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

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Showing 1–19 of 19 evidence records

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Operant AIAI governance, risk, and complianceSource checkedStrong public support for this requirement

Operant claims a centralized AI and Model Context Protocol (MCP) registry, security graph, threat mappings, agent and tool governance, audit artifacts, regulatory-control mappings, endpoint inventory, and real-time policy across the AI surface.

Establish a centralized governance framework for managing AI agents and tools across the enterprise.

Related framework references (5)

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

Operant AIAI assurance and adversarial testingSource checkedStrong public support for this requirement

Operant claims open-source Woodpecker red teaming for early vulnerability detection and attack simulation as part of its AI security approach.

Operant’s Woodpecker simplifies this with open-source red teaming, enabling early vulnerability detection.

Related framework references (5)

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

Operant AIAI model and supply-chain securitySource checkedStrong public support for this requirement

Operant claims an enterprise Model Context Protocol (MCP) and skills registry, trust scoring, trust zones, artifact quarantine, component and relationship mapping, and blocking of untrusted servers, tools, skills, plugins, packages, and supply-chain behavior.

Map trust scores and enforce trust boundaries, ensuring only verified entities operate within your AI agent supply chain.

Related framework references (5)

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

Operant AIAI gateway, tool-connection, and runtime controlsSource checkedStrong public support for this requirement

Operant claims an large language model (LLM) Gateway and Model Context Protocol (MCP) Gateway with routing, request firewall, prompt and response inspection, tool-call blocking, intent guards, data loss prevention (DLP), redaction, threat detection, rate limits, and runtime response.

Tool-call inspection and blocking with full AuthNZ enforcement.

Related framework references (5)

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

Operant AIAI agent identity and permissionsSource checkedStrong public support for this requirement

Operant claims AI non-human identity detection, agent identity and access control, fine-grained identity-aware Model Context Protocol (MCP) enforcement, least privilege, authorization validation, trust scores, and per-agent tool restrictions.

Detect and block unauthenticated and unauthorized AI agent behavior in real time.

Related framework references (5)

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

Operant AIAI coding-agent and workstation securitySource checkedStrong public support for this requirement

Operant claims device-layer controls for Claude Code, Cursor, Copilot, Cline, Windsurf, Aider, and custom agents, covering shell commands, files, repositories, credentials, packages, plugins, skills, prompts, Model Context Protocol (MCP) tools, application programming interfaces (APIs), and proprietary code.

Real-time shell command monitoring distinguishes legitimate developer tooling from injection-driven attacks — and blocks before execution.

Related framework references (5)

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

Operant AIAI cost and usage controlsNo supporting claim found

Operant AI platform 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)

Commercial Metadata NIST AI RMF Playbook NIST Cybersecurity Framework 2.0 ISO/IEC 42001 OWASP Agentic AI Security Solutions Landscape

Operant AIUnapproved AI use discoverySource checkedLimited public support for this requirement

Operant claims real-time visibility and controls for every Model Context Protocol (MCP) server, client, tool, and connection in the environment, including registries, allow/block lists, and non-human identity (NHI) access controls.

Real-time visibility and controls for every MCP server, client, tools, and connections in your environment, with MCP registries, white list/black lists, and NHI access controls, so your entire team can develop AI and Agents, safer and faster.

Related framework references (5)

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

Operant AIAI-feature discovery in business applicationsSource checkedLimited public support for this requirement

Operant claims it can discover managed and unmanaged agents running in software as a service (SaaS) platforms.

Discover managed and unmanaged agents running in cloud environments, SaaS platforms, and development tools.

Related framework references (5)

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

Operant AIApproved AI usage monitoringSource checkedLimited public support for this requirement

Operant AI claims it secures AI prompts, interactions, agents, and all data-in-use through the live application stack.

Operant actively secures AI prompts, interactions, agents, and all data-in-use as it flows through your live application stack

Related framework references (5)

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

Operant AIControls for unapproved AI useSource checkedStrong public support for this requirement

Operant AI claims inline controls that block rogue agents, out-of-scope actions, unauthorized access, and critical agentic attacks.

blocking out-of-scope actions before execution and alerting your security team with full action traces before damage is done.

Related framework references (5)

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

Operant AISensitive-data protection for generative AISource checkedStrong public support for this requirement

Operant AI claims it auto-redacts sensitive data inline across AI prompts, interactions, agents, and data-in-use within the live application stack.

Proactively block critical LLM and GenAI threats like prompt injection and data exfiltration while maintaining full data privacy and data governance with Inline Auto-Redaction of Sensitive Data.

Related framework references (5)

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

Operant AIAction-taking agent monitoringSource checkedStrong public support for this requirement

Operant claims real-time protection across the full agent toolchain from Model Context Protocol (MCP) clients and endpoints to live, interactive agentic applications.

Operant’s real-time protection across the full agent toolchain — from MCP clients and endpoints to live, interactive agentic applications — lets technology leaders move fast without compromising customer privacy

Related framework references (5)

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

Operant AIAgent-to-agent communication securitySource checkedLimited public support for this requirement

Operant AI claims real-time protection across the agent toolchain, including Model Context Protocol (MCP) clients, endpoints, and live interactive agentic applications.

Operant’s real-time protection across the full agent toolchain — from MCP clients and endpoints to live, interactive agentic applications — lets technology leaders move fast without compromising customer privacy

Related framework references (5)

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

Operant AINon-human identity and service-account securitySource checkedStrong public support for this requirement

Operant AI claims Agent Protector catalogs agent identities, including user and service accounts, and its Model Context Protocol (MCP) security includes non-human identity (NHI) access controls.

The system creates detailed catalogs of agent identities, including both user and service accounts

Related framework references (5)

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

Operant AIBrowser and business-application controlsNo supporting claim found

No public claim found for this capability.

No quoted source text is recorded for this claim.

Related framework references (5)

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

Operant AIGenerative AI application securitySource checkedStrong public support for this requirement

Operant AI claims it detects and prioritizes AI-specific risks including prompt injection, large language model (LLM) poisoning, model theft, and sensitive data leakage.

Detect and prioritize AI-specific risks like prompt injection, LLM poisoning, model theft, and sensitive data leakage.

Related framework references (5)

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

Operant AILicensing modelNo supporting claim found

No public claim found for this capability.

No quoted source text is recorded for this claim.

Related framework references (2)

Commercial Metadata CSA AI Controls Matrix

Operant AIApproved AI platform contextSource checkedLimited public support for this requirement

Operant AI claims AI Gatekeeper provides real-time security for AI applications and agents.

AI Gatekeeper Real-time Security for AI Applications and Agents

Related framework references (5)

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