Public-source research
Review what vendors say publicly, the exact quoted source text, the security requirement each statement may support, and what still needs verification.
Showing 701–720 of 1280 evidence records
Reco claims AI security posture visibility across approved AI agents, software as a service (SaaS) applications, users, permissions, and data access.
Visibility and control over every agent from day one.
Reco claims teams can sanction approved agents, block unauthorized ones, and enforce least-privilege policies across the enterprise ecosystem.
Sanction approved agents, block unauthorized ones, and enforce least-privilege policies across your enterprise ecosystem.
Reco claims it identifies and mitigates data exposure risks across the agent and app ecosystem.
Identify and mitigate data exposure risks across your agent and app ecosystem.
Reco claims it maps every agent in the environment to its owner, permissions, and risk with lineage and context.
Know exactly what every agent in your environment can access, who owns it, and where the risk is. Before the next class of AI finds out first.
Reco claims AI-agent risk reduction through mapping cross-app connections, permissions, and automated actions across software as a service (SaaS).
Cross-application connection mappings
Reco claims it makes agents, integrations, and non-human identities visible and maps what they can access.
Every day, your business deploys more agents, integrations, and non-human identities. Most of them operate invisibly. Reco makes them visible, maps what they can access, and tells you when they deviate from policy, before they become a liability.
Lakera claims Workforce AI Security discovers shadow AI and stops sensitive data exposure across AI apps, browser extensions, desktop agents, integrated development environments (IDEs), and Model Context Protocol (MCP)-connected tools.
Discover shadow AI, assess risk, govern employee usage, and stop sensitive data exposure across AI apps, browser extensions, desktop agents, IDEs, and MCP-connected tools.
Lakera claims workforce AI visibility and policy enforcement across AI apps, browser extensions, desktop agents, integrated development environments (IDEs), Model Context Protocol (MCP)-connected tools, and software as a service (SaaS) services.
Employee AI usage is spreading faster than traditional controls can keep up — across browser tools, desktop apps, copilots, IDEs, and connected SaaS services.
Lakera claims employee AI usage includes approved and unapproved tools across browser, desktop, and software as a service (SaaS).
Teams are using sanctioned and unsanctioned AI tools across the browser, desktop, and SaaS.
Lakera claims security teams need policy by app, user, data type, and action for employee AI usage.
Security teams need policy by app, user, data type, and action — not blanket allow or block decisions.
Lakera claims Workforce AI Security stops sensitive data exposure across AI apps, browser extensions, desktop agents, integrated development environments (IDEs), and Model Context Protocol (MCP)-connected tools.
Discover shadow AI, assess risk, govern employee usage, and stop sensitive data exposure across AI apps, browser extensions, desktop agents, IDEs, and MCP-connected tools.
Lakera claims AI-agent landscape discovery, risk assessment, and real-time protection enforcement.
Discover your agent landscape, assess risk, and enforce protection in real time.
Lakera claims AI Agent Security provides visibility into agent usage and Model Context Protocol (MCP)-connected systems, adjacent to agent-to-tool security.
AI Agent Security provides visibility into agent usage and MCP-connected systems across your environment, including agents your teams did not explicitly build or register.
No public claim found for this capability.
Zenity claims full inventory and attribution of AI agents across platforms, including creators, tools, accessed systems, roles, permissions, runtime activity, and shadow AI.
Zenity provides full inventory and attribution of AI agents across platforms including who created them, what tools they use, and what systems they access. You can drill into user roles, permissions, and runtime activity to track usage and uncover shadow AI.
Zenity claims coverage spans software as a service (SaaS), home-grown agentic platforms, and end-user devices.
Security and governance across all environments - SaaS, home-grown agentic platforms (Cloud), and end-user devices (Endpoint) - with unified visibility, policy control, and threat prevention.
Zenity claims full-stack observability for approved and shadow AI, including inventory, owners, prompts, actions, and runtime activity.
Know which agents exist, who owns them, what they can access, and how they behave across your environment.
Zenity claims intent-based detection examines execution paths, including tool calls, memory access, data usage, and control flow, to identify malicious or unintended outcomes.
By examining the full execution path - including tool calls, memory access, data usage, and control flow - Zenity identifies malicious or unintended outcomes even when inputs look harmless. This intent-focused approach exposes attacks that prompt-based firewalls miss.
Zenity claims it identifies when AI agents access or expose sensitive data and lets teams flag, redact, or block unsafe behavior.
Zenity identifies when AI agents access or expose PHI, PII, PCI, or hardcoded secrets
Zenity claims it monitors step-level agent execution and enforces inline controls to stop unsafe actions.
Monitor step-level agent execution, correlate behavior with context, and enforce inline controls to stop unsafe actions before they impact the business