๐—ป๐—ฝ๐—บ ๐—ฆ๐˜‚๐—ฝ๐—ฝ๐—น๐˜†-๐—–๐—ต๐—ฎ๐—ถ๐—ป ๐—”๐˜๐˜๐—ฎ๐—ฐ๐—ธ

๐Ÿ”Ž๐—ฆ๐˜๐—ฟ๐—ฒ๐—ป๐—ด๐˜๐—ต๐—ฒ๐—ป๐—ถ๐—ป๐—ด ๐—–๐˜†๐—ฏ๐—ฒ๐—ฟ๐˜€๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜†: ๐—Ÿ๐—ฒ๐˜€๐˜€๐—ผ๐—ป๐˜€ ๐—ณ๐—ฟ๐—ผ๐—บ ๐˜๐—ต๐—ฒ ๐—ฅ๐—ฒ๐—ฐ๐—ฒ๐—ป๐˜ ๐—ป๐—ฝ๐—บ ๐—ฆ๐˜‚๐—ฝ๐—ฝ๐—น๐˜†-๐—–๐—ต๐—ฎ๐—ถ๐—ป ๐—”๐˜๐˜๐—ฎ๐—ฐ๐—ธ

Earlier this month, 18 widely used npm packages were compromised in one of the most significant supply-chain attacks on the JavaScript ecosystem. The breach originated from a phishing campaign impersonating npm support to obtain two-factor authentication credentials. Once the attackers secured access, they published malicious updates containing crypto-stealer code, exfiltrating cryptocurrency from millions of users.

The incident not only demonstrated the significant damage a supply-chain attack can cause but also showed how attackers are increasingly exploiting human factors like phishing to gain initial access.

A comprehensive security strategy needs to be adopted to effectively address these evolving threats. At Ringus, we have experienced professionals that provide a range of security services designed to identify and remediate weaknesses across both technical systems and human factors. Our key services include:
๐Ÿ’ก Penetration Testing: Simulate real-world attacks to uncover vulnerabilities in your applications and network environment.
๐Ÿ’ก Vulnerability Scanning: Perform thorough scans to identify and prioritize security gaps across your systems and networks.
๐Ÿ’ก Phishing Simulation: Conduct realistic phishing campaigns simulation to assess and improve employee awareness and response.
 

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Speed Without the Sprawl

Leveraging OutSystems' rapid development strengths, our team achieves true Agile development, focusing intensely on user requirements. However, requirements are never fixed; they take time to refine within the project's cycle. If a developer simply builds projects based on the initial requirements, it leads to significant rework when those requirements are inevitably revised. This creates serious technical debt that can derail a project's schedule. To combat this, we strictly follow the OutSystems Canvas Design architecture to define each module's usage and content. We generalize logic into foundational modules, optimizing reusability and providing high adaptability when requirements change. This approach allows us to eliminate complicated dependenciesโ€”avoiding the deployment nightmares that plague monolithic systems. The Real-World Challenge: "The Spaghetti Monolith" Weโ€™ve all seen it. A project starts fast. The "Idea-to-App" time is record-breaking. But as sprints pass and requirements evolve, the "interest rate" on technical debt spikes. Suddenly, changing a simple UI element breaks a core business process because the logic was trapped inside the screen. Deployment becomes a "big bang" event where everything must go live at once because of circular dependencies. In our team, we don't just "code fast"; we architect for resilience. Our Solution: The 4 Layer Canvas Strategy We treat the 4 Layer Canvas not just as a suggestion, but as our structural imperative. Here is how we use it to handle volatile requirements:  Isolating Volatility (End-User Layer): We keep our User Interfaces (UI) and interaction logic in the End-User Layer. This layer is highly volatileโ€”it changes constantly based on user feedback. By isolating it, we can redesign a "Customer Portal" without risking regressions in our core business rules.Stabilizing Business Logic (Core Layer): We abstract our entities and business rules into the Core Layer. This is the backbone of our factory. Whether the data is accessed by a Mobile App, a Web Portal, or a Timer, the validation rules remain consistent. This promotes the "Don't Repeat Yourself" (DRY) principle.Enabling Independent Deployments: By using Service Actions (Weak Dependencies) in our Core layer, we decouple our modules. This allows different squads to deploy changes independently without forcing a factory-wide refreshโ€”a critical enabler for our CI/CD pipelines.The Governor: AI-Driven Architecture How do we ensure we stick to these rules when moving at Agile speeds? We don't just rely on manual code reviews; we use the AI Mentor System. This tool acts as our automated architect. It scans our entire factory to detect architectural violations that humans might miss, such as: Upward References: Preventing foundational libraries from depending on business logic.Side References: Ensuring our End-User apps don't tightly couple with one another.Circular Dependencies: Identifying the "deadly embrace" between modules that locks deployments.The AI Mentor System quantifies this debt, allowing us to pay it down proactively before it hinders our release velocity. Join a Team That Values Architecture In our Taiwan office, we believe that low-code doesn't mean "low-architecture." We are building resilient, composable enterprise ecosystems that can scale. If you are a developer who cares about structural integrity, clean code, and mastering the art of OutSystems architecture, we want to hear from you. 

๐—ก๐—ฒ๐˜„ ๐—ฅ๐—ฒ๐˜๐—ฟ๐—ถ๐—ฒ๐˜ƒ๐—ฎ๐—น ๐—”๐˜‚๐—ด๐—บ๐—ฒ๐—ป๐˜๐—ฒ๐—ฑ ๐—š๐—ฒ๐—ป๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป (๐—ฅ๐—”๐—š) ๐—”๐—œ ๐—š๐˜‚๐—ถ๐—ฑ๐—ฎ๐—ป๐—ฐ๐—ฒ

Germany's Data Protection Conference just released comprehensive guidance on AI systems with Retrieval Augmented Generation (RAG) - a game-changer for organizations implementing AI governance under ISO 42001.Key Compliance Requirements:๐Ÿ”ŽData Accuracy - Enhanced Large Language Model (LLM) responses but error accountability remains๐Ÿ”ŽTransparency - Improved document traceability within RAG knowledge bases๐Ÿ”ŽPurpose Limitation - Technical implementation through client/functional separation๐Ÿ”ŽData Minimization - Strategic vector database content management๐Ÿ”ŽData Subject Rights - Full rights coverage across prompts, outputs, and databases๐Ÿ‘‰ Why This Matters for ISO 42001:RAG systems are becoming mainstream for internal chatbots and enterprise AI. The Data Protection Conference guidance directly aligns with ISO 42001's requirements for AI risk management, data governance, and algorithmic accountability.Organizations deploying RAG technology must now ensure their AI management systems comply with both German data protection standards and international ISO 42001 frameworks.Our cybersecurity and privacy consultation expertise helps organizations navigate these complex requirements, ensuring your RAG implementations meet regulatory standards while maximizing business value.