Petronella Cybersecurity News

Secure MLOps: Model Risk, Controls, and Compliance Introduction Machine learning systems now decide credit approvals, route ambulances, screen job applicants, flag fraud, and generate content at industrial scale. With that reach comes a simple truth: if models go wrong or get abused, the blast radius is enormous. Secure MLOps is the discipline that combines engineering […]

HIPAA-Compliant GenAI: From Pilot to Production Healthcare organizations are eager to harness generative AI to reduce administrative burden, speed up documentation, and improve patient communication. Yet the moment protected health information (PHI) enters the picture, the operational and legal stakes rise sharply. The path from a promising proof of concept to a safe, compliant, and […]

NIST CSF 2.0 in Practice: A Board-Level Cyber Roadmap Board accountability for cybersecurity is no longer an abstract concept. With regulatory scrutiny intensifying, threat actors professionalizing, and digital dependencies multiplying, boards need a pragmatic way to steer cyber risk as a core business issue. The NIST Cybersecurity Framework 2.0 (CSF 2.0) offers that structure—but the […]

Zero Trust for OT & IoT: Securing Physical Ops Introduction: From “trusted perimeters” to verifiable safety Operational technology (OT) and the Internet of Things (IoT) now run factories, energy grids, hospitals, buildings, and logistics chains. These systems no longer live on islands. They exchange data with enterprise IT, cloud analytics, and remote maintenance teams. The […]

Govern AI Code Assistants: Speed Without IP Risk AI code assistants are transforming software delivery. They autocomplete boilerplate, generate test scaffolding, translate APIs, and even propose refactors. Teams report double-digit improvements in pull request throughput, fewer context switches, and happier developers. Yet the same systems that accelerate output also change the intellectual property risk profile […]

Platform Engineering: Build Your Internal Developer Portal Platform engineering has emerged as a pragmatic answer to the operational complexity of modern software delivery. Instead of every team re-solving infrastructure, security, and deployment for themselves, a platform team abstracts common workflows into paved roads that are safe, fast, and delightful for developers. The centerpiece of that […]

Confidential Computing: Collaborate Without Leaking Data Organizations increasingly face a paradox: the highest-value insights lie in joint analysis across data sets that span partners, competitors, and regulators, yet the risk of exposure, misuse, and regulatory breach grows with every copy and movement of data. Confidential computing resolves this paradox by allowing multiple parties to compute […]

Taming the “❌ Invalid response from OpenAI”: How to Build Resilient AI Integrations Few messages trigger more anxiety in an AI-powered application than a stark “❌ Invalid response from OpenAI.” It can appear sporadically in production logs, blow up critical user flows, and make debugging feel like chasing smoke. While the exact wording varies by […]

Security Data Lakes: Cut SIEM Spend, Improve Detection Security operations want two things that often feel at odds: comprehensive visibility and manageable cost. Traditional SIEM platforms are great for real-time alerting and correlation, but their ingest-based pricing and proprietary data stores create painful trade-offs. Teams either dial back telemetry to stay under budget or accept […]

Data Contracts: Stop Bad Data at the Source Introduction: A pact that changes outcomes Every data team has lived the same story: a quietly changed field upstream derails dashboards, machine learning features go stale, and urgent backfills devour a week of engineering time. Most fixes happen downstream where symptoms are visible, yet the cause sits […]

Passkeys for Enterprise: A Passwordless Playbook Enterprises have spent the last decade layering more controls on top of fragile passwords: complexity rules, frequent resets, one-time codes, push approvals, and security questions. Yet breaches and phishing still happen at scale, help desks remain overloaded with account recovery calls, and users experience friction at the worst possible […]

Model Provenance: The SBOM for Enterprise AI Introduction Enterprises are racing to operationalize generative AI, yet most lack a reliable way to answer the simplest questions about their models: What is inside? Where did it come from? Who changed it, when, and why? In software, the answer is the Software Bill of Materials (SBOM), a […]

On-Device AI: Cut Latency, Cloud Costs, and Risk Over the past decade, AI experiences have been delivered largely from the cloud: apps captured input locally, sent it to a remote model, then waited for a response. That architecture made sense while models were large, hardware-constrained, and tooling immature. But the landscape has shifted. Modern phones, […]

Data Clean Rooms: Privacy-Preserving Growth Engine Data clean rooms have emerged as a way for organizations to collaborate on data without sharing raw, personally identifiable information. They promise the best of both worlds: measurable business growth through richer insights and activation, and robust privacy protections aligned with evolving regulations and consumer expectations. When designed well, […]

Data Mesh vs Data Fabric: Choosing Your Enterprise Future Enterprises are swimming in data yet struggle to put it to work. Two architectural movements dominate the conversation: Data Mesh and Data Fabric. Each promises to tame complexity, accelerate delivery, and govern safely at scale. Yet they approach the challenge from different starting points—one emphasizes organizational […]

Knowledge Graphs for Enterprise AI: From Silos to Value Enterprises have spent decades collecting vast amounts of data, yet struggle to convert it into timely, trustworthy insight. Data lives in silos, teams speak different vocabularies, and AI systems hallucinate or drift because they can’t ground their answers in a shared understanding of the business. Knowledge […]

RAG vs Fine-Tuning: A Buyer’s Guide for Enterprise AI Enterprises are moving past pilots and into production with generative AI, but many teams stall on a basic design choice: Should we use retrieval-augmented generation (RAG), fine-tuning, or both? The right answer changes cost, time-to-value, risk profile, and even the organizational skill set you’ll need. This […]

The Machine Identity Crisis in Cloud Security Introduction: When Machines Outnumber People In modern cloud environments, machines outnumber humans by orders of magnitude. Microservices, serverless functions, data pipelines, build agents, IoT gateways, and bots all talk to each other—and to external services—using non-human credentials. These machine identities are the connective tissue of digital systems, and […]

Post-Quantum Cryptography: A CIO Readiness Guide Introduction Quantum computing promises breakthroughs in science and industry, but it also threatens the cryptography that protects digital business. As a CIO, you don’t need to wait for a fault-tolerant quantum computer to be operational to feel the impact. Strategic decisions you make in the next 12–24 months will […]

Sovereign AI: Data Residency as a Competitive Edge The term “sovereign AI” is quickly moving from policy papers and keynote slides into boardroom decisions and product roadmaps. At its core, it captures a simple idea: organizations and countries want control over the data, models, and infrastructure that underpin their most valuable AI capabilities. In practice, […]