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GKData.io MCP

AISecurity theme

AI integration boundaries.

Authority boundaries around model input, tools, and downstream actions. 7 disclosures · 12 related references · 1 diagrams.

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Disclosures

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Related learning

Model Context Protocol Technical Standard

MCP elicitation: consent, credential custody and completion

Form elicitation excludes secrets. URL elicitation places sensitive interactions outside the MCP client and model context, with the requesting server and destination visible to the user. Agreeing to open the interaction…

Reviewed 2026-10-04Read

OWASP Gen AI Security Project Implementation Guide

OWASP LLM05:2025: generated-output consumer trust

Explains why model-generated content remains untrusted when passed to browsers, databases or backend functions. The relevant boundary is the consuming component: plausible model text must not acquire executable meaning…

Reviewed 2026-10-03Read

OWASP Cheat Sheet Series Architecture Guide

LLM Prompt Injection Prevention Cheat Sheet

Defense-in-depth guidance for LLM applications that consume untrusted content or invoke tools. Covers data provenance, least privilege, action authorization, monitoring, and the limitations of guardrails.

Reviewed 2026-10-02Read

Connected collection

Visual models

Related learning follows the topic crosswalk or an explicit diagram relationship. It does not classify a resource as a finding. Topics overlap, so their counts should not be added together.

GitHub snapshot 2026-10-04

53796974ace8 · JSON exports & schemas · CC BY 4.0 content / MIT software