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.

Comments
2 Million Fake Net Neutrality Comments Stole American Identities
Newest First  |  Oldest First  |  Threaded View
Joe Stanganelli
50%
50%
Joe Stanganelli,
User Rank: Ninja
12/18/2017 | 7:09:16 PM
Addresses of commenters
WTH?

I'm really concerned how much of these comments are a matter of public record. People's names and addresses are often enough to commit identity theft.

Of course, the same goes for most voting records.

It's a shame, really.
REISEN1955
50%
50%
REISEN1955,
User Rank: Ninja
12/15/2017 | 3:41:25 PM
Re: Ratio of "pro" to "con" fake posts could suggest unseen economic or political motives
As a past resident of NY State, I have many reasons to hate ALBANY and all that goes on there.  BUT ONE WORD OF GREAT ADVICE ----- IF you have or had relatives in the state, checked UNCLAIMED FUNDS ---- We came away with a substantial chunk of unknown change in the XX,XXX.xx number range. 
gruntsters
50%
50%
gruntsters,
User Rank: Strategist
12/15/2017 | 11:35:21 AM
Re: Ratio of "pro" to "con" fake posts could suggest unseen economic or political motives
I agree. Which way did the 2 million accounts lean? Why hasn't the NY AG listed this information?
SchemaCzar
50%
50%
SchemaCzar,
User Rank: Strategist
12/15/2017 | 9:17:28 AM
Ratio of "pro" to "con" fake posts could suggest unseen economic or political motives
Schneiderman's office did a valuable service.  Now this is definitely one of the more useless ways of gauging public opinion - no real authenticated identity to canvass citizens?  

However, the question I have is what is the ratio pro/con of fake comments?  If we see one side or the other exerting money and effort to swing the decision, it may lead us to hidden consequences of rescinding or preserving net neutrality that would give us further information in this important debate.

It's sort of disappointing that Schneiderman did not reveal this ratio.


Commentary
Cyberattacks Are Tailored to Employees ... Why Isn't Security Training?
Tim Sadler, CEO and co-founder of Tessian,  6/17/2021
Edge-DRsplash-10-edge-articles
7 Powerful Cybersecurity Skills the Energy Sector Needs Most
Pam Baker, Contributing Writer,  6/22/2021
News
Microsoft Disrupts Large-Scale BEC Campaign Across Web Services
Kelly Sheridan, Staff Editor, Dark Reading,  6/15/2021
Register for Dark Reading Newsletters
White Papers
Video
Cartoon
Current Issue
The State of Cybersecurity Incident Response
In this report learn how enterprises are building their incident response teams and processes, how they research potential compromises, how they respond to new breaches, and what tools and processes they use to remediate problems and improve their cyber defenses for the future.
Flash Poll
Twitter Feed
Dark Reading - Bug Report
Bug Report
Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2021-34390
PUBLISHED: 2021-06-22
Trusty TLK contains a vulnerability in the NVIDIA TLK kernel function where a lack of checks allows the exploitation of an integer overflow on the size parameter of the tz_map_shared_mem function.
CVE-2021-34391
PUBLISHED: 2021-06-22
Trusty TLK contains a vulnerability in the NVIDIA TLK kernel�s tz_handle_trusted_app_smc function where a lack of integer overflow checks on the req_off and param_ofs variables leads to memory corruption of critical kernel structures.
CVE-2021-34392
PUBLISHED: 2021-06-22
Trusty TLK contains a vulnerability in the NVIDIA TLK kernel where an integer overflow in the tz_map_shared_mem function can bypass boundary checks, which might lead to denial of service.
CVE-2021-34393
PUBLISHED: 2021-06-22
Trusty contains a vulnerability in TSEC TA which deserializes the incoming messages even though the TSEC TA does not expose any command. This vulnerability might allow an attacker to exploit the deserializer to impact code execution, causing information disclosure.
CVE-2021-34394
PUBLISHED: 2021-06-22
Trusty contains a vulnerability in all TAs whose deserializer does not reject messages with multiple occurrences of the same parameter. The deserialization of untrusted data might allow an attacker to exploit the deserializer to impact code execution.