Software Composition Analysis (SCA) is the practice of identifying the open source libraries your code depends on. By using SCA, you can analyze these dependencies and determine whether they are affected by any known vulnerabilities, contain malicious code, introduce licensing risk, or are poorly maintained. SCA helps teams understand their software’s dependencies and the security implications of using them so that they can safely build on and innovate with open source code.

As your business evolves to serve more users, your applications and infrastructure will generate an increasing volume of logs, which may contain sensitive data such as credit card numbers, IP addresses, and tokens. When you collect sensitive data, you may be subject to laws such as GDPR—which restricts the transfer of personal data across borders, and you may face legal consequences if this data is exposed outside your infrastructure.

Shipping secure code rapidly and at scale is a challenge across the software industry, as evidenced by continued news of high-profile data breaches and critical vulnerabilities. To address this challenge, organizations are increasingly adopting DevSecOps, a practice in which application developers work closely alongside operations and security teams throughout the development life cycle.

Achieving and maintaining compliance in the cloud proves challenging for many organizations, as it is a complex, ongoing effort that includes safeguarding sensitive data and ensuring infrastructure resources are correctly configured. Success often hinges on the ability to monitor compliance-related trends over time, enabling organizations to spot risk patterns, gauge their current compliance posture, and adapt as new risks emerge. However, gathering this data can be difficult.

As Windows organizations migrate toward cloud-based environments, they often lose context of their full stack. In addition to securing their on-premises servers, they now need to deal with virtual servers, managed services, and platform-as-a-service offerings. Cloud-based resources require organizations to relinquish control over physical infrastructure and limit their access to underlying operating systems.

APIs are foundational to modular application development. They support an organization’s internal services as well as provide a mechanism for customers to access certain services or datasets for their own applications. Because of the role that both internal and public-facing APIs play in applications, they are considered one of the top targets for threat actors.

In recent years, the popularity of Kubernetes deployments has surged—as has the prevalence of security risks associated with the technology. Red Hat’s State of Kubernetes Security for 2023 reveals that 67 percent of organizations have encountered delays in application deployments due to Kubernetes-related security issues. Additionally, 37 percent have experienced significant revenue or customer losses stemming from Kubernetes security incidents.

Organizations are adopting Google Cloud at a growing rate. This growth is partially influenced by both the rise of AI computing and a push towards multi-cloud usage. A recent report found that 85 percent of organizations deploy their applications on multi-cloud architecture. With the shift to AI computing and multi-cloud adoption, organizations are reconsidering their cloud security coverage now more than ever.

Detecting malware in container environments can be a major challenge due to the rapid development of malicious code, the proliferation of insecure container images, and the multilayered complexity of container stacks. Staying ahead of attackers means tracking the constant evolution of malware and rooting out threats in your codebase at the expense of considerable compute.

Cloud environments are susceptible to a wide variety of cyberattacks, making them difficult to secure. Some cyberattacks are easier to detect than others, so a priority in cloud security is having adequate detection and response systems in place to mitigate them. Unauthorized cryptomining has become a prevalent threat in recent years, especially in cloud environments where it can be harder to detect.