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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 1–19 of 19 evidence records

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Prompt Security / SentinelOneAI governance, risk, and complianceSource checkedStrong public support for this requirement

Prompt Security claims enterprise AI and Model Context Protocol (MCP) discovery, risk scoring, policy enforcement, searchable interaction logs, role-based controls, compliance policy, drift monitoring, and human oversight for agentic systems.

Get complete, searchable logs of every interaction for risk management.
Related framework references (5)
Prompt Security / SentinelOneAI assurance and adversarial testingSource checkedStrong public support for this requirement

Prompt Security claims automated preproduction and continuous red teaming for prompt injection, data exposure, privilege escalation, jailbreaks, unsafe agent behavior, drift, and other AI-specific risks with evidence and remediation guidance.

Run pre-production red teaming, prioritize issues using risk scoring and evidence, and confidently ship production-ready AI applications.
Related framework references (5)
Prompt Security / SentinelOneAI model and supply-chain securitySource checkedLimited public support for this requirement

Prompt Security claims dynamic risk scoring of more than 13,000 Model Context Protocol (MCP) servers, vulnerability profiles, certification checks, shadow-server discovery, and agent skill integrity and drift checks.

MCP risk scoring, dynamically assessing over 13,000 MCP servers on GitHub to identify emerging threats.
Related framework references (5)
Prompt Security / SentinelOneAI gateway, tool-connection, and runtime controlsSource checkedStrong public support for this requirement

Prompt Security claims an AI and Model Context Protocol (MCP) Gateway that inspects requests, responses, prompts, templates, agent actions, and server interactions in real time with allow or block policy, threat intelligence, data loss prevention (DLP), and endpoint enforcement.

Inspecting every request and response in real time to protect sensitive data and information.
Related framework references (5)
Prompt Security / SentinelOneAI agent identity and permissionsSource checkedLimited public support for this requirement

Prompt Security claims granular policy by user, group, server, and action plus attribution of AI use, data sharing, agent responses, and Model Context Protocol (MCP) activity.

Allow/block by user, server, or action according to your security policy.
Related framework references (5)
Prompt Security / SentinelOneAI coding-agent and workstation securitySource checkedStrong public support for this requirement

Prompt Security claims endpoint and integrated development environment (IDE)-integrated governance for coding assistants, Model Context Protocol (MCP) servers, exposed commands, secrets, PII, generated code, prompt responses, and action-level policy across tools including Cursor and GitHub Copilot.

Fine-grained policies that determine which MCPs are allowed, which commands can be run, and under what circumstances.
Related framework references (5)
Prompt Security / SentinelOneAI cost and usage controlsNo supporting claim found

SentinelOne Prompt Security materials reviewed did not provide a public product claim for AI usage-cost attribution, token or spend metrics, budgets, chargeback, or cost-aware model routing.

No quoted source text is recorded for this claim.
Related framework references (5)
Prompt Security / SentinelOneUnapproved AI use discoverySource checkedStrong public support for this requirement

SentinelOne Prompt Security claims it inventories every AI tool and code assistant in use, including unapproved shadow AI.

Inventory every AI tool and code assistant in use, including unsanctioned shadow AI
Related framework references (5)
Prompt Security / SentinelOneApproved AI usage monitoringSource checkedLimited public support for this requirement

SentinelOne Prompt Security claims integration with AI code assistants such as GitHub Copilot and Claude Code for secure AI usage policy enforcement in development environments.

Yes. Prompt Security integrates with AI code assistants like GitHub Copilot and Claude Code to prevent secrets, credentials, and proprietary code from leaking into prompts, while enforcing secure AI usage policies across development environments.
Related framework references (5)
Prompt Security / SentinelOneControls for unapproved AI useSource checkedStrong public support for this requirement

SentinelOne Prompt Security claims granular, role-based controls for who can use AI, how, and with what data.

Set granular, role-based controls for who can use AI, how, and with what data.
Related framework references (5)
Prompt Security / SentinelOneSensitive-data protection for generative AISource checkedStrong public support for this requirement

SentinelOne Prompt Security claims it redacts sensitive data and enforces policies across 15,000+ AI services in real time.

Redact sensitive data and enforce policies across 15,000+ AI services in real time
Related framework references (5)
Prompt Security / SentinelOneAction-taking agent monitoringSource checkedStrong public support for this requirement

SentinelOne Prompt Security claims searchable audit logs for every agent action, decision, and enterprise system interaction.

Get a searchable audit log of every agent action, decision, and enterprise system interaction
Related framework references (5)
Prompt Security / SentinelOneAgent-to-agent communication securitySource checkedLimited public support for this requirement

Prompt Security claims runtime policy controls for Model Context Protocol (MCP) interactions, including allow or block decisions by user, server, and action.

Allow/block by user, server, or action
Related framework references (5)
Prompt Security / SentinelOneNon-human identity and service-account securitySource checkedLimited public support for this requirement

Prompt Security from SentinelOne claims visibility into agents and Model Context Protocol (MCP) servers plus least-privilege access enforcement for AI agents.

Enforce least-privilege access so agents operate only within their defined scope
Related framework references (5)
Prompt Security / SentinelOneBrowser and business-application controlsSource checkedStrong public support for this requirement

Prompt Security claims it provides employees with visibility, security, and governance over AI tools usage.

Attain visibility, security and governance for AI tools usage
Related framework references (5)
Prompt Security / SentinelOneGenerative AI application securitySource checkedStrong public support for this requirement

Prompt Security claims it blocks prompt injections, data leaks, and toxic large language model (LLM) content for homegrown generative AI apps.

Block prompt injections, data leaks and toxic LLM content
Related framework references (5)
Prompt Security / SentinelOneApproved AI platform contextSource checkedRelated public context only

SentinelOne positions AI security as connected with endpoint, cloud, identity, and AI telemetry, making Prompt Security a platform-extension candidate for existing Singularity Endpoint customers.

SentinelOne connects endpoint, cloud, identity, and AI telemetry so teams can see risk clearly without stitching tools together.
Related framework references (5)