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.

ABTV

12/30/2019
07:00 AM
Larry Loeb
Larry Loeb
Larry Loeb
50%
50%

Mac Malware Breaks Into Top 5 Threats of 2019 – Malwarebytes Labs

Of the top 25 detections across all platforms, six were Mac threats, the researchers discovered.

Malwarebytes Labs has been checking its year-end lists to see what's been naughty and nice and there were a few surprises in it. They foundwhat they called a “startling upward trend” in the detection of Mac threats.

For the first time ever, Mac malware broke into the top five most-detected threats in the world.

What ML did is to look at the top detections across all platforms: Windows PCs, Macs and Android. They found that, "Of the top 25 detections, six of them were Mac threats. Overall, Mac threats accounted for more than 16 percent of total detections."

This may not sound impressive. Indeed, it may seem to be in line with the lower number of Macs that are in use. However, ML says that its Mac user base is about one twelfth the size of their Windows user base; which means that the 16% figure becomes fairly significant when compared to the overall sample's size.

They go on to say that the most interesting statistic that emerged from their data was how many Mac detections they saw per machine in 2019. On Windows, they saw 4.2 detections per device over the year. The Mac users, on the other hand, saw a yearly rate of 9.8 detections per device -- more than double the amount of detections when compared to Windows users.

Refreshingly, ML considered whether or not there was an inherent bias in these numbers. They wondered if the Macs that were represented by the data could have been machines that already had some kind of suspected infection, which is why Malwarebytes was installed in the first place. They realize that Mac users tend not to think that antivirus software of any kind is needed for their machines.

This leads the researchers to believe that "the overall threat detection rate for all Macs (and not just those with Malwarebytes installed) is likely not as high as this data sample."

But the detection ranked as the second-highest of 2019 is a Mac adware family known as NewTab. ML found it at around 4% of the overall detections across all platforms. NewTab is adware that uses browser extensions as a tool to modify the content of web pages. NewTab has been found to pose as an app, such as a flight tracker, maps/navigation, email access or tax form.

At 3% of the total detections there is fifth-placed PUP.PCVARK. These are a variety of potentially unwanted programs (PUPs), most of them clones of Advanced MacKeeper.

Standard "full-scope" malware does exist for the Mac but it tends to be more targeted or otherwise limited in effect. This year, both the Mokes and Wirenet malware targeted Mac users through a Firefox vulnerability. But it was only users at certain cryptocurrency companies that were targeted.

The upshot of this research is that Mac users should not be lulled into a false sense of invincibility against malware.

— Larry Loeb has written for many of the last century's major "dead tree" computer magazines, having been, among other things, a consulting editor for BYTE magazine and senior editor for the launch of WebWeek.

Comment  | 
Print  | 
More Insights
Comments
Newest First  |  Oldest First  |  Threaded View
COVID-19: Latest Security News & Commentary
Dark Reading Staff 9/25/2020
Hacking Yourself: Marie Moe and Pacemaker Security
Gary McGraw Ph.D., Co-founder Berryville Institute of Machine Learning,  9/21/2020
Startup Aims to Map and Track All the IT and Security Things
Kelly Jackson Higgins, Executive Editor at Dark Reading,  9/22/2020
Register for Dark Reading Newsletters
White Papers
Video
Cartoon
Current Issue
Special Report: Computing's New Normal
This special report examines how IT security organizations have adapted to the "new normal" of computing and what the long-term effects will be. Read it and get a unique set of perspectives on issues ranging from new threats & vulnerabilities as a result of remote working to how enterprise security strategy will be affected long term.
Flash Poll
How IT Security Organizations are Attacking the Cybersecurity Problem
How IT Security Organizations are Attacking the Cybersecurity Problem
The COVID-19 pandemic turned the world -- and enterprise computing -- on end. Here's a look at how cybersecurity teams are retrenching their defense strategies, rebuilding their teams, and selecting new technologies to stop the oncoming rise of online attacks.
Twitter Feed
Dark Reading - Bug Report
Bug Report
Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2020-15208
PUBLISHED: 2020-09-25
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can ...
CVE-2020-15209
PUBLISHED: 2020-09-25
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, a crafted TFLite model can force a node to have as input a tensor backed by a `nullptr` buffer. This can be achieved by changing a buffer index in the flatbuffer serialization to convert a read-only tensor to a read-write one....
CVE-2020-15210
PUBLISHED: 2020-09-25
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and ...
CVE-2020-15211
PUBLISHED: 2020-09-25
In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indices f...
CVE-2020-15212
PUBLISHED: 2020-09-25
In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to `segment_ids_data` can alter `output_index` and then write to outside of `outpu...