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Public-source research

Vendor evidence

Review what vendors say publicly, the exact quoted source text, the security requirement each statement may support, and what still needs verification.

Research library coverageCounts describe the research workflow, not vendor quality or product effectiveness.View details
Evidence records1280
Source checked863
Needs verification0
Source captured0
No supporting claim found411
Excluded from evidence6

Showing 61–70 of 70 evidence records

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MindgardSensitive-data protection for generative AISource checkedStrong public support for this requirement

Mindgard claims inline detection and enforcement for data leakage in AI application traffic.

inline detection and enforcement for prompt injection, data leakage, and tool abuse
Related framework references (5)
Enkrypt AISensitive-data protection for generative AISource checkedStrong public support for this requirement

Enkrypt AI claims runtime controls against sensitive-data exfiltration through tools, retrieval, and model outputs.

Sensitive data exfiltration via tools, retrieval, or outputs
Related framework references (5)
AktoSensitive-data protection for generative AISource checkedStrong public support for this requirement

Akto claims controls that stop PII, secrets, and source code from leaking into AI prompts.

Stops PII, secrets and source code leaking into prompts sent to AI tools
Related framework references (5)
Okta for AI AgentsSensitive-data protection for generative AISource checkedLimited public support for this requirement

Okta claims least-privilege policies that constrain agent access to critical systems and data.

Enforce least-privilege policies to protect critical systems and data.
Related framework references (5)
CyberArk Secure AI AgentsSensitive-data protection for generative AISource checkedLimited public support for this requirement

CyberArk claims task-specific least-privilege access to protect sensitive resources used by agents.

Permissions are granted to AI agents only for a specific task
Related framework references (5)
BigID AI Security and GovernanceSensitive-data protection for generative AISource checkedStrong public support for this requirement

BigID claims labeling, masking, redaction, data loss prevention (DLP), data minimization, prompt interception, and sensitive-data controls for AI.

intercept risky prompts
Related framework references (5)
Obsidian AI SecuritySensitive-data protection for generative AISource checkedStrong public support for this requirement

Obsidian claims blocking sensitive prompts before proprietary data leaves the browser for third-party generative AI platforms.

catching and blocking sensitive prompts at the source
Related framework references (5)
Cloudflare AI Security SuiteSensitive-data protection for generative AISource checkedStrong public support for this requirement

Cloudflare claims data loss prevention (DLP) and prompt protection that block sensitive data in prompts, responses, and Model Context Protocol (MCP) traffic.

Scan user prompts and model responses to block sensitive data
Related framework references (5)
Backslash Agentic AI Endpoint SecuritySensitive-data protection for generative AISource checkedStrong public support for this requirement

Backslash claims real-time prevention of data exfiltration from agentic endpoints, including source code, secrets, credentials, and internal IP.

Detect and prevent attempted data exfiltration
Related framework references (5)