The Software Development Life Cycle (SDLC) provides a systematic framework for developing and maintaining software from conception to modification, producing high-quality software that meets stakeholder and customer requirements within specified time and cost constraints. However, traditional SDLC practices fall short of ensuring thorough application security. Why?

Like any chain, a software supply chain contains many links. These links consist of every actor involved in the development & deployment of your code in the Software Development Life Cycle (SDLC). An actor can be the developers, infrastructure components, and even repositories like GitHub. A company might have a very secure supply chain. However, it will only be as strong as its weakest link.

Between customer requirements, regulatory or legislative mandates and executive orders, incorporating strong security controls throughout the Software Development Lifecycle (SDLC) has become a central focus for development groups, leadership teams and governing bodies. However, regardless of external motivators, maintaining a secure SDLC also provides the developer tangible benefits regarding the health of the software by ensuring a meticulous focus on architecture and solid software-building practices.

Lax security measures in the software development lifecycle (SDLC) can lead to severe financial repercussions for organizations. The Verizon 2024 Data Breach Investigations Report highlights this growing risk, stating, "Our ways-in analysis witnessed a substantial growth of attacks involving the exploitation of vulnerabilities as the critical path to initiate a breach when compared to previous years.

This is an analysis of the impacts and implications on cybersecurity practices, benefits, challenges, and how to deal with the transition to the new NIST CSF 2.0 framework. NIST released an update to its Cyber Security Framework (CSF) in February 2024. Two of the most obvious takeaways from this version are the addition of a new pillar and the expansion of its application beyond critical infrastructure.

A malicious code, commonly known as malware is simply a software created to harm computer systems and applications, make changes to networks, and the victim completely unaware. Unlike accidental security flaws and applications’ configuration failures, which are occurring because of irrelevant mistakes like coding mistakes or other mistakes during development activities, deliberate code is purposely designed in order to cause some harm.

The release of the February 2024 White House Technical Report, Back to the Building Blocks: A Path Towards Secure Measurable Software, brings about a timely shift in prioritizing software security. Software is ubiquitous, so it’s becoming increasingly crucial to address the expanding attack surface, navigate complex regulatory environments, and mitigate the risks posed by sophisticated software supply chain attacks.

In the ever-evolving landscape of software development, artificial intelligence (AI) is emerging as a transformative force, reshaping the software development lifecycle. While AI use is still not without risk, it's time to reframe the conversation and explore how AI can enhance and streamline various stages of the SDLC. Let’s take a look at how you can strategically incorporate AI in the SDLC and address lingering concerns.

Did you know that nine out of 10 companies detected software supply chain risks in the past 12 months? The increase in the number of dependencies in a supply chain has extended the attack surface for adversaries. It has also caused threat actors to shift their focus from the downstream chain affecting just end users to the upstream chain affecting vendors, customers, and end users alike.