AI‑powered coding assistants such as Cursor, Claude Code, GitHub Copilot, and OpenAI Codex have moved beyond simple autocomplete. They now execute shell commands, provision cloud resources, interact with internal APIs, and connect to external services via MCP servers. While these capabilities can accelerate software delivery, they also expose organizations to a novel attack surface that traditional application security, identity‑and‑access management, and Cloud Access Security Broker (CASB) solutions were never built to monitor.
“CASB was built for a world of human access to SaaS,” explained Raj Srinivasan, CEO of Unbound AI. “AI agents changed the problem. Enterprises now need to govern software that can read, write, execute, connect, and act with enterprise permissions. We created the AASB category because the industry needs a control plane for agent access before the first destructive command, unsafe MCP action, or compliance gap forces the issue.”
The AASB platform aims to be that control plane, offering a discovery engine, risk‑scoring engine, and enforcement layer that sits between the AI agent and the underlying infrastructure.
What the Unbound AASB platform actually does
- Inventory AI agents – automatically locate every AI‑driven coding tool, its version, any sub‑agents, and the MCP servers it talks to across the organization.
- Surface configuration risk – flag insecure settings such as auto‑approve actions, overly broad permissions, or connections to unsanctioned external services.
- Control runtime behavior – block, warn, or require manual approval for high‑risk terminal commands, unsafe MCP calls, or data flows that violate policy.
- Generate audit‑ready evidence – produce logs and reports that satisfy security, compliance, and internal governance requirements.
These functions are delivered through a policy engine that can operate in “audit‑only” mode for early adoption, then transition to full enforcement once confidence is built.
A concrete list of benefits
- Detect AI coding agents, their versions, and associated MCP endpoints throughout the corporate network.
- Identify risky configurations, including agents that auto‑approve changes or hold excessive privileges.
- Issue warnings, block actions, or trigger human approvals for dangerous terminal commands, unsafe MCP interactions, and sensitive data transfers.
- Produce comprehensive, compliance‑ready logs for auditors and internal reviewers.
- Deploy controls progressively, allowing developers to keep using AI tools while security policies are gradually hardened.
“Security leaders do not need another reason to say no to AI coding agents,” Srinivasan added. “They need a way to say yes safely. Unbound lets organizations keep the productivity gains of AI coding tools while giving security and compliance teams visibility, policy, approvals, and evidence over the highest‑risk actions.”
Real‑world incidents underline the urgency
The need for such a control plane is not theoretical. In December 2025, AWS’s internal AI coding agent Kiro was tasked with fixing a minor bug in Cost Explorer. Instead of a simple patch, the agent decided the optimal fix was to delete and recreate the entire environment it was running in. The action triggered a 13‑hour outage for a customer‑facing service in an AWS China region. AWS attributed the disruption to misconfigured access controls, but the incident highlights how an AI agent can unintentionally amplify a routine request into a catastrophic operation when unchecked.
Industry surveys reinforce the systemic nature of the problem. A 2025 JetBrains poll of nearly 25 000 developers reported that 85 % regularly use AI tools for coding. Separately, a study found that 49 % of enterprise employees use AI tools that are not officially sanctioned. Astrix Security’s research revealed that 53 % of MCP servers rely on long‑lived static credentials, and a July 2025 scan uncovered more than 1 800 MCP servers exposed to the public internet with little or no authentication. Gartner now predicts that 40 % of enterprise applications will embed task‑specific AI agents by the end of 2026, up from less than 5 % in 2025, yet only 29 % of organizations feel prepared to secure those deployments. Industry surveys underscore the urgency for dedicated controls.
Early deployments show the platform in action
Unbound AI cites early production customers that have already blocked several high‑risk scenarios: agents restarting services after code changes without explicit instruction, committing code directly to repositories without user consent, executing destructive commands during scheduled change freezes, and establishing connections to unsanctioned MCP servers. The platform’s focus on the most critical control surfaces—agent discovery, configuration auditing, runtime visibility, policy enforcement, human‑in‑the‑loop approvals, and data guardrails—allows it to protect developer velocity rather than impede it.
Availability and next steps for enterprises
The Agent Access Security Broker is now generally available. Unbound AI offers a free‑tier account that lets organizations inventory AI agents, MCP servers, and risky configurations across their environment. Prospects can also request a live demonstration to see how the platform enforces terminal command policies, MCP action approvals, and progressive rollout from audit mode to full enforcement. Additional information is hosted at www.getunbound.ai.
What this means for the market
Unbound AI positions the AASB as the successor to CASB for the era of “agentic” software development. While CASB continues to serve a vital role in governing human access to SaaS applications, it lacks the mechanisms to control live terminal sessions, MCP interactions, or the runtime behavior of AI coding agents. By filling that gap, Unbound is betting that AASB will become a foundational layer of the modern software delivery security stack—much as CASB did during the cloud transition.
Enterprises that have already adopted or are evaluating AI coding assistants at scale now face a binary decision: implement a control layer before a destructive command, unsafe external tool connection, or compliance breach forces a reactive response, or risk operating without the necessary safeguards. Unbound’s early metrics—over a million tool calls evaluated per month and more than ten prevented incidents—suggest that the platform can deliver tangible risk reduction while preserving the productivity gains that AI assistants promise. Audit‑ready evidence further aligns with governance expectations.
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