Every client and customer cares deeply about security. Regardless of the domain, industry or specific application, when a workload is moved to or created in AWS, security and data protection are always important components of the architectural design. To meet these critical security requirements, organizations use AWS Control Tower and Landing Zones, which enable a secure and compliant foundation for your AWS environment.

Setting up an AWS Control Tower and Landing Zone

Setting up a Control Tower and Landing Zone for your enterprise applications can help mitigate many security risks and provide a consolidated and comprehensive view of your AWS landscape. AWS Control Tower and Landing Zone thoroughly propagate the concept of “define once and use across”. This enables you to set up a well-architected, multi-account environment in hours instead of weeks or months, utilizing best practice blueprints tailored to the organization’s needs.

As a security best practice, it is always recommended to have a multi-account approach, where accounts can be categorized based on application/environment/business-unit etc. This approach enhances security through segregation and isolation of workloads and data. This will also significantly reduce the surface attack area when there is a security compromise.

As your organization and customer needs grow, you will have a bunch of accounts to handle – that is when the Control Tower and Landing Zone comes to the rescue as it provides centralized control and policy management across the accounts.

Figure 1 here depicts how you can have all AWS accounts under AWS Organizations and tap on Control Tower features to enforce security and governance.

Setting up a Landing Zone is always one of the best approaches for customer applications running on multiple AWS accounts, if you want to ensure strict traffic inspection, central security logging, and cost savings.

Building a Landing Zone with AWS Control Tower: Core concepts

Here are the core concepts at play while establishing a robust AWS Control Tower and Landing Zone foundational implementation.

Organizational Units: When it comes to planning Organizational Units (OUs), there is no one-size-fits-all approach. It should be based on the best way you can categorize your workloads.

For example, an enterprise company with numerous applications, business units and multiple environments (e.g. Dev/UAT/Prod) can be structured as shown below.

Service Control Policies/Guardrails: Service Control Policies (SCPs) are effectively a policy-driven preventive guardrail. AWS SCPs/guardrails provide organizations with robust tools for optimizing and centrally managing governance, security & compliance enforcement, permission management and operational efficiency. These features make them critical components of a well-architected multi-account strategy in AWS. We recommend you enable all the required guardrails as per industry standards. To get started with AWS Best Practice guardrails, you can refer to the official AWS guidance documentation found here.

You could also create a Test OU within which you can enable and test the effect of guardrails without impacting any production workloads. This is prudent when teams may be unaware of how an SCP guardrail may impact your team’s day to day activities.

Networking for Landing Zone: This is the most important part which often consumes a lot of time for planning. We recommend that organizations should plan for three different types of traffic flow:

• Ingress traffic: The Landing Zone should have a highly available firewall for ingress traffic inspection. Organizations can choose from a number of firewall appliances in the market today, including native AWS Network Firewall.
• Egress traffic: Plan for a central NAT gateway to manage all the egress traffic originating from workload VPCs from all AWS accounts and ensure it is being inspected using the firewall. This saves cost when all your workload VPCs use a central NAT gateway instead of individual NAT gateways for VPCs and enhances security through comprehensive monitoring with a holistic view.
• Inter-VPC traffic: Also referred to as East-West traffic, this is internal traffic between the VPCs within the AWS accounts. Best practice is to have inter-VPC traffic inspected using a firewall to detect internal threats, prevent data exfiltration etc. However, you can choose to ignore inspection for some VPCs – for example, those which require high throughput and require less latency.

We recommend you further define any other flows for your workloads and analyse its effects including latency, costs when it traverses transit gateway, or other cost incurring components.

Figure 3 here shows one of the ways you can design your architecture to achieve the above-mentioned traffic inspection and flows. It uses hub and spoke architecture using AWS transit gateway.

To read more about hub and spoke architecture refer to this AWS article here.

Logging and monitoring: Logs can be considered as a critical asset in any infrastructure. There are a number of different kinds like VPC flow logs, firewall logs, DNS logs, transit gateway attachment logs, application logs, and more. AWS Control Tower offers you a way to centrally store these logs in a separate “Log Archive” account. While AWS Control Tower has the capability to implement centralized storage, the responsibility of log ingestion implementation is allocated to the organization. The logs can be further ingested to other Security Information and Event Management (SIEM) platforms for analytics.

