Analysis
Axora: Axora functions as GoPlus’s security gateway for AI applications and autonomous agents, handling model access, routing, policy enforcement, and runtime controls. It is central to the H1 2026 developments by governing agent information flows and pre-execution actions. The product combines visibility, validation, and governance layers for agent workflows. DeepScan: DeepScan is GoPlus’s AI-powered platform for smart-contract vulnerability discovery, auditing, and continuous monitoring. It is directly relevant to the reported strategy as it addresses risks in contracts that autonomous agents may interact with, moving beyond one-time audits to ongoing assessment. The tool integrates with GoPlus’s broader on-chain intelligence network. SafuSkill: SafuSkill is GoPlus’s platform for AI software supply-chain security, focusing on discovery, assessment, and trusted distribution of agent skills and code. It supports the news narrative by mitigating risks from third-party components that agents rely on before execution. The service aggregates skills and enables secure tokenization for broader ecosystem use. GoPlus Security: GoPlus Security provides Web3 risk intelligence, smart-contract security tools, and token protection services across dozens of blockchains. In this news, the company is expanding its focus from user and transaction protection to securing autonomous AI agent execution through a layered architecture. Its products are positioned to meet rising demand for machine-consumed security services. GoPlus Intelligence: GoPlus Intelligence delivers real-time on-chain risk data on tokens, addresses, and transactions to wallets, applications, and other systems. In the current context, it supplies additional risk context that complements agent-level security when autonomous systems interact with financial infrastructure. The service now includes programmatic access for machine-driven queries. AI Agent Security API: The AI Agent Security API extends GoPlus Intelligence to allow autonomous agents to consume security checks programmatically within their own workflows. It is highlighted in the news as a bridge between established Web3 risk intelligence and the new execution-security model. The API supports usage-based access for counterparty, asset, and transaction risk assessment. Market Shift: Security demand is moving from periodic, human-triggered protection toward continuously consumed, machine-native services embedded in agent workflows. Agent Adoption: Autonomous AI agents are gaining greater access to data, tools, and financial infrastructure, increasing the need for security controls at the point of execution. Security Landscape: AI is lowering the cost and expertise required to discover vulnerabilities and scale established attack techniques across Web3.