Knostic GenAI Knowledge Security
Overview
Product details compiled from public sources, each with a citation.
- Description
- Detects where AI assistants such as Microsoft 365 Copilot and Glean overshare sensitive data and enforces need-to-know access controls on their answers.1agent
- Deployment
- SaaS1agent
- Status
- Active1agent
- Compliance
- SOC 2 Type 22 (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 | Protect | Detect | Coverage | Source |
|---|---|---|---|---|
| Runtime AI Data | Primary | 1 |
Framework Relevance
These frameworks include controls relevant to the asset classes Knostic GenAI Knowledge Security 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 | Runtime AI Data | Prompts (runtime); inference data |
| CSA AI Controls Matrix | Runtime AI Data | Data Security and Privacy Lifecycle Management; Application and Interface Security |
| ISO 42001 | Runtime AI Data | A.7 Data for AI systems; A.8 Information for interested parties |
| Google SAIF | Runtime AI Data | Expand AI red-teaming; runtime input and output safety; prompt defense |
| SANS Critical AI Security Guidelines | 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 | Runtime AI Data | AML.T0051 LLM Prompt Injection; AML.T0054 LLM Jailbreak; AML.T0056 Extract LLM System Prompt (system prompt leaks as inference data; the AI Coding and Orchestration Tools row owns it as configuration) |
| OWASP AI Exchange | Runtime AI Data | Input threats: prompt injection, adversarial inputs, evasion; runtime threats: RAG poisoning, memory tampering |
| OWASP LLM Top 10 | Runtime AI Data | LLM01 Prompt Injection; LLM02 Sensitive Information Disclosure; LLM08 Vector and Embedding Weaknesses; LLM05 Improper Output Handling |
| OWASP Agentic Security Top 10 | 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
- Knostic AI Copilot Readiness listing on AWS Marketplace
- “Knostic offers an AWS-compatible solution that prevents both oversharing of sensitive data and undersharing of valuable business information in enterprise AI search tools through need-to-know access controls.”
- Knostic Trust Center
- “SOC 2 Type 2”
Changelog
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Refreshed source citations to the vendor AWS Marketplace listing and updated the description.
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Corrected matrix coverage (erratum): removed the AI coding and orchestration tools row.
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Added to the catalog from the Knostic documentation.
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Added a company-level SOC 2 Type 2 attestation cited to the Knostic trust center.
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