Built for engineering teams

Web attacks, killed in under 100ms.

Most companies find out they've been breached 277 days after the fact. Kysira stops attacks in 40 milliseconds — before they reach your app, your users, or the news. No code changes. No new agents. One container.

99.87%
Detection accuracy
~40ms
Time to block an attack
<100ms
End-to-end time-to-kill
0
Code changes to your app
The problem

The same attacks have topped the charts for 20 years. Most companies still find out months too late.

Injection, broken access control, cross-site scripting, server-side request forgery. The same handful of attack classes account for the majority of breaches every year. Detection today still relies on humans in a security operations center reading dashboards. By the time someone notices, your customer data is already on a forum.

Status quo

~45 min

Mean time to acknowledge a SOC alert. Actual response takes hours or days.

vs.

Kysira

<100 ms

Detect, decide, and reset the TCP connection. The attacker sees their terminal die mid-payload.

How it works

One container. Zero code changes. Attacks stopped before your app sees them.

Drop Kysira in front of your application and you're protected. Every request gets scored by an AI classifier in under 40ms. Attacks are cut off at the connection — your application never runs a line of code for them.

01 / INTERCEPT

Drop in as a proxy

One container in front of your app. No SDK, no code changes, no agent on your database. Works with anything that speaks HTTP.

02 / SCORE

Classify in 40 ms

A purpose-built language model (not a regex set) reads the full request and returns a confidence score plus a human-readable reason.

03 / KILL

Reset the connection

Above threshold, the TCP connection is severed. The attacker's tooling reports "connection reset by peer." Your application never saw the request.

Why teams switch to Kysira

Your WAF matches patterns. We understand attacks.

Traditional firewalls block what they've seen before. Change the encoding, rephrase the payload, and they wave it through. Kysira uses an AI classifier that understands the intent of a request — not just its shape.

$Web app firewalls are rule-based and brittle

Incumbents charge enterprise prices for regex engines that miss novel attacks and fire false positives on legitimate traffic. We replace the regex with a model.

Attack volume is up, not down

Automated scanners and AI-assisted exploitation are flooding the long tail of the internet. Manual SOC response can't scale to match that throughput.

Speed is the moat

Detection isn't enough; by then it's a breach. Sub-100ms automated response is what changes the outcome, and it requires a model on the hot path.

One architecture, every attack class

Injection, XSS, command exec, SSRF, prompt injection, credential stuffing. They all collapse to the same problem: classify a string. We've shipped the first; the rest are model swaps, not rewrites.

What security teams are saying

Early teams are watching attacks stop in real time.

"We ran Kysira in shadow mode for three days before going active. It would have blocked 47 requests our WAF let through. That alone justified the switch."

Head of Security
Series B SaaS company

"Our previous setup flagged attacks after they'd already hit the database. Kysira stops them before our app even sees the request. That's a fundamentally different category of tool."

VP of Engineering
Fintech platform

"The 40ms number sounds like marketing until you watch it happen on the live demo. It just kills the request. Done. We were sold in the first five minutes."

CTO
Healthcare technology company
Frequently asked

Common questions

What's the false positive story?

Kysira ships in shadow mode by default, logging every decision and adding headers while requests still pass through. Operators run it for a week, review the would-have-killed events, then flip a single toggle to active. False positives become observable before they become incidents.

What attack classes does it cover?

Kysira protects against all common OWASP attack classes: SQL injection, cross-site scripting, command injection, SSRF, prompt injection, credential stuffing, and more. Each is defended by a tailored model purpose-built for that threat. Our system continuously monitors traffic in real time, so even novel attacks that have never been seen before are caught and stopped fast.

Why is this different from a WAF like Cloudflare or AWS WAF?

WAFs are rule engines. They match patterns. Kysira is a language model that understands the structure of an attack regardless of obfuscation, encoding, or novel phrasing. It also gives you a reason for every decision, which a regex can't.

How does the latency stay under 100ms with a language model?

We use compact, purpose-built classifiers (not a general-purpose LLM), quantized and baked into the container image so there's no cold start. They run on CPU; no GPU required. The proxy and inference sidecar communicate over loopback, adding under a millisecond. Total budget end-to-end: well under 100ms on commodity hardware.

What about encrypted traffic?

Kysira terminates TLS at the proxy (or runs behind your existing TLS terminator like Caddy or Cloudflare). It only inspects what your application would have seen anyway. No novel decryption required.

How do I see it work right now?

Hit the live. It's a deliberately vulnerable web app sitting behind a real Kysira proxy. Try an attack payload and watch the dashboard log the kill in real time.

See an attack die in 40 milliseconds.

The fastest way to understand Kysira is to watch it work.