Introducing ChainGuard

AI agents are beginning to enter the environments where continuity matters most.

 

They read tickets. They summarize emails. They review repositories. They process documents, operational notes, tool outputs, and web content. In time, they will support more workflows inside public safety, government, utilities, emergency communications, and other critical infrastructure environments.

 

That creates a new cybersecurity question.

 

Not just: what does the agent know?

 

But: who is the agent taking orders from?

 

OTM Cyber is announcing ChainGuard, a new CyberSystem capability designed to help mission-critical organizations keep AI agents aligned to authorized operator intent.

 

ChainGuard helps protect AI agents from turning untrusted content into unauthorized action.

 

What Makes an AI Agent Different

 

Most people first encounter AI as a chatbot: you ask a question, it gives an answer. That can be useful, but the interaction usually ends with text on a screen.

 

An AI agent goes further. It can be given a goal, gather information, choose steps, use tools, read files, summarize records, prepare changes, open tickets, query systems, or recommend actions across a workflow. In other words, it does not just respond. It helps operate.

 

That difference is what makes agents powerful, but it is also what makes them important to secure.

 

When AI is only answering a question, a bad response is usually the main concern. When an AI agent can take action, connect to tools, or influence operational workflows, organizations need stronger control over where its instructions come from.

 

The Core Problem

 

An AI agent may need to read a help-desk ticket, a vendor document, a repository file, or an email thread. That information helps it do its job. It may contain facts the agent needs to summarize, compare, or reason over.

 

But reading information is not the same as receiving authority.

 

A document should not be able to grant permissions. A ticket should not be able to redirect an agent to a new destination. A web page should not be able to change the agent’s mission. A tool description should not be able to invent approval. A file inside a repository should not be able to quietly tell the agent to disable safeguards or write somewhere outside the intended scope. However, these things are all happening. 

 

That is the boundary ChainGuard is built to protect.

 

Traditional cybersecurity tools were not designed to see this kind of risk.

 

Network monitoring can see traffic, endpoint tools can see process behavior, and data loss prevention can watch for certain forms of egress. Those controls still matter, but agentic systems introduce a different decision point.

 

The risk can materialize before the network event, before the file change, or before the external action.

 

It happens when the agent decides what it is about to do next.

 

In critical infrastructure, that is especially important. Operators need confidence that AI agents are supporting the mission, not being redirected by hidden instructions buried in the data they consume.

 

What ChainGuard Does

 

ChainGuard gives mission-critical organizations stronger control over agent-driven work by helping answer a simple operational question:

 

Was this action authorized by the operator, or did it originate from untrusted content?

 

The capability is designed to support four outcomes:

 

Keeps humans in command
AI agents can support the mission, but they should not invent authority from the information they read.

 

Protects operational continuity
ChainGuard helps reduce the risk of agents being redirected into unsafe, unauthorized, or out-of-scope actions.

 

Fits existing operations
ChainGuard is built into OTM Cyber’s CyberSystem platform, not positioned as another disconnected AI security tool.

 

Controls before consequences
The value is not just alerting after something happens. It is giving operators a chance to warn, require approval, or block high-risk actions before they move forward.

 

Built for High-Consequence Environments

As with all we do, ChainGuard is designed for organizations where the cost of a wrong action is not theoretical.

 

AI agents will continue to become more capable. They will read more. They will connect to more tools. They will support more workflows.

 

That makes the chain of authority ever more important.

 

Our view is straightforward: AI should assist human-led operations. It should not replace accountability, bypass approval, or turn untrusted content into orders.

 

ChainGuard brings that principle into the CyberSystem platform as a practical security control for the age of agentic operations.

 

AI agents can read the data. ChainGuard helps ensure they do not take orders from it.