Explore how AI is reshaping the landscape of API security. From intelligent threat detection to automated policy enforcement, stay ahead with insights, strategies, and innovations at the intersection of artificial intelligence and secure API management.
Claude Code is Anthropic's agentic coding and agent harness tool. Unlike traditional code-completion assistants that suggest the next line in an editor, Claude Code operates as an autonomous agent that reads entire codebases, edits files across multiple directories, runs terminal commands, executes…
Your dashboards scream 99.9% uptime. Latency stays well under 200ms. Error rates dwell at zero. These operational metrics look perfectly all right. Yet customer complaints continue to hit all-time highs. Your AI assistant prescribes incorrect medical dosages. Your cloud bill tripled overnight.…
In today's digital landscape, APIs are the backbone of modern applications, and AI is the engine of innovation. As organizations increasingly rely on microservices and AI-powered features, the API gateway has become the critical control point for managing traffic. But as LLM/GenAI and MCP requests…
MCP servers expose all tools by default. There are two problems with this: security (agents get capabilities they shouldn't have) and performance (too many tools degrade LLM tool selection). The solution? Put a gateway between agents and MCP servers that filters tools based on who's asking. Default…
Let's be honest about what's happening inside most enterprises right now. Development teams are under intense pressure to ship AI features. The mandate from leadership is clear: move fast. And so they do. They spin up LLM connections, integrate third-party AI tools, and route data to models without…
The evolution of AI agents and autonomous systems has created new challenges for enterprise organizations. While securing API endpoints is well-understood, controlling access to individual AI agent tools presents a unique authorization problem. Today, we're excited to announce a powerful solution…
It's natural to consider the necessity of guardrails for your sophisticated AI implementations. The truth is, much like any powerful technology, AI requires a set of protective measures to ensure its reliability and integrity. These guardrails aren't just a good idea; they are fundamental for…
The OWASP Top 10 for LLM Applications 2025 represents a significant evolution in AI security guidance, reflecting the rapid maturation of enterprise AI deployments over the past year. The key updates include expanded focus on agentic AI systems with "excessive autonomy" risks, new attention to…
The adoption of LLMs is accelerating faster than most technological trends we’ve witnessed before. According to recent Gartner projections, by 2026, over 80% of enterprises will have used or experimented with LLMs , a dramatic increase from less than 5% in 2022. Their integration spans across…
LLMs operate as highly capable, non-deterministic pattern matchers. But they come with two significant privacy challenges: If you pass raw user input, internal logs, or structured data directly into an LLM without safeguards, you’re risking the exposure of names, emails, credit cards, health info,…
More than 80% of developers and business leaders say AI investments have already created the opportunity for new products or services, according to Kong’s 2024 API Impact Report . Clearly, AI has proven its value and place in the enterprise, but with new innovations come new potential…
It’s no secret that artificial intelligence (AI) is revolutionizing the way companies operate with its ability to sift through mountains of data and make accurate predictions at record speed. But with great power comes great responsibility. As AI systems are more regularly incorporated into…
Secure your AI infrastructure with prompt guards, PII sanitization, and centralized governance. Control LLM costs with token-based rate limiting and semantic routing across providers.