ASAI Security ResearchIndependent public-source research
Public reviewread only

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

Clear all filters
AIM Security / Cato NetworksAI governance, risk, and complianceSource checkedLimited public support for this requirement

Cato AI Security claims discovery and inventory of managed, local, and shadow agents, centralized runtime visibility, security posture, compliance-risk remediation, and corporate policy across users, agents, applications, models, and tools.

Gain visibility into which agents exist, what data sources and tools they can access, and how they behave at runtime.
Related framework references (5)
AIM Security / Cato NetworksAI assurance and adversarial testingNo supporting claim found

Cato AI Security and AIM materials reviewed did not provide a public customer-facing product claim for automated adversarial testing, repeatable attack suites, model or agent red teaming, or release-gate evaluation.

No quoted source text is recorded for this claim.
Related framework references (5)
AIM Security / Cato NetworksAI model and supply-chain securitySource checkedLimited public support for this requirement

Cato and AIM claim continuous AI-SPM scanning of internal models, agent configurations, Model Context Protocol (MCP) connections, training environments, misconfigurations, and vulnerabilities before production.

Continuously discovers, detects, and remediates AI security and compliance risks before they reach production, and scans internal AI models for misconfigurations and vulnerabilities.
Related framework references (5)
AIM Security / Cato NetworksAI gateway, tool-connection, and runtime controlsSource checkedStrong public support for this requirement

Cato AI Security claims runtime policy across user prompts, model outputs, tool calls, and tool messages, blocking or redacting sensitive data and indirect prompt injection before content reaches an agent or model.

Enforces runtime policies across all four inspection points: user prompts, model outputs, tool calls, and tool messages.
Related framework references (5)
AIM Security / Cato NetworksAI agent identity and permissionsSource checkedLimited public support for this requirement

Cato AI Security claims visibility into agent configurations, licenses, data and tool access, plus corporate policy enforcement and blocking of unauthorized access or unsafe actions across managed and local agents.

Reduce the risk of unauthorized access, sensitive data exposure, and unsafe agent actions.
Related framework references (5)
AIM Security / Cato NetworksAI coding-agent and workstation securitySource checkedStrong public support for this requirement

Cato claims endpoint discovery and runtime control for Cursor, Claude Code, and other coding agents, covering configurations, licenses, Model Context Protocol (MCP) servers, prompts, model outputs, tool calls, tool messages, credentials, PII, and malicious tool responses.

Discover and secure AI agents that run on user endpoints, such as coding agents.
Related framework references (5)
AIM Security / Cato NetworksAI cost and usage controlsNo supporting claim found

Cato AI 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)
AIM Security / Cato NetworksUnapproved AI use discoverySource checkedStrong public support for this requirement

AIM Security (now Cato AI Security) claims it surfaces AI adoption trends, assesses risks, and detects unauthorized data exchange with public AI services.

With Cato, IT teams can understand AI adoption trends with the business, assess risks and enforce granular access controls, and detect unauthorized data exchange with public AI services in real-time.
Related framework references (5)
AIM Security / Cato NetworksApproved AI usage monitoringSource checkedStrong public support for this requirement

AIM Security (Cato) claims it gives full visibility and control into which generative AI apps are used and what data is shared with the AI models.

full visibility and control into what GenAI apps are used, and what data is shared with the AI models
Related framework references (5)
AIM Security / Cato NetworksControls for unapproved AI useSource checkedStrong public support for this requirement

AIM Security (Cato) claims it enforces granular access controls, prevents data leakage, and limits AI misuse via policy enforcement.

enforce granular access controls, and detect unauthorized data exchange with public AI services in real-time.
Related framework references (5)
AIM Security / Cato NetworksSensitive-data protection for generative AISource checkedStrong public support for this requirement

AIM Security (Cato) claims monitoring and governing prompts and responses prevents data leakage and supports governance and compliance.

By monitoring and governing prompt and responses, inline, using APIs or with a browser extension, organizations can prevent data leakage, limit misuse, and ensure governance and compliance for AI use.
Related framework references (5)
AIM Security / Cato NetworksAction-taking agent monitoringSource checkedStrong public support for this requirement

AIM Security (Cato) claims it monitors every interaction between agents, models, and Model Context Protocol (MCP) servers to keep agents secure and compliant.

monitor every interaction between agents, models, and MCP servers, to ensure agents operate securely, remain complaint, and align with business needs.
Related framework references (5)
AIM Security / Cato NetworksAgent-to-agent communication securitySource checkedRelated public context only

Cato AI Security claims monitoring every interaction between agents, models, and Model Context Protocol (MCP) servers helps ensure agents operate securely and remain aligned with business needs.

monitor every interaction between agents, models, and MCP servers, to ensure agents operate securely, remain complaint, and align with business needs.
Related framework references (5)
AIM Security / Cato NetworksNon-human identity and service-account securitySource checkedLimited public support for this requirement

Cato AI Security claims it discovers and analyzes enterprise AI agent activity and monitors interactions between agents, models, and Model Context Protocol (MCP) servers.

monitor every interaction between agents, models, and MCP servers
Related framework references (5)
AIM Security / Cato NetworksBrowser and business-application controlsSource checkedLimited public support for this requirement

AIM (Cato) claims it lets organizations use generative AI securely with full visibility and control into which apps are used and what data is shared.

full visibility and control into what GenAI apps are used, and what data is shared with the AI models
Related framework references (5)
AIM Security / Cato NetworksGenerative AI application securitySource checkedStrong public support for this requirement

AIM (Cato) claims it secures private AI applications in runtime and detects runtime AI attacks and compliance violations.

Homegrown AI applications and AI agents are attractive targets for internal and external attacks—an emerging threat vector that requires dedicated defenses. Using proprietary models specifically trained to detect all types of runtime AI attacks and compliance violations, IT teams can support enterprise-scale secure delivery of AI apps and agents.
Related framework references (5)