clause was effectively making criminals of most US citizens who ever used a work resource to perform unauthorized actions, such as updating a dating profile, checking sports scores, or paying bills at work.

What today’s ruling means is that the CFAA cannot be used to prosecute rogue employees who have legitimate access to work-related resources, which will need to be prosecuted under different charges.

The ruling does not apply to former employees accessing their old work systems because their access has been revoked and they’re not “authorized” to access those systems anymore.

More.

It’s a good ruling, and one that will benefit security researchers. But the confusing part is footnote 8:

For present purposes, we need not address whether this inquiry turns only on technological (or “code-based”) limitations on access, or instead also looks to limits contained in contracts or policies.

It seems to me that this is exactly what the ruling does address. The court overturned the conviction because the defendant was not limited by technology, but only by policies. So that footnote doesn’t make any sense.

I have written about this general issue before, in the context of adversarial machine learning research.

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Adversarial Machine Learning and the CFAA

I just co-authored a paper on the legal risks of doing machine learning research, given the current state of the Computer Fraud and Abuse Act:

Abstract: Adversarial Machine Learning is booming with ML researchers increasingly targeting commercial ML systems such as those used in Facebook, Tesla, Microsoft, IBM, Google to demonstrate vulnerabilities. In this paper, we ask, “What are the potential legal risks to adversarial ML researchers when they attack ML systems?” Studying or testing the security of any operational system potentially runs afoul the Computer Fraud and Abuse Act (CFAA), the primary United States federal statute that creates liability for hacking. We claim that Adversarial ML research is likely no different. Our analysis show that because there is a split in how CFAA is interpreted, aspects of adversarial ML attacks, such as model inversion, membership inference, model stealing, reprogramming the ML system and poisoning attacks, may be sanctioned in some jurisdictions and not penalized in others. We conclude with an analysis predicting how the US Supreme Court may resolve some present inconsistencies in the CFAA’s application in Van Buren v. United States, an appeal expected to be decided in 2021. We argue that the court is likely to adopt a narrow construction of the CFAA, and that this will actually lead to better adversarial ML security outcomes in the long term.

Medium post on the paper. News article, which uses our graphic without attribution.

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Cryptocurrency Pump and Dump Scams

Really interesting research: “An examination of the cryptocurrency pump and dump ecosystem“:

Abstract: The surge of interest in cryptocurrencies has been accompanied by a proliferation of fraud. This paper examines pump and dump schemes. The recent explosion of nearly 2,000 cryptocurrencies in an unregulated environment has expanded the scope for abuse. We quantify the scope of cryptocurrency pump and dump schemes on Discord and Telegram, two popular group-messaging platforms. We joined all relevant Telegram and Discord groups/channels and identified thousands of different pumps. Our findings provide the first measure of the scope of such pumps and empirically document important properties of this ecosystem.

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Clarifying the Computer Fraud and Abuse Act

A federal court has ruled that violating a website’s terms of service is not “hacking” under the Computer Fraud and Abuse Act.

The plaintiffs wanted to investigate possible racial discrimination in online job markets by creating accounts for fake employers and job seekers. Leading job sites have terms of service prohibiting users from supplying fake information, and the researchers worried that their research could expose them to criminal liability under the CFAA, which makes it a crime to “access a computer without authorization or exceed authorized access.”

So in 2016 they sued the federal government, seeking a declaration that this part of the CFAA violated the First Amendment.

But rather than addressing that constitutional issue, Judge John Bates ruled on Friday that the plaintiffs’ proposed research wouldn’t violate the CFAA’s criminal provisions at all. Someone violates the CFAA when they bypass an access restriction like a password. But someone who logs into a website with a valid password doesn’t become a hacker simply by doing something prohibited by a website’s terms of service, the judge concluded.

“Criminalizing terms-of-service violations risks turning each website into its own criminal jurisdiction and each webmaster into his own legislature,” Bates wrote.

Bates noted that website terms of service are often long, complex, and change frequently. While some websites require a user to read through the terms and explicitly agree to them, others merely include a link to the terms somewhere on the page. As a result, most users aren’t even aware of the contractual terms that supposedly govern the site. Under those circumstances, it’s not reasonable to make violation of such terms a criminal offense, Bates concluded.

This is not the first time a court has issued a ruling in this direction. It’s also not the only way the courts have interpreted the frustratingly vague Computer Fraud and Abuse Act.

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SIM Hijacking

SIM hijacking — or SIM swapping — is an attack where a fraudster contacts your cell phone provider and convinces them to switch your account to a phone that they control. Since your smartphone often serves as a security measure or backup verification system, this allows the fraudster to take over other accounts of yours. Sometimes this involves people inside the phone companies.

Phone companies have added security measures since this attack became popular and public, but a new study (news article) shows that the measures aren’t helping:

We examined the authentication procedures used by five pre-paid wireless carriers when a customer attempted to change their SIM card. These procedures are an important line of defense against attackers who seek to hijack victims’ phone numbers by posing as the victim and calling the carrier to request that service be transferred to a SIM card the attacker possesses. We found that all five carriers used insecure authentication challenges that could be easily subverted by attackers.We also found that attackers generally only needed to target the most vulnerable authentication challenges, because the rest could be bypassed.

It’s a classic security vs. usability trade-off. The phone companies want to provide easy customer service for their legitimate customers, and that system is what’s being exploited by the SIM hijackers. Companies could make the fraud harder, but it would necessarily also make it harder for legitimate customers to modify their accounts.

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Chrome Extension Stealing Cryptocurrency Keys and Passwords

A malicious Chrome extension surreptitiously steals Ethereum keys and passwords:

According to Denley, the extension is dangerous to users in two ways. First, any funds (ETH coins and ERC0-based tokens) managed directly inside the extension are at risk.

Denley says that the extension sends the private keys of all wallets created or managed through its interface to a third-party website located at erc20wallet[.]tk.

Second, the extension also actively injects malicious JavaScript code when users navigate to five well-known and popular cryptocurrency management platforms. This code steals login credentials and private keys, data that it’s sent to the same erc20wallet[.]tk third-party website.

Another example of how blockchain requires many single points of trust in order to be secure.

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The Story of Tiversa

The New Yorker has published the long and interesting story of the cybersecurity firm Tiversa.

Watching “60 Minutes,” Boback saw a remarkable new business angle. Here was a multibillion-dollar industry with a near-existential problem and no clear solution. He did not know it then, but, as he turned the opportunity over in his mind, he was setting in motion a sequence of events that would earn him millions of dollars, friendships with business élites, prime-time media attention, and respect in Congress. It would also place him at the center of one of the strangest stories in the brief history of cybersecurity; he would be mired in lawsuits, countersuits, and counter-countersuits, which would gather into a vortex of litigation so ominous that one friend compared it to the Bermuda Triangle. He would be accused of fraud, of extortion, and of manipulating the federal government into harming companies that did not do business with him. Congress would investigate him. So would the F.B.I.

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Details of an Airbnb Fraud

This is a fascinating article about a bait-and-switch Airbnb fraud. The article focuses on one particular group of scammers and how they operate, using the fact that Airbnb as a company doesn’t do much to combat fraud on its platform. But I am more interested in how the fraudsters essentially hacked the complex sociotechnical system that is Airbnb.

The whole article is worth reading.

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Fabricated Voice Used in Financial Fraud

This seems to be an identity theft first:

Criminals used artificial intelligence-based software to impersonate a chief executive’s voice and demand a fraudulent transfer of €220,000 ($243,000) in March in what cybercrime experts described as an unusual case of artificial intelligence being used in hacking.

Another news article.

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