Control How Agents Behave in Production
AI agents make decisions on your infrastructure and inside your application. Impart watches what they do at runtime — identifies adaptive attacks, blocks deceptive behavior, and lets you patch zero-days in minutes instead of sprints.
Agent protection at runtime that enforces, not just observes.
Agents authenticate like users, call APIs like services, and improvise like nothing your stack was designed to handle. The behavior is the attack surface.
Evaluate intent at runtime to control what your agents actually do, not just what they're allowed to.
Inspect
Every agent request in full context. Identity, role, prior actions, the tools the agent has access to, and the sequence of calls leading up to this one.
Decide
What the request is actually trying to accomplish. Privilege escalation, data exfiltration, unauthorized tool use, executing on injected instructions. Intent gets classified, not just the request shape.
Enforce
Malicious behavior stops before the action lands. The decision is made inline, in milliseconds. No second-guessing required.
Impart detects adaptive attacks.
Agentic attacks rarely show up as a single bad request. They adapt, probe, and escalate.
Agent protection runs on the same ingress-layer enforcement engine that inspects your full attack surface. Impart reads the whole arc using a four-phase runtime defense:
every agent making requests through the enforcement layer, whether sanctioned or not, to establish full visibility across your attack surface.
malicious agent attacks by evaluating the full action sequence, instead of just single anomalous requests, to spot patterns like privilege escalation or data exfiltration.
against abuse and exfiltration by classifying the agent's intent and blocking or modifying malicious behavior in milliseconds, before the action executes.
and enforce agent behavior using policy-as-code rules, which are written against live traffic and continuously refined to guide safer operation and stop unauthorized tool use.
One runtime engine for all your agents.
It sits between the agent and your systems, enforcing security before any action executes.
Stateful
Full behavioral history maintained across sessions, identities, and tool chains lets Impart make high quality decisions
Unified
Whatever path the agent takes through your stack, the runtime knows who it is.
What a blocked attack looks like in Impart.
An adaptive attack unfolds in phases. Impart sees it as one sequence and stops it in real time.
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."
"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."
"Great product. Great team. Makes application security so much easier and installs in minutes across both legacy and modern tech stacks."
"When we think about examples of customer love in cybersecurity, some of the most loved companies in security includes Impart Security."
"Hands down one of the best API security products on the market and the most compelling solution for serverless. Integrates with no architecture impact, and great team to work with."
"Examples like Thinkst Canary, Duo Security, Tines, Chainguard, Material, Impart, Panther, Anvilogic, and LimaCharlie show that it is possible to be pragmatic (and successful!) as a business and loved at the same time."
"The team is building something truly top notch in WAF, API Security, and LLM Protection."
All
runtime decisions
"Nothing drives me more than getting to work with highly motivated and super intelligent people. I am happy to be here and looking forward to the long road ahead!"
"Impart is my pick to lead the next wave in application security tooling by leveraging usage (and other) context for decisions and making it visible to both security teams and developers. This unifies two themes in security today: Shift Left and Protect Right."
"I have a sophisticated app sec team, and they regularly complain about how limiting form-based rule builders are. They will be pumped to hear about the ability to build more sophisticated rules via code. Same with dynamic runtime lists. The LLM-powered rule explainer is also pretty cool. It is gen AI that is actually useful, as opposed to framing in another gen AI chatbot and calling it a day."
"Impart offered Crossbeam a single, unified solution for Web application, API security, and LLM protection.The team has provided exceptional support and is a true partner for us."
"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."
"Impart saved the day during a security incident when our WAF and our SIEM failed to detect and mitigate an ongoing API attack. Impart effortlessly detected and stopped the attack for us, with great support from the team."
"We've dramatically reduced our cycle time for adapting to new threats—we can now match the velocity of attackers instead of always playing catch-up. Impart has made our entire security operation more surgical and effective."
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100%
FAQ
Yes. MCP traffic, function calls, and tool invocations are exactly where Impart enforces. Every call gets evaluated for whether it fits the agent's role and the trajectory of the session. Tool poisoning, unauthorized tool use, and chained tool calls that only become attacks in aggregate are all in scope.
Impart sees every agent making requests through the enforcement layer, sanctioned or not. If an agent is calling your APIs, hitting your data, or invoking tools through your infrastructure, it shows up in the runtime. Visibility is the first thing the system gives you, before any policy is written.
Intent gets classified against the agent's role, history, and the full action sequence. A request that looks anomalous in isolation often makes sense in context, and AI Analysis reads the context. Most teams run in observe mode first, watch the decisions Impart would make against real traffic, then turn on enforcement when they're ready. False positives are the failure mode the system is tuned against.
Posture tools tell you what your agents are configured to do. Governance tools tell you what they're allowed to do. Impart enforces what they actually do, in the moment they try to do it. Posture and governance run in advance. Impart runs at execution. Most production teams need both layers.