Putting things in motion

By continuously monitoring workload performance and analysing customer feedback, organizations can effectively adjust resources and processes to align with evolving customer needs, ensuring enhanced service delivery and operational efficiency.

AWS offers native service called AWS CloudWatch, to get you started with Logging and Monitoring – refer to this official AWS documentation. This should help you understand what AWS services’ logs can be centralized, among other important notes.

To sum up, using the AWS Control Tower service will unveil a holistic view of security and governance across all AWS accounts within the organization. Setting up a Landing Zone makes it easier to have total control on all of the traffic entering and exiting your AWS accounts. This will significantly reduce the surface attack area and can efficiently create a scalable architecture and ensure security best practices.

For additional Design Consultation and Cloud Engineering support, Cloud Kinetics currently offers a refined AWS Secure Landing Zone (SLZ) implementation, available here via AWS Marketplace. You can also get in touch with us directly here.

The post AWS Control Tower and Landing Zone: Architecture & Best Practices appeared first on Cloud Kinetics.

• Fraudulent transactions across Europe are an estimated €1.8 billion per annum.
• The number of bank frauds in India was up 166% in FY24.
• In the United States 26% of adults surveyed said they had personally experienced bank/credit fraud.

The explosion of online banking, neobanks, fintechs and financial applications has also made it easier for scammers to strike, making it vital to spot anomalies in transactions and strange behaviour to catch fraud early. In this scenario, Artificial intelligence (AI), Generative AI & Machine Learning (ML) are new sentinels for safe and secure business operations and technology, helping banks, financial services, and insurance (BFSI) companies stay one step ahead of fraudsters.

According to one survey, 62% of UK and US based large/mid-sized businesses intend to deploy AI-based solutions to combat the issue.

Power of AI in fraud detection: Traditional security options vs AI-driven solutions

• AI can “learn” from past fraud cases, helping ML algorithms more accurate with time. An AI model flags suspicious data/anomalies in transactional and behavioural data.
• As self-learning models, AI gets smarter over time, reducing the likelihood of repetitive errors and minimizing false positives.
• AI can not only alert the humans overseeing the systems to potential fraud, but also take action by blocking transactions or removing suspicious attached files.

AI and ML can give banks and financial companies a huge advantage with a “two-steps ahead” approach to security and risk management. For instance, for a large multinational bank, fraud detection traditionally involved wading through mountains of data, reading endless reports, and manually checking every suspicious transaction. It was a slow and painful process, often leading to delays in spotting fraud. Sometimes, customers would even have to report the problem themselves, which could mean losing a lot of money before the bank could fix the issue.

The power of AI-backed fraud prevention means that the same bank can now process copious volumes of data in real time, monitor all activity including transactions as they happen. When a possible high risk event begins to occur, it escalates this to the top of the list for review on priority. The bank can now intervene as the fraud is occurring and prevent it from happening or reduce further potential loss. Overall, this can mean better customer satisfaction with fewer losses incurred.

Using AI in fraud detection means fast detection – since AI algorithms act instantly to freeze/block a transaction/account, and offers increased accuracy over traditional methods – since AI applies dynamic rule setting, learning from itself, rather than just predefined rules. Over time, this results in cost optimization as the long-term cost of prevention vs reaction is lower.

Business impact of AI for fraud prevention

AI can be applied in multiple ways to help mitigate the risk of fraud:

• AI-driven analytics platforms can integrate diverse data sources (financial data, market data, customer data) to provide a comprehensive view of risk exposure.
• GenAI for real-time fraud detection identifies suspicious patterns of behaviour through comprehensive data analysis; this helps block and prevent potentially fraudulent activity. 
• AI-powered alert prioritization is used to classify alerts by risk level, ensuring that higher risk cases get assigned for review and intervention first, which means speedy intervention and protection for the business.
• Predictive analytics help determine future risk based on constantly updated data. AI & ML can minimize false positives, making for a seamless customer experience while ensuring security.
• Data-driven operations backed by AI/ML and robust analytics help ensure regulatory compliance and support KYC verification.
• Automation along with a strong GenAI/AI/ML powered business analytics and data engine supports scalability and boosts operational efficiency.

