We talked about IAM in the past 3 posts, identities in IAM, manage users privilege as an IT person and control privilege boundaries. We also talked about how applications use AWS Cognito Identity Pool to get AWS temporary credentials to access AWS resources in early posts of “What I wish I could have learned before starting using AWS Cognito” and “Authentication and authorization with AWS Amplify under the hood”.
When it comes to evaluating technology in the home, there seems to be no shortage of new devices and shiny gadgets, mainly part of the Internet of Things (IoT), to discuss. Unfortunately, there seems to be no shortage of security issues to consider regarding these same devices, either.
If our friends Security and Networking were on Facebook, they would probably both list their relationship status as “It’s Complicated.” Sometimes everything’s great, but now and then things can get a little weird, unclear, or uncomfortable. At many organizations, there has traditionally been a barrier between the security and networking teams. Each team has its own objectives — and at times, those objectives can be at cross-purposes.
Most organizations have already begun their shift to the cloud. In its Cloud Computing Survey 2020, for instance, International Data Group (IDG) found that 81% of respondents had at least one workload or segment of their computing infrastructure in the cloud. That percentage could grow by the end of the year, as IDG found that 32% of total IT budgets will go to cloud computing—up from 30% in 2018.
To say that the past year presented its fair share of cybersecurity challenges to the InfoSec community would be a drastic understatement. The rapid migration to remote work at scale left 80% of CIOs unprepared, and SecOps teams struggled to confront the evolving threat landscape with disparate toolkits and skill sets. Not to mention that as more organizations shifted to hybrid and multi-cloud environments at scale, cloud complexity (and cloud-based threats) skyrocketed.
Today, we published the open source edition of our annual State of Software Security report. Solely focused on the security of open source libraries, the report includes analysis of 13 million scans of more than 86,000 repositories, containing more than 301,000 unique libraries. In last year’s open source edition report, we looked at a snapshot of open source library use and security.
Artificial intelligence (AI) and machine learning (ML) systems have become the norm for using client data to provide recommendations to customers. As more people are working from home and conducting business online, it is imperative that fraud detection software is used to protect user information. But these protective systems also utilize ML to automate the process and understand when a potential attack is taking place.
