Data443 Risk Mitigation, Inc.

Six months ago, the AI runtime control category didn't really exist. Today there are at least eight vendors, three open-source projects, two ongoing industry standards efforts, and a Q3 2026 AWS Marketplace category dedicated to the space. The post The 2026 State of AI Runtime Control appeared first on Data443.

When one AI agent calls another AI agent, you have a problem that didn't exist a year ago. The first agent generates a request based on its reasoning. The second agent acts on that request. Neither agent has any guarantee about what the other will actually do. The post Why Agent-to-Agent Proxies Need Deterministic Policy, Not LLM-Based Filters appeared first on Data443.

The OWASP Top 10 for LLM Applications (2025 edition) is the closest thing the AI security industry has to a consensus threat model. It enumerates the ten categories of weakness that show up most often when production LLM systems go wrong. The post OWASP Top 10 for LLM Applications, Mapped to Vaikora Runtime Controls appeared first on Data443.

The AI security industry has spent two years building safety layers that depend on the very thing they're trying to make safe. Most "AI guardrails" today work by feeding the AI's output back into anot The post Deterministic Policy vs LLM-Based Filters for AI Agents appeared first on Data443.

The realistic build path is two to three engineering quarters of focused work plus an ongoing detection-engineering tax forever. The buy path is a one-line application change. This guide is the cost-of-ownership comparison: what an in-house build actually has to cover, what an AI runtime control product covers out of the box, and the verdict line a buyer can quote. The post Build vs Buy AI Security: What Enterprises Actually Need appeared first on Data443.

This is a reference architecture for secure AI development: an LLM application talks to its existing SDK, which routes through an inline AI gateway (Vaikora), which forwards to one of 12 supported LLM providers, while audit and detection events flow into a SIEM and identity is centralized via SAML/SCIM. The post Secure AI Development: LLM Reference Architecture appeared first on Data443.

AI gateway, AI firewall, and AI proxy are three terms vendors use almost interchangeably for products in the AI security space — but they emphasize different jobs. An AI gateway is a routing and integration layer for LLM traffic; an AI firewall is a deny / block control plane for prompts and responses; an AI proxy is the inline transport that carries either of those jobs. The post AI Gateway vs AI Firewall vs AI Proxy: Category Definitions appeared first on Data443.

Can You Enforce AI Security in Real Time Without Breaking Latency? Yes — Vaikora adds about 8 ms at the median and stays under 50 ms at P99, which is well under 1% of a typical LLM round-trip time. This guide breaks down where the 8 ms goes, shows the latency histogram in text, explains the methodology behind the measurements, and addresses the three latency objections platform engineers actually raise. The post AI Security Latency: Real-Time Enforcement Explained appeared first on Data443.

This guide walks through how the three redaction modes work, shows a before / after redacted-then-restored payload, presents the architecture diagram for the egress block, and explains the metadata-only audit pattern that keeps your audit log out of HIPAA / GDPR / PCI scope. The post How to Block PII in LLM Traffic Before It Leaves Your Environment appeared first on Data443.

You can put an OpenAI-compatible gateway in front of an existing application by changing one line. No SDK swap, no client rewrite, no application redeploy beyond the config change. This guide shows how Vaikora's drop-in proxy applies the same security policy across 12 LLM providers with provider fallback routing. The post OpenAI Proxy Integration Without Rewriting Your App appeared first on Data443.