If the coronavirus disease (COVID-19) pandemic has caused your enterprise to make a sudden, rapid switch from an on-premises-centered business model to a diverse, dispersed network of ad-hoc home offices, you may have let security and privacy measures slide a bit.
This is part 3 of a 3 part blog series My last two blog entries provided some key elements of a Zero Trust Network (ZTN), which focused on the tenets of zero trust and how the confidence is gained for untrusted traffic and authorized on a continual basis. The comprehensive nature of Zero Trust can be a little overwhelming in a world of limited resources, time and budgets.
For continuous coverage, we push out major Detectify security updates every two weeks, keeping our tool up-to-date with new findings, features and improvements sourced from our security researchers and Crowdsource ethical hacker community. Due to confidentially agreements, we cannot publicize all security update releases here but they are immediately added to our scanner and available to all users. This post highlights a few things that we have improved in the last two weeks.
When we think of open source analysis, security is often the first thing that comes to mind. But open source analysis is so much more than just security. It gives you visibility into your codebase to help you understand and manage your open source components. In this blog, we’ll define open source analysis, look at why it’s important to your business, and describe the characteristics of an effective open source analysis framework.
Why the cloud-native architecture required a new policy language I recently started a new series on the Open Policy Agent (OPA) blog on why Rego, OPA’s policy language, looks and behaves the way it does. The blog post dives into the core design principles for Rego, why they’re important, and how they’ve influenced the language. I hope it will help OPA users better understand the language, so they can more easily jump into creating policy of their own.
We’re back with part two of our three-part blog series on living-off-the-land attacks. If you missed part one, you can read it here. In a nutshell, living-off-the-land (LOTL) refers to a type of attack where the attacker uses the tools and features that already exist in the target environment to carry out malicious activities. The concept of LOTL is not new, but LOTL and file-less attacks have been gaining popularity over the last few months.
In this post we will talk about using image scanning on admission controller to scan your container images on-demand, right before your workloads are scheduled in the cluster. Ensuring that all the runtime workloads have been scanned and have no serious vulnerabilities is not an easy task. Let’s see how we can block any pod that doesn’t pass the scanning policies before it even runs in your cluster.
Anyone who has had any experience on the offensive side of security has had fun with privilege escalation. There’s something exciting about exploiting a system to the point of getting root-level access. Since I have spent most of my time on the defensive side of the fence, the magic of escalating privileges rested in Exploiting for Privilege Escalation or stealing an administrator’s credentials.
Millions of people have moved onto the Zoom video-conferencing platform as the coronavirus pandemic has forced them to work from their homes. According to Zoom’s own statistics, its daily usage has soared from approximately 10 million daily users in December to over 200 million today.
Modern applications aren’t built in silos. They rely on the features of other applications. This reliance can come in the form of open-source libraries, access to a wealth of data, or complex features distilled down into a consumable API. Incorporating third-party dependencies into your own project can be challenging. It comes with the benefits of faster development, and the downside of reliance. There is a relationship that happens when using a dependency.
