Nightfall Infosec Roundup: March 23 to March 30

In the Nightfall InfoSec Roundup, we summarize the latest information security news, breaches, vulnerabilities & advancements. In this week’s edition:

Exploits & Vulnerabilities


Amid the pandemic, critical infrastructure remains vulnerable to cyberattack
Although the Ware Report was declassified in 1975, many of today’s companies still have yet to implement the cybersecurity controls it identified, including robust user access controls, system debugging, testing and certification, encryption and audits. These faliures pose critical risk to infrastructure today.


All 4G Networks Susceptible to DoS Attacks
New research has uncovered a vulnerability affecting all 4G and some 5G telecommunications networks. Astudyof the security of diameter networks completed by Positive Technologies found that weaknesses in the diameter-signaling protocol meant that 100% of 4G networks are susceptible to denial of service (DoS) attacks.


Password vulnerability at Fortune 1000 companies
SpyCloud has combed through their database of breach data for data tied to Fortune 1000 companies, analyzed it and found that employees in media companies are the worse when it comes to password reuse (rate of reuse: 85%), and those is retailing the best (53%), although even they still reuse passwords way to much.

Ongoing Risks & Threats


Organizations not properly set up to manage risk, coronavirus pandemic reveals
Organizations’ current approach to risk governance is not sufficient to tackle the complex risk environment organizations are facing today, according to Gartner. The COVID-19 pandemic is just the latest in a line of recent risk events showing how organizations are not properly set up to manage risk, especially fast-moving ones.


In artificial intelligence, enterprises still not minding their data
Data is the raw material that fuels artificial intelligence and machine learning initiatives, but it actually can’t be that raw. It needs to be as accurate, timely and well-vetted as possible — or else AI will deliver erroneous or biased results. At this stage, most enterprises haven’t quite locked down the viability of the data employed within their AI efforts.

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