Use Cases for BFSI | How AI helps in fraud prevention

AI-based use cases for fraud prevention in the banking and financial services sectors can take on various forms:

1. Real-Time Anomaly Detection: Systems using GenAI can detect fraud early by learning normal behaviour and spotting unusual activity or deviations that might indicate account takeovers from identity theft or phishing. This improves speed – something that’s crucial when dealing with fraud, where every minute counts.

GenAI-powered behavioural analysis can monitor app usage, banking transactions, payments, or any other financial transaction across channels/touchpoints in real time and flag off potential threats like unusual spending pattern/unauthorized account access, blocking them and preventing fraud.

AI-backed fraud detection enables faster action, better communication and quick resolution. Traditionally, we have relied on programming languages to identify any aberrations. With ML algorithms, statistical analyses and AI, we can implement a framework that easily identifies the current unusual behaviour as well as new behaviour in the future without too many changes in the program and environment. This translates to cost savings, cuts developer time and reduces time to market/time to go live.
Dipti Pasupalak, Data & Analytics Architect, Cloud Kinetics

2. Automated Fraud Reporting and Reduced Manual Reviews: AI and ML allows for automated fraud reporting and reduces the need for manual reviews. GenAI generates suspicious activity reports (SARs) incorporating millions of data points. With a lower burden on analysts, finance and IT teams, their time can be freed up to be used to propel business growth, enhance solutions and drive innovation.

Automation also makes the process of identifying investment fraud, payment fraud, or card fraud faster, more efficient and often more accurate, with lower instances of false positives.

3. Enhanced Authentication with AI: Secure authentication powered by AI can be improved with GenAI and reduce risk in case of forgery or identity theft.

GenAI can help refine algorithms used for recognition and verification, thereby making traditional biometric verification methods more effective and limiting access to only legitimate users. This cuts the risk of unauthorized access/ account takeover fraud.

Use Case | Seamless User onboarding & authentication with AI/ML-powered solutions from AWS: In the online registration process for an account, using ML-powered facial biometrics – with pre-trained facial recognition and embedded analysis capabilities, ID verification, user onboarding and authentication – can be done securely with no need for prior ML expertise in-house.

4. Detecting Variations in Usage Patterns: AI is able to analyse metadata to detect variations from the norm that might be missed in manual reviews by the human eye. As fraudsters begin to use sophisticated methods including AI to commit fraud, the use of AI as a defense against things like deepfakes will be critical.

Take for example a scenario where a customer has been duped into sharing their net banking details with a fraudster. Normally transactions after this would not be flagged since the data compromise has not occurred on the bank’s system. But AI-based risk monitoring software will spot any unusual pattern in the transactions or amounts not in line with their normal transactions, or even things like screen resolution, currency or language used and flag it for manual tele-verification in real time, more swiftly than older methods.

Use Case | Fraud prevention with Snowflake’s scalable multi-cluster shared data architecture and advanced data governance: This can help protect merchants from fraud and risk. Snowflake-powered fraud prevention models are able to identify bad actors, detect attack vectors and block account takeover attempts.

5. Offline Fraud Prevention: AI-powered video analytics can flag off suspicious behaviour at ATMs and branches that may be linked to ATM skimming, usage of stolen cards or cheque forgery.

Use Case | Geospatial analytics and AI for fraud detection from Databricks: Geospatial data, machine learning and a lakehouse architecture from Databricks help FSI clients better understand customer spending behaviours and spot abnormal credit card transaction patterns in real time. This enhances the fraud prevention and detection capabilities of the organization, which in turn reduces losses and helps cement customer trust.

Building an AI-backed fraud detection strategy

Banks and financial institutions aren’t the only ones with an eye on AI. According to Deloitte’s Center for Financial Services, fraud losses in the United States could hit US$40 billion by 2027, on the back of GenAI.

With fraudsters already using AI, industry needs to quickly adopt an AI-backed defense as well. Here’s your roadmap:

• Create a cross-functional fraud management team: Drawn from IT, operations, compliance, legal, data sciences
• Build a multi-layered fraud detection strategy: Use AI in tandem with traditional anomaly detection systems, encryption, multi-factor authentication etc.
• Implement the right environment and tools: These must be compatible with existing infrastructure and scalable and effective. Banks must modernize their infrastructure to effectively leverage AI for fraud prevention.

