An Anthropic Claude AI Model Finds Flaws in Tough-to-Crack Encryption Algorithms

A leading A.I. model built by Anthropic has found flaws in a weakened version of a digital encryption standard that is in pervasive use throughout the internet, the company’s researchers said Tuesday, underscoring the potential risks to global cybersecurity posed by ever-improving artificial intelligence software.

During a research-led test, the model, Claude Mythos Preview, was able to detect new ways to attack cryptographic algorithms that keep everything from online bank transactions to private communications to state secrets safe from the prying eyes of hackers or other unwanted third parties.

The research shows that A.I. could one day challenge core assumptions for how the internet operates. While experts say A.I. is likely to upend many industries, A.I. systems have made particularly rapid advancements in coding and cybersecurity.

The flaws identified do not concern a cryptographic standard currently in use today, which means that modern banking and communication systems are not subject to immediate potential intrusions from A.I. Instead, Anthropic’s technology cracked a watered-down version of an algorithm for Advanced Encryption Standard, or A.E.S., a ubiquitous protocol that safeguards web traffic, wireless networks, data storage and more.

It is common to perform tests on weaker versions of encryption algorithms to understand whether more powerful computers could someday crack the actual standards, akin to solving a simpler math problem to identify whether patterns may exist for a more complicated one. In the testing, Mythos was able to break the weaker version of Advanced Encryption Standard in a way that Anthropic said made an assault 200 to 1,000 times faster than what previous human research had managed to do.

While the immediate ramifications are minimal, the long-term implications could be significant. In previous tests, large-language models seemingly could not match or best what humans can do in the mathematically dense field of cryptographic research, but their rapid advances could suggest a future in which top models can surmount traditional internet security protections that are foundational to just about everything that takes place on the internet.