Daksh Pathak

@dakshhhhh16 · User

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GSoC'26 @uaanchorage | LFX'26 @KubeScape | Maintainer @OpenSSF - MinderSec | Machine Learning | DevOps

@CNCF12 followers36 repositories

Repositories

dakshhhhh16/kubescape

Kubescape is an open-source Kubernetes security platform for your IDE, CI/CD pipelines, and clusters. It includes risk analysis, security, compliance, and misconfiguration scanning, saving Kubernetes users and administrators precious time, effort, and resources.

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dakshhhhh16/cel-admission-library

This projects contains pre-made policies for Kubernetes Validating Admission Policies. This policy library is based on Kubescape controls, see here a comlete list https://hub.armosec.io/docs/controls

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dakshhhhh16/operator

Operator is an in-cluster component of the Kubescape security platform. It allows clients to connect to itself, listens for commands from the connected clients and controls other in-cluster components according to received commands.

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dakshhhhh16/helm-charts

Kubescape can run as a set of microservices inside a Kubernetes cluster. This allows you to continually monitor the status of a cluster, including for compliance and vulnerability management

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dakshhhhh16/regolibrary

The regolibrary package contains the controls Kubescape uses for detecting misconfigurations in Kubernetes manifests.

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dakshhhhh16/wagtail

A Django content management system focused on flexibility and user experience

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dakshhhhh16/supabase

The Postgres development platform. Supabase gives you a dedicated Postgres database to build your web, mobile, and AI applications.

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dakshhhhh16/guac

GUAC aggregates software security metadata into a high fidelity graph database.

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dakshhhhh16/p5.js

p5.js is a client-side JS platform that empowers artists, designers, students, and anyone to learn to code and express themselves creatively on the web. It is based on the core principles of Processing. Looking for p5.js 2.0? http://beta.p5js.org

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dakshhhhh16/StockSite-AI

Developed a production-ready dense object detection framework using YOLOv5x on SKU-110K, achieving 92.2% mAP@50 and 30+ FPS. Applied FP16/INT8 quantization, reducing size by 75% from 329MB to 83MB with <1% accuracy loss, and built cross-platform deployment support across PyTorch, TensorFlow, ONNX, and TFLite.

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dakshhhhh16/SearchSmith

Developer-friendly dashboard to turn Google Search Console data into brand insights.

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