Upwind claims it identifies shadow AI usage and unauthorized model network communications in cloud environments.
Identification of shadow AI usage and unauthorized model network communications
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.
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Evidence records1280
Source checked863
Needs verification0
Source captured0
No supporting claim found411
Excluded from evidence6
Showing 1–16 of 16 evidence records
Clear all filtersUpwind materials reviewed did not provide a public claim for embedded AI discovery across the business-application environment.
No quoted source text is recorded for this claim.
Upwind claims its AI bill of materials (AI-BOM) inventories models, agent frameworks, libraries, vector stores, cloud AI services, and runtime dependencies.
unified inventory that connects all layers of the AI stack
Upwind materials reviewed did not provide a public claim for policy enforcement over unapproved AI use.
No quoted source text is recorded for this claim.
Upwind claims real-time detection of sensitive data in prompts and inference payloads traversing cloud networks.
Real-time detection of sensitive data in prompts and inference payloads
Upwind materials reviewed did not provide a public claim for browser or software as a service (SaaS)-session controls for employee AI use.
No quoted source text is recorded for this claim.
Upwind claims AI application testing for prompt injection, jailbreaks, unsafe tool bindings, and hallucination-driven data exposure.
Prompt injection and jailbreak testing
Upwind claims model version, lineage, audit-trail, and posture controls for cloud AI services.
maintain lineage, and enforce audit trails
Upwind claims AI-specific security testing before deployment and continuously as models evolve.
identify weaknesses before deployment, and continuously as models evolve
Upwind claims an AI bill of materials (AI-BOM) correlating code, cloud, model registries, agent systems, AI components, and runtime dependencies.
Correlation with runtime evidence to reveal real dependencies
Upwind claims Model Context Protocol (MCP) runtime tracing of prompts, decision chains, tool calls, file actions, application programming interfaces (APIs), and cloud interactions.
MCP Security brings agentic visibility to runtime by tracing AI-driven actions end-to-end.
Upwind claims end-to-end runtime observation of agent prompts, decisions, tool invocations, file actions, application programming interface (API) calls, and system changes.
Observation of tool invocation and agent function calls
Upwind materials reviewed did not provide a public claim for trust or policy enforcement between agents.
No quoted source text is recorded for this claim.
Upwind claims discovery of AI application programming interface (API) keys and secrets plus detection of overly permissive identity and access management (IAM) roles used by AI services.
Automatically discover AI API keys and ensure they are not exposed.
Upwind materials reviewed did not provide a public claim for agent registration, delegated authorization, task-scoped access, and revocation.
No quoted source text is recorded for this claim.
Upwind materials reviewed did not provide a public claim for coding-agent, integrated development environment (IDE), CLI, workstation, skill, hook, or package-action governance.
No quoted source text is recorded for this claim.