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.

Vulnerabilities / Threats

Americans Rank Criminal Hacking as Their Number One Threat

Global warming and artificial intelligence rate as less of a threat to human health, safety, and prosperity, than getting hacked, according to a survey released today.

Criminal hacking is the greatest threat to Americans' well-being, according to a new survey that found it outranks air pollution, motor vehicle accidents, and artificial intelligence.

The online random survey conducted by ESET, which queried 740 American respondents via SurveyMonkey, asked participants to rate 15 types of risks, from "no risk at all" to "very high risk," as it relates to human health, safety, or prosperity. The participants were left to interpret their own definition of criminal hacking, says Stephen Cobb, ESET senior security researcher.

Criminal hacking scored a weighted average of 5.41, compared to the survey's overall weighted average of 4.92. Not far behind hacking in the rankings was air pollution, with a rating of 5.33, and disposal of hazardous waste in landfills at 5.24.

"It's pure speculation on my part as to why criminal hacking was rated the highest, but one suggestion is criminals breaking into computers is a more immediate threat," Cobb says. "Maybe the headlines in the news also made a difference. The survey was done right after WannaCry and NotPetya."

"One takeaway for enterprises looking at these results is that criminal hacking as a threat to the general well-being of Americans is right up there in Americans' consciousness. This signals to companies that they need to take security seriously," Cobb warns.

Age and Wealth Matter

Americans' views on the risk criminal hacking poses to their well-being varies depending on their age and wealth, the survey shows.

Survey respondents between the ages of 45- to 59-years-old expressed the highest concern for criminal hacking, with 65% rating it a "very high" or "high" threat to their well-being. The next largest age group with similar concerns were respondents 60-years-old and beyond (55%), followed by 18- to 29-year-olds (49%), and 30- to 44-year-olds (47%).

Older people say they limit their Internet use because it reduces their risk of a cyberattack, explains Lysa Myers, an ESET security researcher. Younger people are on the Internet all the time and it would be harder for them to justify that if they felt they were putting their well-being at risk, she notes.

Meanwhile, 58% of survey respondents with household incomes of $75,000 or less rate criminal hacking as a "very high" or "high" risk to their well-being, compared to 48% of survey participants with incomes higher than $75,000, according to the survey.

"If you are working two jobs and have to take time off to sort out identity theft, you may be more concerned about the risk," Cobb says. "People from more well-funded households may feel less risk."

Join Dark Reading LIVE for two days of practical cyber defense discussions. Learn from the industry’s most knowledgeable IT security experts. Check out the INsecurity agenda here.

Related Content:

Dawn Kawamoto is an Associate Editor for Dark Reading, where she covers cybersecurity news and trends. She is an award-winning journalist who has written and edited technology, management, leadership, career, finance, and innovation stories for such publications as CNET's ... View Full Bio
 

Recommended Reading:

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...