By migrating to the cloud or adopting a hybrid approach and establishing a robust data platform, banks can ensure timely access to high-quality data. This real-time data empowers AI, ML, and generative AI systems to analyze patterns, identify potential fraud, and enable rapid intervention.

• Follow transparent & ethical data usage: Adhere to customer privacy norms and practise ethical data usage
• Monitor & update regularly: Retrain with new data to stay effective against new types of fraud
• Run simulations: Run controlled realistic fraud attack simulations to check robustness of the systems in place and keep ahead of advanced fraud attacks

Building an effective AI-backed fraud detection strategy into your organization requires an overall commitment to a security-conscious culture. In addition to the AI, ensure every “human firewall” is well armed to respond to fraudulent activity with regular training and a culture that encourages a security-first approach. Dipti Pasupalak, Data & Analytics Architect, Cloud Kinetics

The post How Banks & Financial Services Can Fight Fraud With AI-Driven Analytics appeared first on Cloud Kinetics.

For industries like manufacturing, transportation, and logistics, embracing modern cloud- and AI-driven solutions is key to staying ahead of the curve. The right technology can not only empower you to adapt swiftly to market changes but also unlock opportunities for growth and innovation.

We had the pleasure of hosting industry leaders and a select group of CXO peers for an intimate roundtable discussion on the transformative benefits of cloud- and AI-powered business strategies.

Takeaways from the event:

• Gaining real-time visibility into your entire supply chain for better decision-making
• Streamlining and automate logistics workflows to achieve maximum efficiency
• Eliminating capacity guesswork and optimize resource utilization
• Leveraging data-driven insights to boost profitability and drive growth

The post Modernize Your IT Stack With Cloud & AI: CXO Roundtable appeared first on Cloud Kinetics.

Tại đây, các nhà lãnh đạo ngành đã chia sẻ những hiểu biết sâu sắc về cách tận dụng các công nghệ mới nhất để đạt được các lợi thế cạnh tranh trong ngành của bạn dựa trên các dữ liệu mới được nghiên cứu gần đây.

Các diễn giả:

Dr. Philip Cao

Cyber Strategist & Evangelist
Co-founder & Advisor, Cloud Security Alliance - Vietnam Chapter

TS Philip Hùng Cao (còn gọi là #DrTekFarmer), EDBA, MSCS, ZTX-I, CCISO, CISM, CMSC, CCSP, CCSK, CASP, GICSP là một nhà chiến lược, cố vấn, cộng tác viên, nhà giáo dục và người truyền cảm hứng. Ông có 23 năm kinh nghiệm trong ngành CNTT/ANTT/ATTT trong các lĩnh vực và vị trí khác nhau, và hiện đang là một Người truyền bá tích cực về ANTT/ATTT và Zero Trust ở Việt Nam cũng như khu vực Đông Nam Á, Châu Á - Thái Bình Dương, Nhật Bản và toàn cầu.

Huong Mai Nguyen

Account Manager
Cloud Kinetics, Vietnam

với hơn 8 năm kinh nghiệm bán hàng trong lĩnh vực viễn thông và công nghệ. Lĩnh vực chuyên môn của tôi là điện toán đám mây, đặc biệt là public cloud. Tôi đã hỗ trợ các dự án "move to cloud" cho nhiều khách hàng, đặc biệt là các ngân hàng và các công ty digital native.

Ruby Duong

Customer Engineer
Google Cloud

Ruby Duong là Kỹ sư Khách hàng tại Google Cloud ở Singapore. Cô làm việc với các startup và doanh nghiệp vừa và nhỏ trong khu vực châu Á Thái Bình Dương về quá trình chuyển đổi công nghệ điện toán đám mây, chuyên về các công nghệ quản lý và phân tích dữ liệu, máy học và trí tuệ nhân tạo.

