Operant sits outside your models, agents and MCP servers and judges every action, tool call and data flow in real time. Allow, block or redact before damage is done.
Operant Semantic Firewall understands the intent behind every agent action and enforces an allow, block, or redact decision inline, in real time—stopping harm before it happens, whether caused by an attacker or an agent exceeding its scope.
Get real-time protection for every AI-enabled endpoint. Discover Shadow AI tools, coding agents, and MCP clients on employee devices. Monitor agent loops and block prompt injection, data exfiltration, and malicious shell execution directly on the device. Endpoint Protector enforces AI trust boundaries where they break first: on the laptop.
Get real-time protection for your entire agentic AI ecosystem. Discover managed and unmanaged agents across cloud, SaaS, and development tools. Monitor behavior, detect threats, and block critical attacks from zero-click exploits to data exfiltration and rogue agents. Agent Protector enforces trust boundaries with active defense for the agentic AI era.
Real-time visibility and controls for every MCP server, client, tools, and connections in your environment, with MCP registries, white list/black lists, and NHI access controls, so your entire team can develop AI and Agents, safer and faster.
You can’t secure AI without securing APIs. Protect your entire API ecosystem in real time with 3D defense, from third party endpoints and internal connections to ghost and zombie APIs. Discover your live API blueprint, block unauthorized access and OWASP Top 10 API attacks, without the cost or overhead of VPC mirroring.
Real-time visibility and controls for every MCP server, client, tools, and connections in your environment, with MCP registries, white list/black lists, and NHI access controls, so your entire team can develop AI and Agents, safer and faster.















Since September, agents taking unauthorized real-world actions went from theory to headlines
Every one of these behaviors will appear in enterprise deployments.
Agents went off-script, targeting government sites.
Agent acts beyond task scope, reaching external systems.
Network and API requests adjudicated against policy in ~100ms, blocked before execution.
Gemini misread scope, accessed real companies.
The agent's own belief about scope is wrong.
Credential use is judged independently of what the agent believes; out-of-policy access never executes.
Reported IPO filing warns models can resist shutdown and evade safety checks.
Agents evade controls that live inside their context.
Control layer sits outside the agent, judges actions rather than reasoning, so it can't be talked around.
Two sides of the same problem: the AI your people use every day, and the AI agents you ship into products and systems.
Coding agents, CLIs and chat tools act with your employees' access, on every device.
The agents you ship take real actions for customers and systems, often with no human in the loop.
One control layer that sits outside your AI and judges what it does, not what it says.
Map every model, agent, MCP server, API and AI tool across devices, clusters and clouds, including the shadow AI nobody approved.
Watch prompts, tool calls and data flows at runtime. Flag prompt injection, data exfiltration and agents acting outside their scope.
Allow, block or redact inline, in real time. Policies are enforced outside the agent, so a compromised model can't talk its way past them.
A breakthrough in performance and precision for industry-leading, real-time defense.

“Securing AI Agents is a critical priority for AI-native companies because you can’t hand off that level of autonomy at scale to these systems without appropriate controls in place.”
“Operant's runtime enforcement gives companies the ability to secure their next-gen K8s initiatives without limiting their ability to scale. The combination of innovation and simplicity that Operant's approach brings is rare and powerful.”
“Secure AI applications like Cohere’s North demand rigorous testing across complex components. Operant’s Woodpecker simplifies this with open-source red teaming, enabling early vulnerability detection and encouraging secure AI adoption.”

“Operant's in-line auto-redaction enables teams to develop AI faster with Kubernetes-native privacy controls that span all the way from infra to AI APIs, so that security, platform, and developers can all have what they need as they work together to build today's leading AI tech.”
“Operant’s real-time protection across the full agent toolchain, from MCP clients and endpoints to live, interactive agentic applications, lets technology leaders move fast without compromising customer privacy, making it a foundational control rather than an afterthought.”
“The Shadow Escape attack demonstrates the absolute criticality of securing MCP and agentic identities. Operant AI's ability to detect and block these types of attacks in real-time and redact critical data before it crosses unknown and unwanted boundaries is pivotal to operationalizing MCP in any environment.”
“The latest from Operant AI is what I'm excited about as far as where the AI security use case is going, and a great example of what's possible focusing on emerging runtime use cases.”
Pick the scenario that matches what's happening in your organization today. Every one runs on the same platform, so you can expand when you're ready.
Discover, detect, and block threats across agents, MCP, and APIs in real time, with no code changes.