United Airlines was hacked by same Chinese group that also breached health insurer Anthem and the US government’s Office of Personnel Management (OPM).
Hackers stole flight manifests from United Airlines in May or early June, exposing the names of people on many different flights in the process, after earlier making off with up to 21.5 million Social Security Numbers from the OPM heist. Bloomberg broke news of the possible link on Wednesday in a story citing unnamed officials and individuals familiar with the investigation.
United declined to comment on the breach investigation. Zhu Haiquan, a spokesman for the Chinese embassy in Washington, issued a blanket denial that China engages in hacking. “The Chinese government and the personnel in its institutions never engage in any form of cyberattack. We firmly oppose and combat any forms of cyberattacks,” he said.
The report of links between the three high-profile attacks is light on details (most notably the tactics and techniques used to breach systems), but the implications run deep. Some independent experts even characterise the linked hacks as a potential game-changer in online espionage.
Ken Westin, senior security analyst at Tripwire, said that the run of attacks seems to show that state-sponsored hackers are upping the ante and going after a range of related targets in one fell swoop.
“If the evidence does reveal nexus points and attribution to a group, particularly a nation state, it would also reveal the disturbing motivation of the attackers,” Westin commented. “Instead of a campaign to breach a single entity, the goal was to compromise multiple disparate sets of data for the purposes of correlation. This correlation would allow the actors to develop targeted profiles of individuals in the United States, particularly those with security clearances, leading to one of the most devastating intelligence compromises we have seen to date.”
“Identifying individuals with security clearances and linking that data to travel information is one example of how the combination of this type of data can be exponentially more damaging than individual data sets alone,” he added. ®