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
Predicting Vulnerability Weaponization
Newest First  |  Oldest First  |  Threaded View
tdsan
50%
50%
tdsan,
User Rank: Ninja
6/29/2019 | 3:22:22 PM
Logical review of the analytics process
With a data set established, we need analytical models to gain predictive insights. By looking at historical weaponization trends, we can train algorithms to look across diverse types of data and identify the combination of traits that best predicts which vulnerabilities will be weaponized by attackers in the wild. Just as importantly, this approach can predict the speed at which a given vulnerability is likely to be weaponized.
  •  Traits and vulnerabilities - Couldn't we start with the threats that actually succeeded. Then take that information and categorize it using the risk score from CVE or others. take that information and create a relationship database (i.e SharedDB or No-SQL columnar DB) where big data comes into play to establish or identify those relationships, this will help the end-user determine the number of similarities between the variants or possible vulnerabilities that exist
  • Locations - identify where the code is coming from by associating the geographic regions, with the code, actors and success levels, this allows for those models (again Big Data) to start narrowing down the attacks to specific regions based on the type of attack, its function, success rate and locale (determine the type of attack and method of attack based on their success rate and design).
  • Finally, use ML to look at the attack vectors from a historical standpoint, the results from BigData can now inject its findings into the ML DB and from those relationshps, we can determine based on risk score if something else will occur as part of the variants evolution (most systems build on itself).

ML Concepts

 

Big Data
alpana.b
50%
50%
alpana.b,
User Rank: Apprentice
6/20/2019 | 6:42:52 AM
Automated Testing
Can there be a solution as Automated Testing? Or a testing that can run 24/7  and immediately identify existing or newly created vulnerabilities? At least for DDoS testing, I know there is such product available - this product doesn't need any maintenance window, for enterprises its a business as usual and testing report is handed over to security team to tackle issues with vendor. https://mazebolt.com/ddos-radar 

Do you see any such product for other security areas which can emerge as new technology?
dmddd
50%
50%
dmddd,
User Rank: Apprentice
6/13/2019 | 11:32:09 PM
Reference
Death Srinivas, Thanks for the interesting article. Would you mind sharing the reference of the underlying research paper? Best regards, David


COVID-19: Latest Security News & Commentary
Dark Reading Staff 8/3/2020
Pen Testers Who Got Arrested Doing Their Jobs Tell All
Kelly Jackson Higgins, Executive Editor at Dark Reading,  8/5/2020
Exploiting Google Cloud Platform With Ease
Dark Reading Staff 8/6/2020
Register for Dark Reading Newsletters
White Papers
Video
Cartoon Contest
Current Issue
Special Report: Computing's New Normal, a Dark Reading Perspective
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
The Changing Face of Threat Intelligence
The Changing Face of Threat Intelligence
This special report takes a look at how enterprises are using threat intelligence, as well as emerging best practices for integrating threat intel into security operations and incident response. Download it today!
Twitter Feed
Dark Reading - Bug Report
Bug Report
Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2020-15479
PUBLISHED: 2020-08-07
An issue was discovered in PassMark BurnInTest through 9.1, OSForensics through 7.1, and PerformanceTest through 10. The driver's IOCTL request handler attempts to copy the input buffer onto the stack without checking its size and can cause a buffer overflow. This could lead to arbitrary Ring-0 code...
CVE-2020-15480
PUBLISHED: 2020-08-07
An issue was discovered in PassMark BurnInTest through 9.1, OSForensics through 7.1, and PerformanceTest through 10. The kernel driver exposes IOCTL functionality that allows low-privilege users to map arbitrary physical memory into the address space of the calling process. This could lead to arbitr...
CVE-2020-5412
PUBLISHED: 2020-08-07
Spring Cloud Netflix, versions 2.2.x prior to 2.2.4, versions 2.1.x prior to 2.1.6, and older unsupported versions allow applications to use the Hystrix Dashboard proxy.stream endpoint to make requests to any server reachable by the server hosting the dashboard. A malicious user, or attacker, can se...
CVE-2020-13376
PUBLISHED: 2020-08-07
SecurEnvoy SecurMail 9.3.503 allows attackers to upload executable files and achieve OS command execution via a crafted SecurEnvoyReply cookie.
CVE-2020-15907
PUBLISHED: 2020-08-07
In Mahara 19.04 before 19.04.6, 19.10 before 19.10.4, and 20.04 before 20.04.1, certain places could execute file or folder names containing JavaScript.