DefendTheCloud

TL;DR; The ability for attackers to successfully attack the cloud has increased due to the creation of generative AI. By 2025, attackers are capable of using generative AI to create very realistic phishing attempts and automatically generate exploit code. Attackers can now automatically map out any cloud environment at machine speed and evade detection systems that were trained on previous attack patterns or methods. This post provides a detailed overview of how these AI-based cyberattacks occur and what AWS Cloud Security Best Practices can be applied today to help to mitigate the risk of this type of cyber attack. Why GenAI Is Fundamentally Changing the Cloud Security Threat Landscape In previous years, sophisticated attacks on cloud infrastructures have required a high degree of knowledge and skill. This meant expertise in understanding AWS IAM policy logic, an understanding of chaining API calls for privilege escalation, and experience with writing code that is clean enough not to ...

A significant data breach occurred at Coupang, a major online shopping platform in Asia, in December 2025. This incident has resulted in millions of customers’ data being accessed with unauthorized access to names, contact numbers, details of card payments and order history. As industrial institutions continue to migrate towards a cloud-native application platform along with high-cycle DevOps methodologies, incidents like this demonstrate one critical fact; security should never be an afterthought. Coupang serves as a case study for developers, cloud engineers and security personnel on how things could be executed successfully. This article will examine what went wrong during this incident, how could attackers have taken advantage of vulnerabilities within Coupang’s systems, and how with compliant security methodologies such activities could be avoided in the future. What Happened During the Coupang Breach? According to public information and cybersecurity reports, attackers stole de...

 In today's hyper-connected world, waiting even a few seconds for data to travel to distant cloud servers can mean the difference between success and failure. Enter edge computing – the game-changing technology that's bringing computational power directly to where data is created and consumed. What is Edge Computing? Edge computing is a paradigm shift in data processing and analysis. As opposed to legacy cloud computing, where data must be sent hundreds or even thousands of miles to centralized data centers, edge computing brings processing closer to the source of data origin. This proximity reduces latency in dramatic ways, optimizes response times, and overall system performance. Consider edge computing as having a convenience store on every corner rather than driving to a huge supermarket out in the suburbs. The convenience store may not have as many items, but you get it right away without the long trip. The technology achieves this by placing smaller, localized computing r...

 The multi-cloud revolution has revolutionized the way businesses engage with infrastructure, but with power comes complexity. Organizations today have an average of 2.6 cloud providers, which are interlocking themselves together in a web of services that can move businesses forward or tangle them in operational mess. Multi-cloud deployment is not a trend, but rather a strategic imperative. Netflix uses AWS for compute workloads and Google Cloud for machine learning functions, illustrating how prudent multi-cloud strategies can harness historic value. But left ungoverned, it can rapidly devolve into what industry commentators refer to as "multi-cloud mania." Understanding Multi-Cloud Complexity The appeal of multi-cloud infrastructures is strong. Companies experience vendor freedom, enjoy best-of-breed functionality, and build resilient disaster recovery architectures. However, the strategy adds levels of sophistication that threaten to overwhelm even experienced IT staff. Ta...