Comprehensive API Security Solution

Stop confidential GenAI leakage by tightening day-one controls (SSO, provisioning, retention), enforcing real-time prompt and output redaction at the boundary with GenAI Protector Plus, locking down RAG sources and integrations, routing confidential collaboration into CoSpaceGPT, and using WebOrion® Monitor to catch unauthorised public-site changes quickly, all within a practical 90-day rollout.

ChatGPT said:

This article explains how to secure employee use of ChatGPT in a corporate environment by making safe behaviour the default through identity, retention, guardrails, and audit-ready governance. It lays out a practical baseline checklist (SSO and MFA, SCIM lifecycle controls, retention and export rules, connector restrictions, SIEM logging, change control, and lightweight training), then shows how to route sensitive or collaborative work into CoSpaceGPT so model choice, sharing, retention, and audit trails stay governed in one place. It also clarifies where GenAI Protector Plus fits to protect the LLM traffic and GenAI apps you control, and how WebOrion® Monitor helps protect brand trust by detecting public-site defacement or unintended changes, supported by a structured 90-day rollout and a quarterly review rhythm.

This article explains why enterprises should secure GenAI before scaling, covering LLM-specific risks like prompt injection, insecure output handling, data poisoning, model denial of service, and supply chain exposure, alongside classic web and app threats. It shows how layered protection works in practice with a GenAI firewall for prompts and responses, a secure workspace for governed employee use, and website integrity monitoring to protect public-facing sites. You will also get a clear evaluation framework, a rollout sequence aligned to NIST AI RMF-style governance, a worked ROI and TCO example, and a clearly labelled hypothetical case study showing how the layers reduce shadow use and create audit-ready evidence.