Online researchers say they have found flaws in Apple’s new child abuse detection tool that could allow bad actors to target iOS users. However, Apple has denied these claims, arguing that it has intentionally built safeguards against such exploitation.

It’s just the latest bump in the road for the rollout of the company’s new features, which have been roundly criticized by privacy and civil liberties advocates since they were initially announced two weeks ago. Many critics view the updates—which are built to scour iPhones and other iOS products for signs of child sexual abuse material (CSAM)—as a slippery slope towards broader surveillance.

The most recent criticism centers around allegations that Apple’s “NeuralHash” technology—which scans for the bad images—can be exploited and tricked to potentially target users. This started because online researchers dug up and subsequently shared code for NeuralHash as a way to better understand it. One Github user, AsuharietYgvar, claims to have reverse-engineered the scanning tech’s algorithm and published the code to his page. Ygvar wrote in a Reddit post that the algorithm was basically available in iOS 14.3 as obfuscated code and that he had taken the code and rebuilt it in a Python script to assemble a clearer picture of how it worked.

Problematically, within a couple of hours, another researcher said they were able to use the posted code to trick the system into misidentifying an image, creating what is called a “hash collision.”

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However, “hash collisions” involve a situation in which two totally different images produce the same “hash” or signature. In the context of Apple’s new tools, this has the potential to create a false-positive, potentially implicating an innocent person for having child porn, critics claim. The false-positive could be accidental or intentionally triggered by a malicious actor.

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ost alarmingly, researchers noted that it could be easily co-opted by a government or other powerful entity, which might repurpose its surveillance tech to look for other kinds of content. “Our system could easily be repurposed for surveillance and censorship,” writes Mayer and his research partner, Anunay Kulshrestha, in an op-ed in the Washington Post. “The design wasn’t restricted to a specific category of content; a service could simply swap in any content-matching data base, and the person using that service would be none the wiser.”

The researchers were “so disturbed” by their findings that they subsequently declared the system dangerous, and warned that it shouldn’t be adopted by a company or organization until more research could be done to curtail the potential dangers it presented. However, not long afterward, Apple announced its plans to roll out a nearly identical system to over 1.5 billion devices in an effort to scan for CSAM. The op-ed ultimately notes that Apple is “gambling with security, privacy and free speech worldwide” by implementing a similar system in such a hasty, slapdash way.

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pple’s decision to launch such an invasive technology so swiftly and unthinkingly is a major liability for consumers. The fact that Apple says it has built safety nets around this feature is not comforting at all, he added.

“You can always build safety nets underneath a broken system,” said Green, noting that it doesn’t ultimately fix the problem. “I have a lot of issues with this [new system]. I don’t think it’s something that we should be jumping into—this idea that local files on your device will be scanned.” Green further affirmed the idea that Apple had rushed this experimental system into production, comparing it to an untested airplane whose engines are held together via duct tape. “It’s like Apple has decided we’re all going to go on this airplane and we’re going to fly. Don’t worry [they say], the airplane has parachutes,” he said.

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Source: Apple’s Not Digging Itself Out of This One

In a new blog post for the International Monetary Fund, four researchers presented their findings from a working paper that examines the current relationship between finance and tech as well as its potential future. Gazing into their crystal ball, the researchers see the possibility of using the data from your browsing, search, and purchase history to create a more accurate mechanism for determining the credit rating of an individual or business. They believe that this approach could result in greater lending to borrowers who would potentially be denied by traditional financial institutions. At its heart, the paper is trying to wrestle with the dawning notion that the institutional banking system is facing a serious threat from tech companies like Google, Facebook, and Apple. The researchers identify two key areas in which this is true: Tech companies have greater access to soft-information, and messaging platforms can take the place of the physical locations that banks rely on for meeting with customers.

The concept of using your web history to inform credit ratings is framed around the notion that lenders rely on hard-data that might obscure the worthiness of a borrower or paint an unnecessarily dire picture during hard times. Citing soft-data points like “the type of browser and hardware used to access the internet, the history of online searches and purchases” that could be incorporated into evaluating a borrower, the researchers believe that when a lender has a more intimate relationship with the potential client’s history, they might be more willing to cut them some slack. […] But how would all this data be incorporated into credit ratings? Machine learning, of course. It’s black boxes all the way down. The researchers acknowledge that there will be privacy and policy concerns related to incorporating this kind of soft-data into credit analysis. And they do little to explain how this might work in practice.

Source: Your Credit Score Should Be Based On Your Web History, IMF Says – Slashdot

So now the banks want your browsing history. They don’t want to miss out on the surveillance economy.