Project Jupiter Explained: Developing a Self-Hosted Security and Monitoring Platform
I’m currently developing Project Jupiter, a self-hosted, multi-tenant SIEM + SOAR platform designed with OCSF-native architecture. The landing page (projectjupiter.in) serves as a showcase of the project’s ongoing research and development, highlighting how ML and AI—through embeddings, vector databases, and LLM-driven analysis—can enhance threat detection, power RAG-based investigations and automate response playbooks.
Why "Jupiter"?
I named this project Jupiter for two reasons:
Just like the planet Jupiter, which is massive and protective in our solar system, I want this platform to act as a shield — absorbing threats before they can do damage.
The name also reflects scale. A platform that starts small in my hands but has the potential to grow into something vast, resilient, and future-ready.
The Spark
Most cybersecurity tools today live at two extremes:
Enterprise platforms — powerful but noisy, expensive, and often locked to a single vendor.
Open-source tools — flexible but fragmented, difficult to set up, and not always future-proof.
I wanted to explore whether one person, with consumer-grade hardware, could build something different:
a self-hosted, privacy-first, AI-assisted security and monitoring platform.
The Vision
Project Jupiter is designed to be:
Learning-first → a journey of exploration and improvement.
Privacy-first → all data remains under user control.
Environment-agnostic → deployable on a laptop, server, cloud, or hybrid setup.
AI-assisted → using machine learning to reduce noise, spot anomalies, and accelerate response.
Future-proof → aligned with open standards like OCSF (Open Cybersecurity Schema Framework).
The Problems I’m Tackling
Alert fatigue → endless false positives overwhelm analysts.
Vendor lock-in → once you commit, it’s hard to leave.
Scaling costs → every log line becomes a billing problem.
Fragmentation → IT, OT, and physical security data live in silos.
The Roadmap
The build is split into clear phases:
Foundation → define scope, principles, and risks.
Core Infrastructure → flows, caching, and observability.
Ingestion & Normalization → parse events, map to OCSF, store efficiently.
Intelligence & Automation → threat intelligence, AI summaries, automated playbooks.
UX & Dashboards → tenant dashboards, reporting, chatbot copilot.
Ops & Recovery → backups, restore drills, resilience testing.
Why Share This?
Because cybersecurity shouldn’t be a black box.
By sharing Project Jupiter openly, I hope to:
Inspire students and hobbyists who want to learn hands-on security.
Explore how AI can make monitoring smarter and less noisy.
Show that meaningful tools don’t always need enterprise budgets.
What’s Next
This is just the prologue.
In the next article, I’ll dive into Phase 0: the blueprinting stage — the research, risks, and first design choices.
Follow along here on Hashnode as I document the journey 🚀