Sunny Nguyen

Territory Manager SMB
Google Cloud

Sunny là người quản lý khách hàng SMB mảng GCP thị trường Việt Nam tại Google Cloud ở Singapore. Sunny chuyên giúp khách hàng giải quyết các bài toán kinh doanh như tối ưu hóa chi phí, số hóa/hiện đại hóa, giải quyết các vấn đề từ nâng cao trải nghiệm khách hàng/ tự động hóa vận hành nội bộ cho đến giảm rủi ro/tăng ROI/tăng bảo mật bằng cách tận dụng danh mục công nghệ tiên tiến và hệ sinh thái đối tác trong ngoài nước và nguồn kỹ sư công nghệ của GCP.

Các luận điểm chính trong sự kiện

Người tham gia đã được trải nghiệm các mà Data Analytics & AI đang trở thành xu hướng và thay đổi các doanh nghiệp trên toàn cầu.

• Mở khóa giá trị doanh nghiệp: bạn đã nhận được các thông tin chuyên sâu về cách tận dụng dữ liệu và AI để đạt được lợi thế chiến lược, đồng thời đảm bảo tính bảo mật mạnh mẽ.
• Các giải quyết các nỗi lo về bảo mật: Tìm hiểu về các rủi ro bảo mật hàng đầu liên quan đến các giải pháp Data Analytics & AI trên nền tảng Cloud.
• Đo lường mức độ thành công: Khám phá các chiến lược để đo lường lợi tức đầu tư (ROI) của dữ liệu và các sáng kiến ​​bảo mật của bạn
• Đảm bảo tính tuân thủ: Hiểu được các phương pháp hay nhất về việc tuân thủ các quy định về quyền riêng tư dữ liệu khi sử dụng các công cụ Cloud.
• Xây dựng Văn hóa về An toàn bảo mật: có được những lời khuyên thiết thực về việc tạo ra một môi trường có ý thức cao về bảo mật trong tổ chức của bạn.

The post Securing Tomorrow: Master Data Analytics, AI & Security With Google Cloud appeared first on Cloud Kinetics.

The event focused on exploring Google Cloud’s Chronicle Security Operations, a cutting-edge solution designed to enhance security operations and protect organizations against emerging threats. Attendees gained valuable perspectives from industry experts and learned from real-world success stories, demonstrating Chronicle’s impact on security resilience and business outcomes. Through dynamic presentations, engaging games, and networking opportunities, participants left with actionable strategies to elevate their security strategies and fortify their organizations for the future.

We thank everyone who joined us to make this event a resounding success! See you on the next event.

The post Securing Tomorrow: Mastering Data Analytics, AI & Security With Google Cloud appeared first on Cloud Kinetics.

As part of their optimization journey, Sieu Viet wanted to review their cloud infrastructure on AWS to take stock of existing capabilities and to identify next steps aligned with their business goals. In addition, a planned CRM system change was lined up as the company headed into its next phase of growth.

“Our partnership with Cloud Kinetics has been invaluable as we navigate our cloud journey and scale our digital infrastructure. Their expertise and focus on continuous optimization perfectly complement our business goals, making them a trusted partner in our transformation strategy.” Dat Vo, Head of Tech, Sieu Viet

The post Recruitment Giant Gets Future Ready With AWS Well-Architected & Freshsales CRM appeared first on Cloud Kinetics.

As more organizations embrace the cloud, securing cloud-native applications has become increasingly complex. Fragmented multi-vendor solutions attempt – and struggle – to shield an attack surface that’s expansive, dynamic and vulnerable. The solution to this growing challenge in cybersecurity could lie in cloud-native application protection platform or CNAPP.

CNAPP is a comprehensive solution that gives DevSecOps and DevOps teams unified automated security that oversees containers, workloads, compliance and more – the entire application lifecycle. It is being used by organizations to crank up security as well as visibility across hybrid and multi-cloud, and private and public cloud environments. But first, let’s see why there’s such a strong case for CNAPP and how it fares over traditional solutions.

Why traditional cybersecurity solutions aren’t always optimal

How did security end up being so complicated? Organizations have grown their cloud investments over time and added solutions and products in phases, organically. The accompanying security products layered over these have also been heterogeneous and operated in silos. The result? DevSecOps is fashioned sometimes from as many as 10 different tools each working in isolation!

