AI Defense Matrix Catalog

Knostic Kirin

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Overview

Product details compiled from public sources, each with a citation.

Vendor
Knostic3
Description
Security for AI coding assistants such as Cursor, Copilot, and Claude Code that inspects MCP connections in real time, monitors IDE extensions and plugins, and blocks risky components.3
Deployment
SaaS2
Status
Active2
Compliance
SOC 2 Type 21 (company-level, see Methodology)

Matrix Coverage

Where this product defends, by asset class and NIST CSF function. The Coverage column shows whether each asset is Primary, Secondary, or Adjacent to what the product does. The table omits empty rows and columns.

Asset class IdentifyProtectDetect Coverage
AI Orchestration Tools Primary 3
AI-Generated Code Secondary 3
Runtime AI Data Secondary 2

Framework Relevance

These frameworks include controls relevant to the asset classes Knostic Kirin defends. This is an editorial inference from the AI Defense Matrix asset-level crossmap, not a statement that Knostic implements these controls or is certified against them.

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Framework Asset class Relevant controls
NIST IR 8596 AI Orchestration Tools Agents as deployed artifacts (orchestration view; see AI Agent Identities row for the principal view); system prompts and templates
Runtime AI Data Prompts (runtime); inference data
CSA AI Controls Matrix AI Orchestration Tools Application and Interface Security; Supply Chain Management
AI-Generated Code Application and Interface Security; Supply Chain Management
Runtime AI Data Data Security and Privacy Lifecycle Management; Application and Interface Security
ISO 42001 AI Orchestration Tools A.6 AI system life cycle; A.5 Assessing impacts of AI systems
AI-Generated Code A.6 AI system life cycle
Runtime AI Data A.7 Data for AI systems; A.8 Information for interested parties
Google SAIF AI Orchestration Tools Secure the AI supply chain; application and pipeline security; agent orchestration controls
AI-Generated Code Secure the AI pipeline; code provenance and supply chain integrity
Runtime AI Data Expand AI red-teaming; runtime input and output safety; prompt defense
SANS Critical AI Security Guidelines AI Orchestration Tools Secure Agentic Systems and AI Autonomy Controls (defined function scope; execution isolation; API and function-call gating); Limit Model Behavior (focused functionality; access controls outside the model)
AI-Generated Code Model I/O Handling (AI deployment in IDEs: prefer local-only integrations to limit exposure of code, keys, and proprietary data); Governance, Risk, Compliance (regularly test and red-team AI applications before and after deployment)
Runtime AI Data Model I/O Handling (sanitize, validate, and filter inputs and outputs; segregate user and system prompts; multilayered prompt-injection defense); Conventional Security Controls (protect augmentation and RAG data with vector-store access controls and validation); Data Minimization and Obfuscation (limit sensitive prompt content; context-window management); Limit Model Behavior (AI guardrails)
MITRE ATLAS AI Orchestration Tools AML.T0051 LLM Prompt Injection; AML.T0054 LLM Jailbreak; AML.T0016 Obtain Capabilities (malicious plugins)
AI-Generated Code AML.T0010 AI Supply Chain Compromise (hallucinated dependencies and slopsquatting); AML.T0018 Manipulate AI Model (when models embed code-execution backdoors)
Runtime AI Data AML.T0051 LLM Prompt Injection; AML.T0054 LLM Jailbreak; AML.T0056 Extract LLM System Prompt
OWASP AI Exchange AI Orchestration Tools Development-time threats: agent framework supply chain; runtime threats: plugin abuse, prompt injection via tools
AI-Generated Code Development-time threats: insecure code generation, license risk, hallucinated dependencies
Runtime AI Data Input threats: prompt injection, adversarial inputs, evasion; runtime threats: RAG poisoning, memory tampering
OWASP LLM Top 10 AI Orchestration Tools LLM01 Prompt Injection; LLM05 Improper Output Handling; LLM07 System Prompt Leakage; LLM10 Unbounded Consumption
AI-Generated Code LLM06 Excessive Agency (code execution); insecure or vulnerable code patterns inherited from training data
Runtime AI Data LLM01 Prompt Injection; LLM02 Sensitive Information Disclosure; LLM08 Vector and Embedding Weaknesses; LLM05 Improper Output Handling
OWASP Agentic Security Top 10 AI Orchestration Tools ASI01 Agent Goal Hijack; ASI02 Tool Misuse and Exploitation; ASI05 Unexpected Code Execution (RCE); ASI07 Insecure Inter-Agent Communication; ASI08 Cascading Failures; ASI10 Rogue Agents
AI-Generated Code ASI05 Unexpected Code Execution (RCE); ASI04 Agentic Supply Chain Vulnerabilities (hallucinated dependencies and vibe-coding artifacts)
Runtime AI Data ASI06 Memory & Context Poisoning; ASI01 Agent Goal Hijack (via prompt injection in runtime inputs)

Provenance

Last sourced 2026-06-13.

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Sources

  1. Knostic Trust Center
    Vendor source accessed 2026-06-13
    • “SOC 2 Type 2”
  2. Kirin | Security Platform for AI Coding Assistants
    Vendor source accessed 2026-06-11
    • “Kirin automatically redacts and guards sensitive data inside your IDE.”
  3. AI Coding Security Solution | Kirin by Knostic
    Vendor source accessed 2026-06-11
    • “Kirin continuously monitors IDE extensions and plugins, detecting vulnerabilities and blocking untrusted or risky components before they impact your workflow.”
    • “By validating MCP servers and extensions, scanning dependencies, and blocking unsafe actions in real time inside the IDE.”

Changelog

  1. Added a company-level SOC 2 Type 2 attestation cited to the Knostic trust center.

  2. Corrected the entry to describe Kirin, the Knostic product that secures AI coding assistants. The previous text described the separate Knostic knowledge-security platform.

  3. Verified details and sources; set the product name to Knostic Kirin (company Knostic) and corrected the URL and category.

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