Apple has encountered monumental backlash to a new child sexual abuse imagery (CSAM) detection technology it announced earlier this month. The system, which Apple calls NeuralHash, has yet to be activated for its billion-plus users, but the technology is already facing heat from security researchers who say the algorithm is producing flawed results.
NeuralHash is designed to identify known CSAM on a user’s device without having to possess the image or knowing the contents of the image. Because a user’s photos stored in iCloud are end-to-end encrypted so that even Apple can’t access the data, NeuralHash instead scans for known CSAM on a user’s device, which Apple claims is more privacy friendly as it limits the scanning to just photos rather than other companies which scan all of a user’s file.
Apple does this by looking for images on a user’s device that have the same hash — a string of letters and numbers that can uniquely identify an image — that are provided by child protection organizations like NCMEC. If NeuralHash finds 30 or more matching hashes, the images are flagged to Apple for a manual review before the account owner is reported to law enforcement. Apple says the chance of a false positive is about one in one trillion accounts.
But security experts and privacy advocates have expressed concern that the system could be abused by highly-resourced actors, like governments, to implicate innocent victims or to manipulate the system to detect other materials that authoritarian nation states find objectionable. NCMEC called critics the “screeching voices of the minority,” according to a leaked memo distributed internally to Apple staff.
Last night, Asuhariet Ygvar reverse-engineered Apple’s NeuralHash into a Python script and published code to GitHub, allowing anyone to test the technology regardless of whether they have an Apple device to test. In a Reddit post, Ygvar said NeuralHash “already exists” in iOS 14.3 as obfuscated code, but was able to reconstruct the technology to help other security researchers understand the algorithm better before it’s rolled out to iOS and macOS devices later this year.
It didn’t take long before others tinkered with the published code and soon came the first reported case of a “hash collision,” which in NeuralHash’s case is where two entirely different images produce the same hash. Cory Cornelius, a well-known research scientist at Intel Labs, discovered the hash collision. Ygvar confirmed the collision a short time later.
Hash collisions can be a death knell to systems that rely on cryptography to keep them secure, such as encryption. Over the years several well-known password hashing algorithms, like MD5 and SHA-1, were retired after collision attacks rendered them ineffective.
Kenneth White, a cryptography expert and founder of the Open Crypto Audit Project, said in a tweet: “I think some people aren’t grasping that the time between the iOS NeuralHash code being found and [the] first collision was not months or days, but a couple of hours.”
When reached, an Apple spokesperson declined to comment on the record. But in a background call where reporters were not allowed to quote executives directly or by name, Apple downplayed the hash collision and argued that the protections it puts in place — such as a manual review of photos before they are reported to law enforcement — are designed to prevent abuses. Apple also said that the version of NeuralHash that was reverse-engineered is a generic version, and not the complete version that will roll out later this year.
It’s not just civil liberties groups and security experts that are expressing concern about the technology. A senior lawmaker in the German parliament sent a letter to Apple chief executive Tim Cook this week saying that the company is walking down a “dangerous path” and urged Apple not to implement the system.
