# GPU Security

Ensuring **complete security and privacy** while renting GPUs is critical when working with **AI models, proprietary data, or sensitive computations**. Nebula AI is designed with **strict isolation**, preventing hosts from accessing rented machines while ensuring **your workloads remain fully private and offline**.

This section covers **how Nebula AI guarantees security**, **best practices for renters**, and how to **eliminate any risk of data exposure**.

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### **Host Isolation & Zero Access Policy**

Unlike centralized cloud providers, where infrastructure owners might have **root access to rented instances**, Nebula AI enforces a **zero-access policy** for hosts. This ensures:

* **No host-side access** to running workloads, active processes, or memory.
* **No ability to monitor GPU activity** beyond standard system telemetry.
* **No storage retention after rental expiration**, with automatic **data wiping** upon session termination.

All GPU rentals operate in **isolated, containerized environments**, preventing **unauthorized data access, logging, or tracking** by the host.

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### **Running Secure Workloads with Full Isolation**

When deploying **AI training, deep learning inference, or cryptographic computations**, it's essential to **fully isolate** your processes. Nebula AI supports:

* **Ephemeral Containers** – Workloads are executed in a **temporary, disposable instance** that is completely reset after rental.
* **No Persistent Storage** – Ensures that no **host or future renter** can access previous workloads.
* **Full Disk Encryption** (Coming Soon) – GPU memory and temporary storage will be **encrypted at runtime**, ensuring an additional layer of protection.

If **absolute security is required**, consider encrypting **all sensitive datasets and model checkpoints** before uploading them to a rented GPU.

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### **Network Security & Remote Access Best Practices**

GPU rentals on Nebula AI provide **remote access** via **SSH, Jupyter Notebook, or API connections**. To prevent unauthorized interception:

* **Disable unnecessary ports and services** before starting computations.
* **Rotate SSH/API credentials** after every session to prevent key reuse.
* **Always run workloads in an isolated virtual environment** to avoid external dependencies.

If your project involves **highly confidential data**, consider running computations **fully offline** by downloading all required dependencies **before execution**.

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### **Preventing Data Leaks & Side-Channel Risks**

Even though **hosts cannot access running processes**, side-channel risks exist in **traditional cloud environments** due to shared infrastructure. Nebula AI mitigates this by:

* **Dedicated GPU Execution** – Ensures that each rental is assigned **a fully isolated GPU instance**, avoiding shared execution with other workloads.
* **Containerized Environments** – Prevents unauthorized access to memory and computational states.
* **No Host-Controlled Monitoring Tools** – Disables potential logging mechanisms that could expose execution traces.

For additional security, **consider obfuscating model weights, encrypting input datasets, and executing workloads in a zero-trust environment**.

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### **Data Erasure & Automatic Cleanup**

At the end of each rental session, Nebula AI ensures **complete data erasure**, eliminating any possibility of data retrieval. The termination process includes:

1. **Secure GPU Memory Wipe** – Clears all allocated memory and computational states.
2. **Instance Termination & Rebuild** – The rented machine is reset, preventing any residual access.
3. **Filesystem Overwrite** – Temporary storage is erased, ensuring **no forensic recovery** is possible.

{% hint style="info" %}
Before rental termination, always verify that **your data is backed up externally**, as all files will be **permanently lost**.
{% endhint %}

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### **Decentralized Privacy & Future Security Enhancements**

Nebula AI is actively working on **additional privacy features** to enhance security, including:

* **Encrypted AI Execution** – Running AI models in **fully homomorphic encrypted environments** for zero-trust processing.
* **Multi-Party Computation (MPC) Integration** – Allows multiple participants to train AI models collaboratively **without exposing raw data**.
* **Self-Destructing Compute Instances** – Disposable GPU workloads that automatically **delete all traces of execution** once completed.

These upgrades will position Nebula AI as **the most secure GPU rental platform**, ensuring **absolute data privacy and computational integrity**.