CCPA

You stop PII from leaking between AI agents by placing a deterministic policy enforcement layer (with probabilistic risk scoring) inline on the A2A task hand-off, so every task message is inspected, classified, and either redacted or blocked before it reaches the Remote-Agent. Concretely, A2A traffic flows through Vaikora as a transparent egress

A2A defines a Task-Based Actor Model — a User sends work to a Client-Agent, which then delegates to one or more Remote-Agents — and a discovery mechanism based on agent cards published at /.well-known/agent.json. This guide shows how Vaikora applies inline policy enforcement on every A2A task message before it crosses an organizational boundary.

MCP is the answer to a simple question: how does an LLM call a tool, read a database, or open a file in a way that any compliant AI application can consume? This guide explains the architecture, the transport layer, and three concrete use cases — and shows where a runtime control layer like Vaikora fits.

This guide explains exactly why "log everything" conflicts with SOC 2, HIPAA, GDPR, PCI DSS, ISO 27001, NIST CSF, and CCPA, and presents the metadata-only logging pattern (content: false) plus a SHA-256 hash chain that satisfies the same evidence requirements without storing prompts.

AI gateway, DLP, and WAF solve different problems and do not substitute for each other. A WAF (Web Application Firewall) inspects HTTP traffic for known web-attack patterns. A DLP (Data Loss Prevention) tool detects sensitive data in files, email, and endpoint flows.

MCP is the answer to a simple question: how does an LLM call a tool, read a database, or open a file in a way that any compliant AI application can consume? This guide explains the architecture, the transport layer, and three concrete use cases — and shows where a runtime control layer like Vaikora fits.

This is a working crosswalk that maps NIST AI RMF 1.0 functions (Govern, Map, Measure, Manage) and ISO/IEC 42001:2023 controls to concrete Vaikora capabilities — policy engine, 7-factor risk scoring, SHA-256 hash-chained audit, content-free logging, and automated reporting. The blog version below highlights the highest-cited rows from each function and explains the design choices behind the mapping.

I agent protocols are the standard ways autonomous AI systems discover services, exchange messages, and call tools across organizations. The four protocols that matter today are MCP (Model Context Protocol), A2A (Agent-to-Agent), ACP (Agent Communication Protocol), and ANP (Agent Network Protocol).

This article explains how AI agent activity can be surfaced in AWS Security Hub using Vaikora. Vaikora’s capabilities include providing deep visibility into AI agent operations and generating comprehensive audit logs for real-time monitoring, compliance tracking, and threat analysis.