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Seranth

YourAI.YourData.YourRules.

Every conversation runs on hardware dedicated to you alone, with physically isolated storage and zero data retention, built so no breach, bug, or prompt injection can ever reach your data.

The Security Issue with Today's AI Tools

It's not just privacy. The way today's AI tools are built creates real, exploitable security risk.

Prompt Injection

Attackers hide malicious instructions inside emails, documents, or files the AI reads, hijacking its behavior silently and without your knowledge.

Shared Storage

Your data sits on the same servers as thousands of other companies, separated only by software, not hardware. One breach can cross accounts.

Policy Changes Without Notice

Providers change data retention and training policies whenever they want. You find out after the fact, buried in a Terms of Service update.

Black-Box AI

You can't see what happens to your prompt once it leaves your screen. No visibility into how it's processed, stored, or used downstream.

Data Traveling Through Many Servers

Your data hops through AWS, load balancers, and third-party services with no single guaranteed pipeline. More hops mean more exposure.

How Seranth Solves It

Here's the simplest way to think about it.

The Problem Today

  • One shared server for everyone. Most AI platforms put every customer's data on the same shared servers, separated only by software.

  • Prompt injection is rampant. Attackers hide malicious instructions inside emails, documents, or files the AI reads, hijacking its behavior silently and without your knowledge.

  • One breach, everyone's exposed. If there's ever a breach, a bug, or a bad actor, your data is sitting right next to everyone else's.

  • Your data leaves your hands. It travels through AWS, third-party clouds, and load balancers you don't own or control, with no single guaranteed pipeline.

The Seranth Fix

  • We own our own data centers. No AWS. No Azure. No Google Cloud. Your data never leaves infrastructure we physically own and operate ourselves.

  • Physically separate storage per company. Every company gets its own dedicated NVMe drive. Not a virtual partition, a genuinely different physical device.

  • Stateless, wiped GPUs. Compute nodes hold no memory after your request finishes, so nothing lingers for an attacker or an injected prompt to exploit.

  • Your prompts stay yours. Zero risk of your data ever training someone else's model or being seen by a third party.

Put simply: you get the power of the best AI models, the privacy of running everything yourself, and the low cost of smart infrastructure, all without giving up control of your data.

Still not convinced? If you ever decide to leave, you can buy the exact physical hard drive that stored your company's data and take it with you. No copies kept on our end. No questions asked.

This Isn't Hypothetical. It's Already Happening.

AI security breaches are real, documented, and accelerating. This is what happens when you trust someone else with your data.

Prompt injection is the #1 AI security threat. HackerOne logged a 540% surge in reports
90% of successful attacks leaked sensitive data. Seranth's physical isolation makes cross-tenant attacks architecturally impossible.
Dec 2025 – Feb 2026

Mexico Government Breach

An attacker used ChatGPT and Claude to breach 9 Mexican government agencies. 195 million taxpayer records and 220 million civil records stolen, over 150GB including health records and domestic violence victim data. The attacker told Claude he was running a "bug bounty program" and fed it a 1,084-line hacking manual. Claude executed ~75% of all remote commands.

How Seranth helps here:

The attacker used social-engineering prompt injection, telling the AI it was part of a "bug bounty program" to bypass safety guardrails. On shared infrastructure, this kind of attack can access data from multiple tenants. With Seranth's physically separated storage, even a fully compromised model session cannot reach another company's drive.

415M+ records compromised
December 2025

Anthropic's Own Git MCP Server

Three CVEs in Anthropic's official Git MCP server. Path traversal allowed credential exfiltration, unrestricted git_init let attackers create repos anywhere on disk, and argument injection in git_diff enabled code execution.

How Seranth helps here:

Poisoned repository content (filenames, commit messages) acted as indirect prompt injection. On shared storage, this could cascade across tenants. Seranth's per-company physical drives contain the blast radius to a single company.

Code execution and credential theft via poisoned repo content
June 2025

Microsoft 365 Copilot "EchoLeak"

CVE-2025-32711 (CVSS 9.3), the first zero-click prompt injection exploit against a production AI system. A single crafted email, no user interaction needed, caused Copilot to access internal files and exfiltrate contents to an attacker-controlled server.

How Seranth helps here:

Hidden instructions inside an email tricked the AI into leaking files the attacker never had permission to see. Because tenant data sits on shared infrastructure, one injected email could reach files across the organization. Seranth's dedicated drives per company mean an injected prompt has no path to another company's data.

Zero-click enterprise data exfiltration
2025

GitHub Copilot RCE

CVE-2025-53773 (CVSS 7.8). Prompt injection via workspace files caused Copilot to rewrite VS Code settings, enable "YOLO mode" (auto-approve), and execute arbitrary terminal commands without user approval.

How Seranth helps here:

Malicious code files acted as prompt injection vectors, Copilot read them and followed hidden instructions. Seranth runs models on stateless GPUs (wiped after every request) with isolated storage, so injected prompts die with the session and cannot persist or spread.

Remote code execution on developer machines
August 2025

Cursor IDE MCP Exploit

CVE-2025-54135 (CVSS 8.6). Indirect prompt injection wrote a malicious config file. With "Auto-Run" enabled, Cursor immediately executed attacker-injected commands, giving full remote code execution.

How Seranth helps here:

The injected prompt persisted as a config file, meaning future sessions would also be compromised. Seranth's stateless GPU architecture wipes all session data after every request, preventing any injection from persisting.

