ASAI Security ResearchIndependent public-source research
Public reviewread only

Solution approach

Sensitive-data discovery and access

Find sensitive data, understand who can reach it, and reduce unsafe exposure to AI.

Use-case context

How this approach relates to the selected use case

Applications and agents: Additional if: AI retrieves sensitive company data — Sensitive information retrieved from company data stores must be protected as it enters an AI workflow.

Back to use case →
Research scopeVendorsPublicly documented vendor profiles
Evaluation guideRequirementsRequirements connected to the selected use case
Evidence basisSourcesPublic claims linked to their original sources
Unresolved itemsQuestionsMissing support is labeled instead of assumed
View research coverageThese counts describe available public research, not product quality or suitability.Expand
Vendor profiles
12 shown in this view
Security requirements
1 to review
Strong public support
10 requirement records
Limited public support
2 requirement records
Open research
0 with no supporting claim · 0 incomplete

Evaluation guide

What to verify for this use case

Foundational security requirement

Sensitive-data protection for generative AI

Detect, classify, redact, or block sensitive data in prompts, responses, files, retrieval, memory, and AI-connected workflows.

Questions to test
  1. Sensitive prompt, response, or file test data is detected and classified during an AI interaction.
  2. A policy redacts, blocks, coaches, or records the sensitive data event before it leaves the approved path.
  3. The evidence record shows data class, user, app or model, action, and timestamp.
Related frameworks

NIST AI RMF Playbook · NIST Cybersecurity Framework 2.0 · CIS Critical Security Controls · ISO/IEC 42001 · OWASP GenAI Security Solutions Landscape

Vendor research

Vendors with public research for this approach

Choose vendors to compare →

Only requirements explicitly connected to the selected use case are shown. Vendors are grouped by whether this approach is a core product focus or related coverage, then ordered by documented support across the requirements shown. This organizes public research coverage; it is not a product ranking or recommendation.

Evidence labelsStrong public supportLimited public supportNo supporting claim foundResearch incomplete
VendorPrompt and data protectionSourcesAction
Core product focusThis approach is central to how these vendors present the product · 7 vendors
BigID AI Security and GovernanceScaledSupport found for 1 of 1 requirementStrong public support1Profile →
CyberhavenScaledSupport found for 1 of 1 requirementStrong public support1Profile →
Microsoft Purview DSPM for AIEstablishedSupport found for 1 of 1 requirementStrong public support1Profile →
Nightfall AIGrowth stageSupport found for 1 of 1 requirementStrong public support1Profile →
Orca AI-SPMScaledSupport found for 1 of 1 requirementStrong public support1Profile →
Varonis AI SecurityEstablishedSupport found for 1 of 1 requirementStrong public support1Profile →
Veeam / Securiti AIEstablishedSupport found for 1 of 1 requirementStrong public support1Profile →
Related coverageThese vendors address the requirements through another core product focus · 5 vendors
Netskope AI SecurityEstablishedSupport found for 1 of 1 requirementStrong public support1Profile →
Palo Alto Networks Prisma AIRSEstablishedSupport found for 1 of 1 requirementStrong public support1Profile →
Wiz AI-SPM / Google CloudEstablishedSupport found for 1 of 1 requirementStrong public support1Profile →
Singulr AIEmergingSupport found for 1 of 1 requirementLimited public support1Profile →
Upwind AI SecurityScaledSupport found for 1 of 1 requirementLimited public support1Profile →

Company maturity remains a filter and profile attribute; it does not affect the research-coverage order.