AI and GenAI Security: A Complete Guide for 2026
A complete guide to AI and GenAI security in 2026, covering the threat landscape, the OWASP Top 10 for LLMs and defense-in-depth controls.
Kuldeep Paul
LLM API Rate Limiting with Virtual Keys and Budgets
TL;DR
* LLM API rate limiting caps how many requests and tokens a consumer can send in a time window, while budgets cap how much money that consumer can spend; you need both to prevent 429 errors and runaway cost.
* In Bifrost, the open-source AI gateway by Maxim AI,
LLM Monitoring: Metrics, Audit Logs, and Controls
TL;DR
* LLM monitoring is the continuous collection of cost, latency, token, and error-rate signals for every model call, so engineering and compliance teams can see what happened and who did it.
* The core metrics to track are cost per request, latency (including time to first token), token consumption,
Top 5 Tools for LLM Cost and Usage Monitoring
Bifrost, LiteLLM, Langfuse, Datadog LLM Observability and Weights & Biases Weave compared on cost attribution, budget enforcement and deployment.
What Is an AI Gateway? A Complete Guide for Production Teams
A complete guide to AI gateways for production teams, covering how they differ from API gateways and the six core capabilities they provide.
Enterprise AI Security: The Controls That Apply to LLM Traffic
TL;DR
* Enterprise AI security is the set of controls that govern how an organization's applications, users, and agents send data to and receive data from language models.
* LLM traffic is a distinct security surface: prompts can carry sensitive data out, responses can carry it back, and agents
How to Implement AI Guardrails at the Gateway Layer
TL;DR
* AI guardrails are policy checks that validate model inputs and outputs in real time, blocking or redacting prompt injection, PII leakage, credential exposure, and unsafe content before it reaches a model or a user.
* Implementing guardrails at the gateway layer applies one policy set to every model and