Add to that the fact that cloud environments often involve microservices, containerization or serverless architecture. A far cry from traditional IT environments. This is why traditional intrusion detection and firewalls just don’t cut it when it comes to the distributed and dynamic cloud environments of today. These modes of security were designed to serve a fixed network perimeter like a data centre. Not the complex distributed cloud environments that are par for the course today.

The most significant driver is the need to unify risk visibility across the entire hybrid application and across the entire application life cycle. This simply cannot be achieved using separate and siloed security and legacy application testing offerings. – 2023 Gartner® Market Guide for Cloud-Native Application Protection Platforms

Your cloud security & CNAPP

What is CNAPP? A cloud-native application protection platform offers a simplified security architecture to enable enterprises to reduce complexity and costs of security solutions that operate in silos. CNAPP lets a business benefit from a unified continuous security structure without any added investments by way of more manpower or investment in more tools.

The compelling case for CNAPP in cybersecurity

The global CNAPP market is set to grow at 19.9% (CAGR) between 2022 and 2027, to USD 19.3 billion, driven by a growing risk of breaches and reported incidents of cyber threats, an increasing use of cloud solutions, a manpower crunch within the IT security teams in-house, as well as the potential vulnerability posed by an increasingly WFH/remote workforce.

By 2025, 60% of enterprises will have consolidated cloud workload protection platform (CWPP) and cloud security posture management (CSPM) capabilities to a single vendor, up from 25% in 2022. 2023 Gartner® Market Guide for Cloud-Native Application Protection Platforms

CNAPP was built to protect cloud-based infrastructure and applications. The solution is agile, dynamic and scalable. Large existing cloud users like ISVs and SaaS companies have begun to see the benefits of CNAPP.

The issue of combined risk is something CNAPP is capable of dealing with. While security solutions like cloud infrastructure entitlement management (CIEM), cloud workload protection platform (CWPP) and cloud security posture management (CSPM) do offer data on vulnerability and risk they are unable to come together in a way that – as Gartner puts it – connects the dots. CNAPP identifies the effective risk across the various layers that comprise cloud-native applications, helping prioritize risk and easing the burden on overstretched security and developer teams.

Here are some features of CNAPP that make it the smart choice for enterprises that operate in the cloud.

• Is a combined cloud security solution
• Is purpose-built for cloud-native environments
• Is integrated with the app development life cycle
• Does not add additional complexity to the application
• Supports scanning and quick response to any misconfiguration

How to choose a CNAPP solution

There is a palpable shift underway in the market, to consolidate cloud security solutions and benefit from the ease and visibility that a single CNAPP solution brings.

If you are considering CNAPP, here is a quick guide to choosing the right partner. The exercise will be most effective if those doing the selection are drawn from the various teams that will be involved with or impacted by the solution – namely, developers, development security, app security, cloud security, workload security and middleware security teams.

Make a CNAPP decision for your cybersecurity!

Finding a good partner for your CNAPP solution is critical and Cloud Kinetics has the expertise you need. Cloud Kinetics offers CNAPP in partnership with Plerion, an all-in-one Cloud Security Platform that supports workloads across AWS, Azure and GCP. If securing your entire cloud with an all-in-one cloud security platform is on your mind, we can help!

Cloud Kinetics is an award-winning, certified cloud transformation and managed services partner headquartered in Singapore and operating globally. We use cutting-edge platform-driven services to accelerate and secure our clients’ digital and business transformation journeys. Get in touch with our cloud experts for a non-obligatory discussion at contactus@cloud-kinetics.com

You can also download the CNAPP Cloud Security Handbook Here

The post Cloud Native Application Security (CNAPP): A Game Changer In Cybersecurity appeared first on Cloud Kinetics.

We were thrilled by the turnout and participation at this exclusive session hosted by AWS, HashiCorp and Cloud Kinetics, where we explored the critical topic of Zero Trust Security Adoption in the Cloud.

As businesses migrate to cloud environments, the conventional approach to security is evolving. The shift from static and perimeter-based security to dynamic and identity-based security is a paradigm we cannot ignore. Zero Trust Security, rooted in the principle of trusting nothing and authenticating everything, is clearly the way forward.

