DevSecOps
Amid growing pressure to enhance productivity and maintain a competitive edge, organizations are streamlining their application development processes. While increasingly integrating DevSecOps and Generative AI (GenAI) into their workflows, development teams must align to safeguard against application security threats and manage risks effectively ...
I've loved witnessing CISA's Secure-By-Design (SBD) movement gain momentum worldwide, as the United States, Australia, New Zealand, Canada, Singapore, Japan, Germany, and the UK commit to integrating similar guidelines and expectations into their respective cybersecurity strategies — with many of these nations also contributing to the original US recommendations.
As we approach 2025, the cyber security landscape will be shaped by the rise of AI-powered attacks, the looming threat of quantum computing, and the growing vulnerability of social media platforms. Part 2 continues the predictions ...
As we move into 2025, the cyber security landscape will become more complex, with new challenges emerging as rapidly as the technologies that drive them. From artificial intelligence (AI)-enhanced malware to looming quantum computing threats, the forecast from Check Point Software Technologies highlights the trends that organizations must prepare for to stay secure in this evolving digital environment ...
The escalating complexity of software supply chains and the applications being built is shifting greater security responsibilities onto developers. This shift is driving up costs and workload, threatening developer productivity and the overall quality of applications. Left unchecked, these pressures can jeopardize the very security that DevSecOps aims to enhance ...
Agile security sprints are specialized iterations within the Agile framework focused on embedding security into the sprint cycle. Rather than treating security as an afterthought or a final checkpoint, it's integrated into the regular sprint rhythm ...
The evolution of AI, particularly in cloud and serverless environments, has opened up new possibilities — but it's also introduced significant complexities, especially around privacy and data security. DevOps engineers are on the frontlines of these challenges ...
Part 12 of this series features expert recommendations on how to avoid the risks associated with using AI to support software development ...
In Part 6 of this series, the experts warn of the security risks associated with using AI to help develop software ...
Part 2 of this series covers more processes that can be supported or improved by AI, including security, testing, deployment, documentation and more ...
In DevOps, hierarchical security practices involve embedding security measures into every development lifecycle stage. Unlike traditional models where security is a final checkpoint before deployment, hierarchical security integrates security from the outset, beginning with the planning and design phases. By doing so, potential vulnerabilities are identified and mitigated early ...
The meteoric rise of artificial intelligence (AI) in the past few years has been a boon for software developers, who quickly embraced AI's ability to help them create code more quickly. But the other edge of the AI sword is that its code isn't always secure, because AI models trained on flawed code, which exists in plenty of applications, are only going to repeat the same mistakes ...
DevSecOps emerged as a potential solution to address delays and missed vulnerabilities, streamlining development and operations by prioritizing speed and collaboration without compromising on security. But the growing complexity of cloud-native environments and the surge in the volume and vectors of the threat landscape is once more reshaping the way organizations approach software development. The latest evolution increasingly demands that security be treated as an integral part of the software development process ...
CyCognito recently conducted an analysis of over 39 million data points from a diverse range of companies, providing concrete evidence validating the growing concerns about the vulnerability of our software supply chains. The report's findings reveal a troubling reality: our digital ecosystems are far more vulnerable than we'd like to believe ...
The incorporation of generative AI and machine learning into DevSecOps has unlocked significant potential to improve organizational efficiency in software development. Yet, despite these developments, mitigating friction between development and security teams remains a persistent challenge ...