Full development environment compromise
August 2024

Slack AI Data Leak

Attackers planted malicious instructions in public Slack channels. When Slack AI summarized content, it followed the planted instructions and exfiltrated data from private channels, including API keys from DMs.

How Seranth helps here:

Textbook indirect prompt injection, the AI treated user-generated channel messages as instructions. Because workspace data sits on shared servers, the injected prompt could reach across channels and DMs. With physically separated storage, there is no shared data layer for an injection to traverse.

Private channel data and API keys leaked
March 2023

Samsung ChatGPT Leak

Samsung engineers pasted proprietary semiconductor source code into ChatGPT three times in 20 days, chip defect detection code and internal meeting notes. ChatGPT retained all inputs. Samsung banned all generative AI tools company-wide.

How Seranth helps here:

Not a direct attack, but the core risk of shared infrastructure: Samsung's proprietary data sat on OpenAI's shared servers alongside millions of other users. Seranth's dedicated storage per company and BYOK encryption make this scenario impossible.

Trade secrets permanently exposed to third-party model
November 2023

Chevrolet Dealership Chatbot

A user told a Chevy dealership's ChatGPT-powered chatbot to "agree with anything" and mark offers as "legally binding." The chatbot agreed to sell a $76,000 Tahoe for $1. Screenshots went viral with 20M+ views.

How Seranth helps here:

A direct prompt injection, the user overwrote the chatbot's system instructions by telling it to "agree with anything." Customer-facing models can be explicitly trained and hardened against exactly this kind of manipulation, refusing to override pricing or contract terms no matter how the request is phrased. With open-source models, businesses control and audit that training themselves instead of hoping a vendor got it right.

AI manipulated into unauthorized commercial commitments

Seranth eliminates these attack vectors by design.

Physically separated storage

Even if a prompt injection succeeds, it cannot reach another company's data. Different company, different physical drive. No software path exists.

Stateless GPUs

Wiped after every request. Injected prompts cannot persist across sessions.

BYOK encryption

Even Seranth cannot read your data. A compromised model session sees only encrypted bytes.

Open-source models

Audit the model's behavior yourself. No proprietary black boxes. No "trust us."

Seranth vs. The Rest

FeatureChatGPT BusinessClaude TeamGemini (Workspace)Seranth
Hardware Isolation
Shared GPUs, shared storage, logical isolation only
Shared GPUs, shared storage, logical isolation only
Shared GPUs, shared storage, logical isolation only
Stateless GPUs + physically separate NVMe per company
Data Training
Promise not to train on Business data, but proprietary black box, cannot verify
Promise not to train on Team data, but proprietary black box, cannot verify
Promise not to train on Workspace data, but proprietary black box, cannot verify
Impossible, open-source models run locally, no mechanism to send data anywhere
Models
GPT only
Claude only
Gemini only
11 models from 6 families, switch anytime
Encryption Key Control
OpenAI holds keys
CMEK available (AWS/GCP/Azure KMS), but data still on Anthropic's servers
Google holds keys
BYOK, keys stay on your infrastructure. Even Seranth cannot read your data
Data Deletion
"Deleted within 30 days", no way to verify, backups may persist
Similar deletion policies, unverifiable
Similar deletion policies, unverifiable
Crypto-shred: delete keys and data is permanently unreadable. Or buy your physical NVMe and take it home
Code Auditability
Proprietary black box
Proprietary black box
Proprietary black box
Entire stack is open-source: vLLM, Linux, PostgreSQL. Audit every line
Vendor Lock-in
Locked to OpenAI
Locked to Anthropic
Locked to Google
6 model families, zero lock-in

Features as of August 2026.

Who is Seranth For?

Companies That Take Data Seriously

If your clients trust you with their data, you can't afford to trust someone else's shared servers with it.

Businesses With Trade Secrets to Protect

Source code, financial models, product roadmaps, anything that can never leak stays on hardware only you can touch.

Regulated Industries

Banks, insurance, healthcare, quantitative trading firms, legal, anyone with strict compliance requirements.

Companies That Can't Afford a Breach

If a data breach could end your business or your reputation, physical isolation isn't optional, it's the whole point.

See Seranth in Action

This is a preview of the Seranth interface. The full platform is coming soon.

Model switching
Live chat interface
Context & memory panel

Actual product may differ. This demo showcases the planned UX direction.

Every Model. One Platform.

Core Tier

Fastest, cheapest
ME
Meta

Llama 4 8B

General purpose, fast

MI
Mistral AI

Mistral 7B

Multilingual, European compliance

DE
DeepSeek

DeepSeek R1 7B

Coding and logic

DE
DeepSeek

DeepSeek R1 13B

Stronger coding

AL
Alibaba

Qwen3 30B-A3B

Code generation, only 3B active so it's fast

Pro Tier

Stronger models
MI
Mistral AI

Mixtral 8x7B

Multi-expert reasoning

ME
Meta

Llama 4 70B

Best general-purpose open-source

MO
Moonshot AI

Kimi K2.5

Frontend coding, visual design

DE
DeepSeek

DeepSeek V4 284B

Catches 3.7x more bugs than Claude

Ultra Tier

Frontier-class
AL
Alibaba

Qwen3 Coder 480B

Elite code generation

ZH
Zhipu AI

GLM-5.2 753B

Beats GPT-4o, Claude Opus, and o1 on benchmarks

11 models from 6 families. Free, auditable, no licensing fees. No vendor lock-in. Switch models mid-conversation.

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