Speakers

Partono Luminto

Sales Director
Cloud Kinetics

Hendra Tanto

Sr. Solutions Engineer
HashiCorp

Fitra Alim

Technical Director
Cloud Kinetics

Highlights of the session

• Participants gained insights into the latest advancements in cloud security strategies
• Sessions focused on best practices for implementing Zero Trust Security in organizations.
• A productive opportunity to network with peers and industry leaders in the cloud security domain

Agenda

• 15.00 – 15.30: Welcome and Registration
• 15.30 – 15.35: Welcome Address by Cloud Kinetics
• 15.35 – 15.55: Zero Trust in Action with Cloud Kinetics: Fitra Alim, Technical Director, Cloud Kinetics
• 15.55 – 16.15: The Pillars of Zero Trust X Vault & Boundary: Hendra Tanto, Sr Solutions Engineer, HashiCorp
• 16.15 – 16.35: Fun Activity / Coffee Break
• 16.35 – 16.55: Managing Secrets Securely: Hendra Tanto, Sr Solutions Engineer, HashiCorp
• 16.55 – 17.15: Managing Your Data Securely: Fitra Alim, Technical Director, Cloud Kinetics
• 17.15 – 17.35: Q&A Session
• 17.35 – 17.40: Closing Speech by Cloud Kinetics 
• 17.40 onwards: Networking & Dinner

We look forward to your presence at  our next knowledge-packed session. Together, let’s explore the future of cloud security through the lens of Zero Trust!

The post HashiCorp Day: Zero Trust Security Adoption appeared first on Cloud Kinetics.

According to the HashiCorp State of Cloud Strategy Survey, a significant 89% of participants emphasized the importance of security for successful cloud implementation. However, as organizations embrace the cloud, they face the challenge of reevaluating their approach to securing applications and infrastructure. The traditional notion of security, defined by a static and IP-based perimeter, is evolving into a dynamic and identity-based paradigm with no clear boundaries. This transformative concept is commonly referred to as zero trust security.

The increasing adoption of zero trust reflects the rising security challenges faced by enterprises. Organizations have seen their attack surfaces expand as remote work policies become more prevalent and endpoint devices are used outside the corporate network. Concurrently, the frequency and intensity of cyberattacks have significantly increased.

Zero Trust is based on three guiding principles that shape its implementation:

Verify explicitly: The Zero Trust paradigm does not assume trust by default. Users must actively request access to resources, and they must provide proof of identification. Authentication and authorization are required depending on a variety of data points, such as user identification, location, device, service or workload, data classification, and anomalies.

Impose least-privileged access: Each user is only given the privileges required for their work. This restricts users to just-in-time and just-enough access, employs risk-based adaptive controls, and implements data security measures. As a result, the risk of unintentional or purposeful misappropriation of corporate assets is reduced.

Assume breach: Until proven otherwise, every user within the organization, including employees, contractors, partners, and suppliers, is regarded as potentially malicious. To guard against this risk, security measures should be put in place. Access must be segmented by network, user, device, and application, and data must be encrypted. Analytics must be used for threat detection and better security.

Top use cases of Zero Trust

Reducing business and organizational risk: Zero-trust solutions ensure that applications and services can communicate only after verification based on their identity attributes. This approach reduces risk by uncovering the presence of assets on the network and how they communicate. Moreover, zero-trust strategies eliminate overprovisioned software and services while continuously verifying the credentials of every communicating asset.

Gaining access control over cloud and container environments: The migration to the cloud raises concerns regarding access management and loss of visibility. Zero-trust architecture addresses these concerns by applying security policies based on workload identities directly tied to the workloads themselves. This approach ensures that security remains closely integrated with protected assets, independent of network constructs like IP addresses or ports, and guarantees consistent protection as the environment evolves.

Thorough inspection and authentication: Zero trust operates on the principle of least privilege, assuming every entity to be hostile. Each request undergoes a thorough inspection, including authentication and permissions assessments for users and devices, before granting trust. Continual reassessment occurs as contextual factors change, such as user location or accessed data. By eliminating trust assumptions, even if an attacker infiltrates the network through a compromised device, their ability to access or steal data is restricted due to the zero-trust model’s secure segment isolation.

