Cencurity is a security gateway that proxies LLM/agent traffic and detects, masks, and blocks sensitive data and risky code patterns in requests and responses. It provides real-time protection while recording everything as audit logs.
Cencurity is an LLM security gateway designed to protect enterprise AI agents from data leakage and unauthorized access. It sits as a proxy between your LLM calls and the models, inspecting every request and response for sensitive data and risky code patterns. This tool is built for development teams that rely on AI coding assistants like Cursor or Copilot, as well as custom agent workflows. Its core value lies in providing real-time protection without requiring any changes to existing code—just plug it in and instantly gain visibility and control over all agent traffic.
The primary problem Cencurity solves is the inherent risk of prompt leakage and sensitive data exposure when using LLMs in production. Developers often inadvertently send secrets, PII, or proprietary code to third-party models, while agents can generate harmful or confidential output. This creates compliance nightmares, especially under regulations like SOC2, HIPAA, or GDPR. Without a gateway, teams have no centralized way to monitor what goes in and out of their LLM calls, making it nearly impossible to enforce policies consistently across different models and IDEs. Cencurity addresses this by becoming the single control point for all agent communication.
One of the standout features is the Centralized Security Dashboard, which offers a single pane of glass for every agent call. This dashboard displays real-time metrics such as request count, response latency, policy hits, redactions, and blocks. You can see exactly when a secret was detected or a risky output was stopped, along with the full context of the interaction. This eliminates the need to manually sift through scattered logs or rely on incomplete monitoring. By providing instant visibility, it allows security teams to spot anomalies and refine policies quickly, reducing the window of exposure.
Real-time protection is another critical feature that automatically detects and blocks secrets, PII, and risky output before they reach users or models. Cencurity uses pattern-based and machine-learning detection to identify credit card numbers, API keys, passwords, and other sensitive data. When a leak is detected, the gateway can either mask the sensitive content or block the entire request/response, depending on your policy. This edge-based enforcement ensures that data never leaves your controlled environment without meeting your security rules, giving you confidence even when interacting with external AI providers.
Publisher
A
admin
Launch Date2026-02-18
Platformweb
Pricingfree