Secure every agent. Control every action.
Research-backed security for every AI agent in your company.
AI agents now sign in, read, write, pay and deploy across your company.
ANTWALL is the security platform that decides what each one may do, and stops everything else before it runs.
AI agents run everywhere.
Secure them from one place.
Agents are built by different people with different tools in three different environments. ANTWALL puts every one of them behind the same wall.
Local agents
Developers run Claude Code, Cursor and Codex on their laptops, often connected to MCP servers that can access production code, internal APIs and customer data. These connections may exist without security approval or visibility into what the agents can access and do.
ANTWALL for coding agents →Cloud agents
Engineering teams build agents using Amazon Bedrock, Azure AI Foundry, LangChain, LangGraph and Agno. These agents can connect tools and interact with production systems using real credentials—creating significant risk if their access and actions are not properly controlled.
ANTWALL for cloud agents →SaaS agents
Sales, HR and finance teams build agents in platforms such as Copilot Studio and Agentforce—often without security’s visibility. As adoption grows, organizations can discover far more agents than they expected.
ExpandingWhy ANTWALL
Secure every agent, wherever it runs
From employee devices to cloud infrastructure and SaaS platforms, bring every AI agent under one roof. No blind spots across your AI landscape.
Keep sensitive systems within reach—and out of harm
Give AI agents the access they need, while keeping sensitive data, systems, and business operations protected.
Bring every AI risk into one view
Discover agents, understand their access, and manage security risks across your organization from one central control plane.
Secure AI without slowing your teams down
Work with the tools, gateways, and infrastructure you already use. Adopt AI with confidence, without re-architecting your environment.
Research-backed. Built for trust.
AI security demands more than keeping up. It demands understanding what comes next.
The Antz research team investigates how AI agents are compromised—in real-world environments and in our own labs. That research informs how ANTWALL protects your agents, helping you move forward with confidence.
From prompt injection and poisoned tools to compromised packages, exposed credentials, and agents acting beyond their intended scope, our research explores the threats that matter to your business.
We turn validated research into detections, scans, and policy controls—so the knowledge we gain helps protect ANTWALL customers. Our work is mapped to established frameworks, including the EU AI Act, NIST AI RMF, and ISO/IEC 42001.
Our Agent Simulator and attack simulations put agents through realistic attack scenarios, helping uncover weaknesses before deployment. Because confidence comes from knowing your defenses have been tested.
Four products.
One view of every AI agent.
Discover every agent. Define what it can do. Protect it while it runs. Simulate attacks before it goes live.
Each ANTWALL product strengthens the others—giving your organization a shared view of its AI agents and a consistent way to secure them.
Agent Discovery
Know what’s running across your local devices, cloud environments and code. Discover agents, MCP servers, skills and models, with ownership and risk context. Identify agents that appear without registration.
Learn more →Access Control
Define what each agent is allowed to access and do—from tools and data to models and spend. Turn your policies into versioned rules that can be monitored, notified on, or enforced.
Learn more →Runtime Defense
Keep agent actions within approved boundaries as they happen. Block unauthorized actions, protect sensitive data, and stop an agent when needed.
Learn more →Supply Chain & Red Teaming
Check the components your agents rely on. Scan MCP servers, models and packages for tampering, and test agents with attack simulations before they reach production.
Learn more →What teams secure with ANTWALL
Coding agent security
Secure Claude Code, Cursor and Codex across developer laptops. Review changes before they reach main, protect secrets from prompts, and check new tools before use—without slowing developers down.
Agent runtime security
Keep every agent within its approved boundaries. Access control defines what agents can do, while runtime security helps ensure they stay within those limits.
MCP security
Know which MCP servers your agents use. Scan them for risks, detect poisoned tool descriptions and unexpected changes, and isolate servers that no longer meet your security standards.
Agent identity
Know which identity each agent uses, what it is authorized to access, and whether its actions align with the user’s intent. Manage agent identities throughout their lifecycle, including when they are retired.
AI asset discovery
Discover AI agents across your organization—including those security teams may not know about. Identify new agents, understand their ownership, and bring them into view.
AI supply chain security
Understand the risk in the models, MCP servers, tools and packages your agents depend on. Identify unsafe components before they become part of your AI environment.
Cost control
Understand AI spend by agent, track usage against contracted rates, and set budgets that help prevent unexpected costs. Give security and finance a shared view of AI spending.
Compliance and audit
Give your board and auditors evidence of how AI is governed: agent inventory, framework mappings, security tests, and traceable records of agent activity.
Leadership views
Give the CEO, CFO, CIO, CISO and COO a clear view of the AI risks and decisions that matter to them—grounded in the same trusted record.
AI security, through every leader’s lens
Security owns the controls. Every leader has a different question about AI agents.
Choose a role to see what matters to that leader—and how ANTWALL helps answer it.
CEO, CFO, CIO and CISO views are available today, with some capabilities still evolving. The COO view is planned.
Example dashboard. Names and figures are illustrative.
Give every agent a role, an owner, and clear limits
Every person on a team has a role, a manager, boundaries, a budget, and a record of their work. ANTWALL gives AI agents the same structure—so teams can put them to work with greater confidence.
| A person in a role has | An agent on ANTWALL has |
|---|---|
| A job description | Clear limits on the tools, data, and models it can use |
| A manager | A named owner accountable for its actions |
| Approval limits | Human approval for sensitive actions |
| A budget | A spending limit and approved models |
| A performance record | A record of actions that can be reviewed and replayed |
Roles we set up most often
- Support and sales assistantSees only the customer it is helping. Bulk exports and emails to outside addresses are blocked.
- Finance and HR clerkPrepares the work for a person to approve. Unusual amounts and offer letters require sign-off, and costs are assigned to the right team.
- Code reviewerWorks alongside a developer on their laptop. A person reviews its code before it reaches production, secrets stay hidden, and new tools are checked before use.