4 reasons organizations are opting for Zero Trust security

Enhanced cybersecurity: Zero trust models enable companies to establish more effective cybersecurity practices. This provides reassurance that even in the event of a cyberattack, the data remains secure from malicious actors.

Compliance support: Zero trust models help organizations meet compliance requirements, such as HIPAA regulations. By implementing a zero-trust approach, companies can ensure compliance without worrying about potential issues arising later due to non-compliance.

Risk reduction: By allowing access only when needed and limiting unnecessary access, zero-trust models reduce risks for businesses. This approach protects against both internal threats like malware infections and external threats like phishing attacks and ransomware.

Comprehensive data protection: With a zero-trust model, you can have peace of mind knowing that your data is safeguarded. This approach covers a wide range of threats, providing protection against various internal and external risks.
By following the core principles of zero trust, organizations can strengthen their security posture, comply with regulations, reduce risks, and ensure the safety of their valuable data.

Zero trust security with HashiCorp

HashiCorp offers solutions for enterprises that need zero trust security for multi-cloud environments. It manages secrets across multiple clouds and private data centres, enforces security with identity and provides governance through policies. HashiCorp Vault enables enterprises to centrally store, access, and distribute dynamic secrets like tokens, passwords, certificates, and encryption keys across any public or private cloud environment. Unlike burdensome ITIL-based systems, HashiCorp solutions issue credentials to both people and machines in a dynamic fashion, creating a secure, efficient, and multi-cloud solution suited to today’s insecure world.

It’s part of the company’s “zero trust” security which secures everything based on trusted identities. Organizations can use zero trust to manage the transition to the cloud while maintaining the level of security required, one that trusts nothing and authenticates and authorizes everything.

There are now thousands of companies who seek to leverage the cloud (whether hybrid or multi-cloud) to run mission-critical workloads. It’s imperative that they seriously consider zero trust to secure access to authorized personnel. That’s where Cloud Kinetics and HashiCorp can help significantly.

Organizations are rethinking how to secure their apps and infrastructure on the cloud. Security in the cloud is being recast from static, IP-based (defined by a perimeter) to dynamic, identity-based (with no clear perimeter). This is the core of zero trust security.

This is especially true with emerging and booming markets. Sandy Kosasih, Cloud Kinetics Country Director for Indonesia, says, “HashiCorp’s approach to identity-based security and access provides a solid foundation for companies to safely migrate and secure their infrastructure, applications, and data as they move to a multi-cloud world.” Suhail Gulzar, HashiCorp’s Regional Manager of Solutions Engineering for Asia, adds: “Companies use different identity platforms for federated systems of record. Leveraging these trusted identity providers is the principle of identity-based access and security. Our products provide deep integration with the leading identity providers.”

How does zero trust enable human-to-machine access?

“Traditional solutions for safeguarding user access used to require you to distribute and manage SSH keys, VPN credentials, and bastion hosts, which creates risks of credential sprawl and users gaining access to entire networks and systems. Cloud Kinetics deploys HashiCorp’s Boundary solution to secure access to apps and critical systems with fine-grained authorizations that don’t require managing credentials or exposing your entire network. This is an excellent security feature to protect the core network.”Fitra Alim, Cloud Kinetics Country Technology Officer

As security challenges continue to grow, embracing the zero-trust model becomes increasingly crucial for organizations aiming to safeguard their valuable assets from the ever-evolving threat landscape. If you have any questions about improving your cybersecurity practices with zero trust security, get in touch with us. Cloud Kinetics security specialists will be happy to have a non-obligatory discussion with you.

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Participants joined AWS, Snyk and Cloud Kinetics for a deep dive into shifting security left and enhancing the security of their containers and infrastructure as code (IaC).

This workshop also offered hands-on with Amazon Inspector, a native vulnerability management service, and Snyk’s developer security tools that can help find and automatically fix vulnerabilities in code, dependencies and containers.

Keynote speakers explained how these tools could improve the security of containers deployed on AWS and how to use AWS and Snyk tools to develop more securely.

Speakers:

Kimberly Dickson

Security Solutions Architect
AWS

Abhijit Neelgar

Director of Alliances and Channel Sales
Snyk

Nidhi Mishra

Senior Channel Solutions Engineer
Snyk

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