The latest News and Information on CyberSecurity for Applications, Services and Infrastructure, and related technologies.
The internet has been ablaze since the announcement of Log4Shell, the nickname for CVE-2021-44228, an arbitrary remote code execution vulnerability in the Java logging utility Log4j. So far two additional vulnerabilities ( CVE 2021-45046, CVE-2021-45105) have now been identified. The code has been vulnerable since 2013 and millions of hosts and services are affected.
This post originally appeared on The New Stack and is re-published here with permission. In our technology-driven business climate, most companies have at least some, if not all, workloads on the cloud. And unlike on-premises networks, these cloud environments lack secure outer perimeters and specific off times. Cloud networks are always on and always available. While convenient, this also means hackers can access them at any time.
This december, we are posting security advice and modules, every day until December 25th. Now, it’s December 21st, and we’ve gotten through most of the security hardening holiday calendar.
While I write this blog post, I reflect on the years of being a system administrator and the task of ensuring that no sensitive data made its way past me. What a daunting task right? The idea that sensitive data can make its way through our systems and other tools and reports is terrifying! Not to mention the potential financial/contractual problems this can cause.
Just when the Microsoft Exchange exploit CVE-2021-26855 thought it would win the “Exploit of the year” award, it got unseated by the – still evolving – Log4J exploit just weeks before the end of the year! Had somebody asked Sysadmins in November what Log4J was then I suspect that the majority would have had no idea. It seems that the biggest challenge the Log4J exploit poses for Sysadmins is simply the fact that nobody knows all the places where Log4J is being used.
Researchers discovered that diagnostic artificial intelligence models used to detect cancer were fooled by cyberattacks that falsify medical images. Diagnostic artificial intelligence (AI) models hold promise in clinical research, but a new study conducted by University of Pittsburgh researchers and published in Nature Communications found that cyberattacks using falsified medical images could fool AI models.
On December 9, 2021, a vulnerability was reported that could allow a system running Apache Log4j 2 version 2.14.1 or below to be compromised and allow an attacker to execute arbitrary code on the vulnerable server. This vulnerability was registered on the National Vulnerability Database as CVE-2021-44228, with a severity score of 10. Here is a diagram of the attack chain from the Swiss Government Computer Emergency Response Team (GovCERT).
On Nov. 8, I started as the new Chief Information and Security Officer at Grafana Labs. In my first five weeks, I’ve met about 100 really amazing people; learned and absorbed early lessons about our workplace culture; kicked off working groups for our 2022 initiatives (bug bounty FTW); and contributed to tackling our first-ever 0day. Amid all of that, I’ve also been doing a lot of thinking.