Your AI agents are everywhere — browser, docs, inbox — and every one acts with your access. AariaSec learns each one's normal, so the instant one steps out of line, you know. Locally. Privately.
A real slice of the AariaSec console, running on sample data right here in your browser. Run a session, and see the content firewall wave it through while behavior gives it away.
Click through discovery, the live catch, session replay, and enterprise onboarding — in about two minutes.
No agents to rewrite, no cloud to configure. Point your AI traffic through AariaSec and it does the rest.
Install the app and route an agent with one line — HTTPS_PROXY. Discovery finds the rest of your AI apps automatically.
AariaSec learns each agent's normal — tools, egress, timing, token rhythm — recognized from day one, fully baselined in about three days.
When an agent drifts or is hijacked, a Red/Blue/White panel returns a clear verdict and risk score (0–100) — and can contain it, automatically.
Most tools scan the words an agent sends. AariaSec watches how it behaves — so an agent that's been tricked, and still has all your access, gets caught. Signatures miss that. Behavior doesn't.
Tool cadence, egress targets, token rhythm — measured continuously, scored against its own normal, not a generic rule set.
An independent AI panel argues both sides of every alert and returns a clear verdict with a risk score — not a black-box flag you're asked to trust.
Agents don't only get hacked — they wander. AariaSec watches for the slow drift away from normal, not just one-off injection attempts.
When one deployment flags a bad agent, every other recognizes it on day one — collective defense, while only anonymous hashes ever leave a device.
An estimated per-agent token spend — including browser and web-app AI that never shows up on any bill. A sudden cost spike is often the first sign an agent has gone off-script.
Runs entirely on your device. Prompts and responses are never stored at all — only their SHA-256 fingerprints, with a tamper-evident audit trail to prove it.
One environment variable routes agent traffic through AariaSec — no SDK.
Known agents are trusted on day 0; unknown ones learn over a short window.
Behavior that breaks the baseline triggers a Red/Blue/White debate.
A clear verdict, a risk score, and the full debate transcript — evidence you can replay.
Most tools assume they cover everything. AariaSec measures it — and shows you the gap. New AI gateways and routers (OpenRouter, LiteLLM, Azure OpenAI, Bedrock) quietly move agent traffic off the paths other tools watch. We detect them, flag any app pointed at an unmonitored one, and let you bring it under watch in one click.
api.openrouter.aiCustom LLM proxyThe free app secures one machine. Enterprise runs it across your whole fleet from one console — a single pane of glass that never takes your data to anyone's cloud. Prompts and behavioral data stay on each endpoint; the console only ever sees health, versions, and the anonymous hashes you consent to share.
See every enrolled install's health, version, and drift in one place. Push policy and staged version rollouts to a group, promote canary → broad, and roll back centrally — all without touching an endpoint.
SAML / OIDC single sign-on (MFA enforced by your IdP), SCIM user & group provisioning that maps directory groups to roles, and org-defined custom roles with least-privilege permission sets.
Stream detections to Splunk, open tickets in Jira / ServiceNow, and bulk-export events & alerts to your own warehouse. Metadata only — never prompt or response content.
Each install's management identity is kept cryptographically separate from the anonymous threat-intelligence it contributes. Enterprise-grade fleet manageability, with a privacy guarantee most EDR platforms can't make.
Five clips, under four minutes total — see it work, then why it matters.
.sha256 sidecar you can check before you run it.Two public artifacts, free to anyone. One documents how AI agents actually break in the wild. The other measures whether a monitoring system would catch it — ours included, scored in public alongside everyone else's.
A curated library of real-world incidents — prompt-injection campaigns, agent breaches, espionage patterns — each mapped to the behavioural rules that catch it and the controls we recommend. 25 incidents tracked and growing. No login, free on every tier.
Every other agent benchmark scores the agent — whether it can be jailbroken. PRAMANA scores the detector. It exists because our architecture never stores prompt content, so the corpus is publishable where a content-reading vendor's never could be.
We do not top our own leaderboard. A forty-line longitudinal baseline beats us on season v2, and we score zero on sybil coordination where it scores one. Those are real gaps, published deliberately — a benchmark that only embarrasses other people is marketing.
.sha256 sidecar — run shasum -a 256 -c <file>.sha256 (macOS/Linux) or Get-FileHash <file> (Windows).