Koreshield

Product Introduction

1. Definition: Koreshield is a runtime security and trust control platform specifically engineered for AI-powered support workflows. It operates as a security layer that intercepts and inspects data flows between the customer, the AI model, and backend systems in real-time.
2. Core Value Proposition: It exists to prevent data poisoning, prompt injection, and unauthorized tool execution in AI support agents. Koreshield's primary function is to establish a zero-trust boundary for AI interactions, ensuring that untrusted customer input, retrieved knowledge base documents, and proposed agent actions are validated before they can influence the AI's behavior or trigger application functions.

Main Features

1. Three-Point Trust Boundary Inspection: Koreshield performs discrete security checks at three critical junctures in an AI support workflow. First, it screens raw customer messages and attachments for malicious prompts or data leaks. Second, it analyzes context retrieved from databases, CRMs, or RAG systems to prevent poisoned documents from being trusted. Third, it evaluates the AI agent's proposed tool calls (like creating a ticket or issuing a refund) against security policy before execution.
2. Detect-Before-Enforce Posture: A key operational feature is its phased rollout capability. Teams can first deploy Koreshield in "detect mode," where it passively monitors and logs potential threats without blocking traffic. This allows for validation against real support cases, identification of false positives, and evidence gathering before switching to active "enforce mode" which blocks violating requests.
3. Evidence-Based Decision Logging: Every scan and decision made by Koreshield is recorded with a full audit trail. Each request (e.g., REQ_001) is tagged with a decision (detected, allowed), severity level, and the operational mode. This creates immutable evidence for security reviews, compliance audits, and fine-tuning of detection policies.

Problems Solved

1. Pain Point: AI support agents inherently trust all inputs—user queries, retrieved help articles, and internal notes—which can contain hidden instructions, malicious data, or policy violations that "jailbreak" the agent or cause harmful actions.
2. Target Audience: This product targets Security Engineers and DevOps teams managing AI customer support platforms, Product Managers responsible for AI agent safety and compliance, and Support Operations leaders needing to mitigate risks from AI automation in ticketing, live chat, and CRM integrations.
3. Use Cases: Essential for scenarios where AI handles sensitive customer data (PII, financial info), automates high-stakes actions (account changes, transactions), or operates on knowledge bases that could be tampered with. It is critical for preventing supply-chain attacks via poisoned RAG documents and stopping prompt injection attacks that manipulate agent behavior.

Unique Advantages

1. Differentiation: Unlike static API gateways or simple content filters, Koreshield is purpose-built for the dynamic, multi-stage data flow of AI support workflows. It does not replace the AI model or the authorization system but acts as a dedicated runtime guardrail. Competitors often focus on pre-deployment "red teaming," while Koreshield provides continuous runtime protection.
2. Key Innovation: Its core innovation is the conceptualization and technical implementation of the "trust handoff." It treats each stage—user input, context retrieval, and action proposal—as a separate trust boundary that must be independently validated, preventing a failure in one stage from compromising the entire chain. The "evidence-first" deployment model also reduces operational risk.

Frequently Asked Questions (FAQ)

1. How does Koreshield prevent prompt injection attacks? Koreshield analyzes customer input and retrieved context before they are sent to the AI model, using specialized detection algorithms to identify hidden instructions, malicious payloads, and attempts to manipulate the system prompt, thereby neutralizing the attack vector before the AI processes it.
2. Can Koreshield be integrated with any AI support platform? Yes, Koreshield is designed as an API-first security service. It can be integrated via a server-side call into the request flow of most AI support platforms, chatbots, or custom-built agents that use large language models (LLMs) for customer interaction and tool automation.
3. What is the difference between "detect mode" and "enforce mode"? Detect mode is a passive monitoring state where Koreshield scans traffic and logs threats without blocking requests, used for baselining and validation. Enforce mode is an active security state where requests that violate the configured policy are blocked or redirected to a fallback path, preventing the potentially harmful action.
4. Does Koreshield inspect images and file attachments? Currently, Koreshield's primary focus is on inspecting text-based content—messages, documents, and structured data. The platform explicitly states it does not yet inspect arbitrary files or images, focusing its deep inspection capabilities on the textual vectors of AI support workflows.