Dark Reading is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them.Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

Endpoint Security

11/15/2017
04:38 PM
Curtis Franklin
Curtis Franklin
Curt Franklin
50%
50%

iPhone's Facial Recognition Shows Cracks

A research firm says that it has successfully spoofed the facial recognition technology used in Apple's flagship iPhone X.

Multi-factor authentication is becoming a "must" for many applications but questions remain about which factors are secure. A recent report from researchers in Vietnam has cast doubts on one promising new factor now available to millions.

In September, Apple announced the iPhone X with much fanfare and a flurry of new technology components. One of the most discussed is its facial recognition technology, which Apple has touted as being convenient, low-friction and very, very secure. Bkav, a security firm based in Vietnam, doesn't dispute the first two qualities but says that the security aspect may be somewhat over-stated.

In a test, researchers at Bkav said that they were able to defeat the iPhone X's facial recognition technology -- technology that Apple claims is not vulnerable to spoofing or mistaken identity -- using a mask made with approximately $150 in materials. While the spoof has yet to be confirmed by other researchers, the possibility raises some discomfiting possibilities.

The most troubling aspect of the demonstration is that the spoof was pulled off using a mask, after Apple went to great pains to show that their technology would only work with the living face of the device owner. In a blog post, Bkav said that they listened carefully to Apple's statements, worked to understand the AI used in the facial-recognition software, and found a vulnerability.

In a statement announcing the vulnerability, Ngo Tuan Anh, Bkav's Vice President of Cyber Security, said: "Achilles' heel here is Apple let AI at the same time learn a lot of real faces and masks made by Hollywood's and artists. In that way, Apple's AI can only distinguish either a 100% real face or a 100% fake one. So if you create a 'half-real half-fake' face, it can fool Apple's AI".

It has been pointed out that building the mask was not easy, requiring 3D scans of the owner's face, high-resolution 3D printing and multiple attempts to get the spoof right. That means that this is not a vulnerability likely to be used in any common scenario.

In the world of serious cybersecurity, though, unlikely is still possible and that's enough to take a technology out of the candidate pool for security covering high-value individuals and data. For most consumers (and for many users in business scenarios) the facial recognition technology in the iPhone X could be good enough. Before it can be considered a real replacement for more proven multi-factor authentication, though, the facial recognition technology may need more time to mature and improve.

Related posts:

— Curtis Franklin is the editor of SecurityNow.com. Follow him on Twitter @kg4gwa.

Comment  | 
Print  | 
More Insights
Comments
Newest First  |  Oldest First  |  Threaded View
Cloud Security Threats for 2021
Or Azarzar, CTO & Co-Founder of Lightspin,  12/3/2020
Why Vulnerable Code Is Shipped Knowingly
Chris Eng, Chief Research Officer, Veracode,  11/30/2020
Register for Dark Reading Newsletters
White Papers
Video
Cartoon Contest
Write a Caption, Win an Amazon Gift Card! Click Here
Latest Comment: This comment is waiting for review by our moderators.
Current Issue
2021 Top Enterprise IT Trends
We've identified the key trends that are poised to impact the IT landscape in 2021. Find out why they're important and how they will affect you today!
Flash Poll
Assessing Cybersecurity Risk in Todays Enterprises
Assessing Cybersecurity Risk in Todays Enterprises
COVID-19 has created a new IT paradigm in the enterprise and a new level of cybersecurity risk. This report offers a look at how enterprises are assessing and managing cyber-risk under the new normal.
Twitter Feed
Dark Reading - Bug Report
Bug Report
Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2020-27772
PUBLISHED: 2020-12-04
A flaw was found in ImageMagick in coders/bmp.c. An attacker who submits a crafted file that is processed by ImageMagick could trigger undefined behavior in the form of values outside the range of type `unsigned int`. This would most likely lead to an impact to application availability, but could po...
CVE-2020-27773
PUBLISHED: 2020-12-04
A flaw was found in ImageMagick in MagickCore/gem-private.h. An attacker who submits a crafted file that is processed by ImageMagick could trigger undefined behavior in the form of values outside the range of type `unsigned char` or division by zero. This would most likely lead to an impact to appli...
CVE-2020-28950
PUBLISHED: 2020-12-04
The installer of Kaspersky Anti-Ransomware Tool (KART) prior to KART 4.0 Patch C was vulnerable to a DLL hijacking attack that allowed an attacker to elevate privileges during installation process.
CVE-2020-27774
PUBLISHED: 2020-12-04
A flaw was found in ImageMagick in MagickCore/statistic.c. An attacker who submits a crafted file that is processed by ImageMagick could trigger undefined behavior in the form of a too large shift for 64-bit type `ssize_t`. This would most likely lead to an impact to application availability, but co...
CVE-2020-27775
PUBLISHED: 2020-12-04
A flaw was found in ImageMagick in MagickCore/quantum.h. An attacker who submits a crafted file that is processed by ImageMagick could trigger undefined behavior in the form of values outside the range of type unsigned char. This would most likely lead to an impact to application availability, but c...