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
Wiz claims centralized AI inventory, posture, ownership context, compliance mapping, security baselines, prioritized risk, and remediation workflows across models, agents, services, data, infrastructure, and applications.
AI-SPM is designed to secure AI pipelines and accelerate AI adoption while maintaining protection against AI-related risks.
Related framework references (5)
Microsoft Purview claims security and compliance oversight for AI-agent interactions, including inventory, data security posture management (DSPM) reporting, audit, retention, eDiscovery, communication compliance, and policy recommendations.
All the listed agents are supported by DSPM for AI and have their own dedicated Apps and agents page.
Related framework references (5)
Noma claims continuous discovery, an enterprise agent and Model Context Protocol (MCP) registry, risk context, accountable ownership, and approved, review, or blocked governance states across AI systems.
Every agent, connected MCP server, and tool surfaces in a dynamic registry with context already attached.
Related framework references (5)
WitnessAI claims unified governance across employees and agents using AI inventory, contextual policies, audit trails, reporting, approved-tool control, and compliance-oriented interaction logging.
Apply governance consistently across employees and agents.
Related framework references (5)
Netskope claims unified AI governance using AI inventory, risk assessments, interaction logs, compliance mappings, policy controls, guardrails, and a single platform policy framework.
Log detailed session information, including initializations, tool requests, and responses, to provide the transparency required for AI governance.
Related framework references (5)
Zscaler claims AI asset management, AI bill of materials, posture and risk assessment, compliance heat maps, governance status, access policy, and data-lineage visibility across the AI lifecycle.
Discover and map your entire AI ecosystem, from shadow AI to risky apps, models, and pipelines.
Related framework references (5)
Check Point AI Agent Security claims continuous agent inventory, holistic risk ratings, contributing-factor explanations, and risk mappings to OWASP and MITRE ATLAS.
Every discovered agent gets a holistic risk rating with the contributing factors explained.
Related framework references (5)
Lasso claims continuous agent discovery, AI bill of materials (AI-BOM) inventory, risk scoring, ownership, intent-aware policy, compliance mapping, audit logs, and cross-platform governance from code to runtime.
A single source of truth for governing agentic AI from code to runtime.
Related framework references (5)
Pangea AI Guard claims customizable security recipes, centralized usage summaries, tamper-resistant activity logging, attribution, webhooks, and audit trails for AI application events.
Requests to the AI Guard APIs and their processing results are logged in your Pangea project’s audit trail.
Related framework references (5)
F5 claims centralized observability, audit-ready logs, policy enforcement, regulatory assurance, usage tracking, customizable rules, and continuous compliance across AI models and applications.
Complete traceability of AI decisions for regulatory reviews.
Related framework references (5)
Oasis claims agent discovery, inventory, ownership, credential governance, policy-driven approvals, chain-of-custody evidence, regulator-ready auditability, and lifecycle control for AI agents and non-human identities.
Every session generates a complete chain of custody: Human → Agent → Prompt → Intent → Policy → Identity → Actions → Results.
Related framework references (5)
Astrix claims real-time inventory of agents, Model Context Protocol (MCP) servers, and NHIs with ownership, business context, policy-at-creation, automated attestation, activity trails, and lifecycle governance.
Apply policy as agents are deployed to establish clear ownership and automate attestation.
Related framework references (5)
Entro claims discovery, ownership, lineage, blast-radius mapping, approval workflow, lifecycle provisioning and offboarding, continuous policy, segregation of duties, compliance dashboards, and audit-ready reports for agents and NHIs.
Every discovered agent and identity is mapped with ownership, permissions, lineage, and blast radius.
Related framework references (5)
Aembit claims centralized agent access policy, cryptographically verifiable identity, per-request policy decisions, and audit logs tying agent identity, user identity, target server, credential, and resource access together.
Every MCP request is logged with agent identity, user identity, target server, and policy decision.
Related framework references (5)
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)
Harmonic claims organization-wide AI discovery, interaction visibility, team-level intent analysis, unified policy for humans and agents, governance analytics, auditability, and real-time controls across browser, desktop, embedded, and Model Context Protocol (MCP) surfaces.
Every interaction visible. Every interaction governable.
Related framework references (5)
Cyberhaven claims continuous inventory of AI agents, applications, and Model Context Protocol (MCP) servers, multidimensional AI risk scoring, data-lineage chain of custody, behavioral telemetry, and policy enforcement for autonomous systems.
Continuous, automatically maintained inventory of every AI agent, GenAI application, and MCP server across your environment.
Related framework references (5)
Nightfall claims agent and Model Context Protocol (MCP) inventory, user and device attribution, usage mapping, audit-ready reports, full request and response logs, approval status, and consistent generative AI governance across software as a service (SaaS), endpoints, and agentic workflows.
Export audit-ready reports for compliance teams.
Related framework references (5)
Island claims unified visibility, governance, data protection, policy, audit, human oversight, usage analytics, and return on investment (ROI) reporting across browser, desktop, extension, network, embedded AI, and governed agents.
Every AI interaction across the organization is visible, governed, and protected from the start.
Related framework references (5)
LayerX claims centralized policy and operational visibility across user and agent prompts, actions, identities, applications, and data exchanges in browsers, desktop apps, integrated development environments (IDEs), extensions, and on-device agents.
Control every prompt, agent action, and data exchange across any browser, AI application and IDE.
Related framework references (5)