Why Impart | Runtime AI Security & Inline Protection
Built for Attacks That Don't Exist Yet
Signature-based defenses fail the moment an attacker changes encoding, splits a payload across requests, or chains tool calls in a new order.
Impart inspects every request inline, normalizes payloads before evaluation, and correlates behavior across sessions. Novel attacks get caught the first time they show up.
Start protecting; stop posturing.
If it’s not inline, it’s not enforcement.
Virtual patches in minutes
Other solutions respond to zero days and CVEs and other disclosures with virtual patches that take days to weeks. With Impart, security teams can design, develop, test, and deploy a virtual patch within minutes.
Impart stops attacks inline
Unlike most solutions, Impart runs inline in production. This allows Impart to evaluate and stop attacks inline while they’re happening instead of after they’re finished.
Protections as code
Most runtime solutions are based on regex or rego rules, which aren’t flexible enough to detect AI attacks. Impart’s code based WebAssembly rules run at machine speed and enable complex detection logic that can be audited and trusted.
Unified runtime protection
Avoid point solutions that fragment your attack surface and complicate daily operations with a single platform for every runtime attack surface.
Every other tool solves part of the problem.
Other tools fragment your attack surface with protections at different layers. Impar is a universal protection layer with multiple deployment options that covers all runtime layers.
| Tier | Traffic Type | What it sees | What it can stop |
|---|---|---|---|
| CDN | HTTP Requests | Basic injections and volumetric abuse. | Basic injections and volumetric abuse. |
| Ingress | API Calls | IDOR and auth bypass | IDOR and auth bypass |
| App | Application Logs and calls | Nothing | Nothing |
| Every Layer | HTTP, API, AI Tokens, tool calls | The complete attack - including multi-layer sequences | The complete attack - including multi-layer sequences |
Running in production. Enforcing in real time.
"The Impart team is really innovating in the API security space. Really smart use of LLMs in their product that help security teams especially with firewall rules, which are a huge problem."
Travis McPeak, CEO
"API security is now a critical aspect of every application security program. Every CISO needs to have an integrated solution that can comprehensively protect their APIs across their entire lifecycle."
Zane Lackey, Co-Founder
"Great product. Great team. Makes application security so much easier and installs in minutes across both legacy and modern tech stacks."
Steve Hopkins, CTO
"Impart has everything you'd want in an API security platform, and there's little reason to look elsewhere - they provide discovery, testing, and protection—all in a single platform. Impart’s combination of accurate discovery with anomaly detection made them stand out in a crowded space filled with other great tools."
James Berthoty, CEO
FAQ
What is the difference between inline and out-of-band security?
Inline security tools sit directly in the path of live traffic and enforce before the request completes. Out-of-band tools receive a copy of traffic, analyze it, and surface findings after the request has already been processed. A runtime protection platform is inline by architecture. The enforcement decision happens at the origin, in milliseconds, without requiring a human in the loop.
Why do AI-native attacks require AI-native defenses?
AI agents probe hundreds of endpoints in parallel, chain valid-looking requests into multi-step exploits, and complete attacks faster than a human analyst can reach the alert. Static rules and periodic reviews can't keep pace with traffic that adapts in real time. AI-native defenses run inline at the application layer, evaluate the full session instead of a single request, and update enforcement continuously from observed behavior. The defenses operate on the same timescale as the attacks, on the same data plane that handled them.
What is runtime enforcement?
Runtime enforcement is the ability to detect and block a threat at the moment the request is made, inline in the path of live traffic, before it reaches your application. It is distinct from detection-only tools that observe traffic and alert after the fact, and from shift-left tools that look for vulnerabilities before deployment.
Does Impart cover AI agent traffic?
Yes. Impart's LLM and AI Agent Firewall deploys inline in front of your LLM endpoints and AI agent workflows. It builds behavioral profiles for every agent interacting with your infrastructure, traces multi-step agent workflows across sessions and surfaces, and enforces against deviation before the request reaches your model. It covers prompt injection, exfiltration, agent abuse, and sensitive data leakage inline, before the response leaves your environment.