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Koreshield

PaidAPI

Your AI support agent passes testing clean — then a customer pastes a poisoned ticket comment, and your model treats it as a trusted instruction. Koreshield sits at each trust boundary in that workflow and stops the handoff before the damage lands.

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Summary

Koreshield evaluates three specific points where trust can fail in an AI support workflow: the customer's raw input, the content retrieved from your RAG store or CRM, and the tool calls your model proposes before they execute. Each decision is recorded with a reason, so when a threat is detected you have evidence, not just an alert. You start in detect mode — traffic flows uninterrupted while the tool builds a picture of what your workflow actually looks like — then you flip to enforcement once you understand the fallback path. The vendor is explicit about what it does not do: it does not replace your authorization system, does not inspect arbitrary files or images, and does not claim complete attack coverage. Teams operating under audit or compliance requirements get the evidence export they need; teams expecting a silver bullet will need to pair this with other controls.

Bottom line: Pick this for the move from AI support testing to regulated production, where every blocked request needs a logged reason — but if your threat surface includes file uploads or image attachments, you will need a separate scanning layer today.

Pricing Plans

Subscription

Starter

$20per month

250,000 protected requests/month. Input, context, and action scans. 7-day evidence window.

  • Detect and enforce modes
  • API key management

Growth

$99per month

2 million protected requests/month. Advanced screening. 30-day evidence window.

  • Validation and alerting workflows
  • Policy review

Enterprise

Custom

Custom volume and deployment. SSO/SAML, SIEM export, custom retention.

  • Hosted, VPC, self-hosted, air-gapped options
  • Dedicated support

View full pricing on koreshield.ai →

Pricing may have changed since last verified. Check the official site for current plans.

Find your fit

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Pros

  • Scans customer input, retrieved RAG context, and proposed tool calls as three independent trust boundaries, so a poisoned ticket comment cannot silently inherit model authority the way it does in a single-pass filter.
  • Detect mode records every threat decision without blocking traffic, which means you accumulate evidence against your real support workflow before you commit to enforcement — and you can show that evidence in an audit.
  • Reason-logged decisions on every scan, so teams in regulated environments can export a trace of what was blocked and why rather than reconstructing that from application logs after an incident.
  • API-first integration with server-side scan keys, so the security boundary stays out of client code and the decision path does not depend on the model you are running or the support platform you are using.
  • Staged rollout posture built into the product, which means the path from 'evaluating' to 'enforcing in production' has a defined checkpoint — you enforce only where the fallback behavior is understood, not at first deploy.

Cons

  • File and image attachments are outside the scan boundary at this stage — teams whose customers submit screenshots, PDFs, or other files as part of support tickets are exposed at exactly that input surface and need a separate scanning layer to cover it.
  • The tool does not replace your authorization system, it sits beside it — which means any team expecting a single control to cover both threat detection and access enforcement will be maintaining two systems regardless, and the integration burden lands on your side.
  • Coverage is bounded by what the vendor describes as not promising complete attack coverage, so novel injection patterns that have not been characterized yet pass through in detect mode as misses; teams with adversarial customers or high-value targets cannot treat logged decisions as a complete threat record.
  • No self-hosted option is available, which means teams with data-residency requirements or policies against third-party cloud routing for customer message content must either get a contractual exception or move to a competitor that supports on-premises deployment.

About

API Available
Yes
Self-Hosted
No
Last Updated
September 24, 2026

Best For

Who it's for

  • Teams moving AI support from testing to production
  • Regulated or high-volume AI workflows
  • Organizations needing evidence export and alerting

What it does well

  • Protecting production AI support workflows
  • Reviewing security decisions in teams
  • Enforcing policies on AI actions and context

Frequently Asked Questions

Is Koreshield free?
Koreshield is a paid tool. A 7-day free trial is available.
Does Koreshield have an API?
Yes. Koreshield exposes a developer API. See the official documentation at https://koreshield.ai for details.

The problem Koreshield is built around is prompt injection through trusted context: a poisoned CRM note, a malicious ticket attachment, or a retrieval result that inherits system-level authority it was never meant to have. The tool scans three boundaries independently — the raw customer message, the retrieved context passed to the model, and the tool calls the model proposes — and records a structured decision for each. The integration is API-first: you create a server-side scan key, point your workflow at the FastAPI security service backed by PostgreSQL, and begin receiving decisions before you block anything.

The defining architectural choice is detect-before-enforce. The vendor describes a staged rollout: observe live traffic without interrupting it, review the evidence log for misses and false positives, and only enable enforcement once you understand what the fallback behavior looks like when a request is stopped. This makes the evaluation period auditable rather than speculative — you can show stakeholders exactly what the tool caught and what it missed against real production traffic before any policy takes effect.

Koreshield fits teams moving AI support workflows from internal testing into environments where a bad decision has compliance or customer-facing consequences. The docs describe it as a complement to existing authorization systems, not a replacement — a distinction that matters for regulated workflows where access control and threat detection need to stay separate. The ceiling appears when your inputs include files or images: the vendor states the tool does not inspect arbitrary files or images at this stage, which means teams with those vectors need a parallel scanning solution or must exclude those input types from coverage.

Deployment runs as a FastAPI service with PostgreSQL, connected to from a hosted console or your own support infrastructure. The API is available for server-side integration, and the scan key model keeps security decisions server-side rather than inside client code. Teams evaluating the tool start with a no-card evaluation period before any enforcement decisions are made.

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