SecureAI Guardian reads what a prompt actually means — not just which keywords it contains — and scores it across 9 detection layers before it ever reaches your AI model.
SecureAI Guardian sits between your users and your AI models, reading intent, scoring risk, and logging every decision — without adding meaningful latency.
Keyword filters catch what they've seen before. SecureAI Guardian is built around actual comprehension, so novel attacks and disguised requests don't slip through.
Prompts are read for real meaning and intent using a connected AI model — local via Ollama or cloud-hosted — not just scanned for trigger words.
Every prompt passes through tokenization, behavioral analysis, semantic relationships, and pattern matching before a verdict is reached.
Every decision comes with the specific rule that triggered it, so you can explain any Allow, Warn, Restrict, or Block to an auditor.
Every analysis is logged with timestamp, risk score, and reasoning, private to each signed-in account and ready to export.
Run entirely on your own hardware with Ollama for full data control, or use the built-in cloud backend so it works for every visitor instantly.
Every user signs in with their own account. History, settings, and results never mix between people using the same deployment.
Nothing gets Allowed, Warned, Restricted, or Blocked without a governance rule attached to it — so security teams can explain outcomes instead of guessing at a black box.
Tokenization, behavioral indicators, semantic relationships, contextual framing, and pattern matching all run on every single prompt — in real time, not on a delayed batch job.
Every prompt resolves to a single 0–100 risk score, mapped transparently to a governance outcome — no hidden weighting, no unexplainable model confidence number.
Alongside every score, the AI model writes out exactly why it reached that conclusion — in language a non-technical reviewer can actually read and trust.
Private per-account data, a permanent governance trail, and exportable logs make this suited for organizations that need to demonstrate control over AI usage.
Real accounts, real email verification, and a choice of AI engine — before a single prompt is ever analyzed.
Sign up with your email and a password through Supabase Auth.
Click the confirmation link Supabase sends before you can sign in.
Add your name, organization, and role on first login.
Cloud AI (Cloudflare Workers AI) or Local Ollama — your call.
Every submission is scored, explained, and logged to your private audit trail.
The same pipeline runs on every single request, whether it's a test in the dashboard or live traffic from your application.
A prompt is entered manually or arrives through your application, exactly as a user or system wrote it.
A connected model interprets intent — recognizing disguised requests, roleplay framing, and social engineering, not just flagged words.
Tokenization, behavioral indicators, semantic relationships, and pattern matching each contribute to a single risk score and category.
Allow, Warn, Restrict, or Block is returned instantly, with the governance rule applied and a permanent record in your audit log.
As more products wire real actions to AI models — refunds, database queries, code execution, customer support — the prompt itself became an attack surface. A single cleverly-worded message can talk a model into ignoring its instructions, leaking data, or taking actions it was never meant to.
Most defenses stop at keyword filters, which miss anything phrased differently than the examples they were trained on. SecureAI Guardian was built around a simpler idea: have an AI model actually read the prompt for what it means, the same way a human reviewer would, then back that judgment with a transparent, explainable governance layer — so every decision can be defended, not just trusted.
Prompt injection and jailbreak attempts don't target one industry — they target any system where a model's output can trigger a real-world action or expose real data.
Internal copilots and support bots wired to real business systems and data.
AI assistants with access to accounts, transactions, or fraud systems.
Clinical assistants handling sensitive patient data and records.
Research and administrative tools open to large, varied user populations.
Public-facing AI services that must be defensible and auditable.
Infrastructure providers hosting AI workloads for thousands of tenants.
Model providers whose own products can be turned against their guardrails.
Anyone shipping an LLM feature without a dedicated security review process.
Any product embedding a chat or agent feature into its core workflow.
No hidden pieces — this is the real, current architecture.
HTML5, CSS3, and vanilla JavaScript — no framework build step required.
Cloudflare Pages Functions serving REST-style API endpoints at the edge.
Cloudflare Workers AI for zero-setup cloud inference, with Ollama supported for fully local, private analysis.
Supabase Postgres with Row Level Security enforcing per-user data isolation.
Supabase Auth — real accounts, email verification, and session management.
Cloudflare Pages — global edge hosting for both the site and its API.
Real-time risk scoring, audit history, and governance status — all inside the dashboard your team signs into every day.
Start free on your own infrastructure, or scale up when you need managed cloud AI for every visitor.
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