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5 Soothing Security Products We Wish Existed
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User Rank: Ninja
4/23/2020 | 9:33:57 AM
Centralized brain
There was a company in the past called Enterasys, they made a product called Net-Sight Atlas. What this product did was it pulled information from switches, routers, firewalls, servers, and authentication servers (Radius/AD). It created a list of potential threats, basically derived this information by creating a baseline of information about the specifics of your network (whos logging in, from where, and remote access).

The application would look into a list of 17K-24K policies and those you wrote or identify a zero-day attack by constantly analyzing the various environments (sentinel type of capability). Once it identified the threat, it would move the threat to "sandbox" for analysis or by moving the data stream or file using the information it obtained from the network. Once isolated (it would do this for regular users if the user did not have the right patches), the solution would utilize a number of checks and balances by checking for viruses, unknown files from a baseline developed put in place by the user; the system would identify an isolate APTs, malare or unauthorized user access to create a basis of understanding that would be stored for later retrieval. This application was ahead of its time, they'r office was located in Northern VA.

Amazing technology and capability, a number of companies use SIEM to perform a number of tasks but SIEM does not act upon a threat (prescriptive analytics); this soluiton would identify, analyze, mitigate, inform and learn. This is the tool that was not utilized because the marketing of their product was not at the paramount of the IT business, but these guys were brilliant in their foresight and evolutionary thinking.

Extreme Networks NetSight | NetSolutionStore.com


User Rank: Apprentice
4/20/2020 | 12:22:02 PM
A data integrity test solution
I enjoyed reading this article to put a bit of humor into the day.  You overlooked the scratch and sniff data integrity test for data poisoning in AI applications.  Clean data has a fresh laundry smell while poisoned data has a rotten egg smell.

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