Agent-to-agent communication security
Proofpoint materials reviewed did not provide a public claim for trust or policy enforcement between agents.
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 181–200 of 1280 evidence records
Proofpoint materials reviewed did not provide a public claim for trust or policy enforcement between agents.
Proofpoint materials reviewed did not provide a public claim for non-human identity, service-account, secret, or workload credential lifecycle controls.
Proofpoint claims Model Context Protocol (MCP) authentication and approved-server registry controls but does not establish full agent identity lifecycle management.
maintains a registry of approved servers
Proofpoint materials reviewed did not provide a public claim for coding-agent, integrated development environment (IDE), CLI, workstation, skill, hook, or package-action governance.
Securiti claims an AI model catalog that includes shadow AI.
Catalog AI models for full visibility, including shadow AI
Securiti claims discovery and cataloging of AI models across public cloud, private cloud, software as a service (SaaS), and internal projects.
Discover and catalog AI models in use across public clouds, private clouds, and SaaS applications.
Securiti claims collection of model details from software as a service (SaaS) and internal AI projects.
Collect AI model details from SaaS and internal projects
Securiti claims controls over enterprise use of data and AI.
Establish controls on use of data and AI.
Securiti claims mapping and monitoring of data sources, processing, risks, obligations, and data flows connected to AI models.
Map AI models to data sources, monitor data flow
Securiti AI materials reviewed did not provide a public claim for browser or software as a service (SaaS)-session controls for employee AI use.
Securiti claims controls that mitigate AI risks described by OWASP's large language model (LLM) risk categories and NIST adversarial machine-learning attacks.
Mitigate AI security risks such as OWASP top 10 issues for LLMs and NIST Adversarial Machine Learning Attacks.
Securiti claims assessments and automated compliance checks mapped to NIST AI RMF, the EU AI Act, and more than twenty regulations.
Conduct assessments to comply with standards such as NIST AI RMF, EU AI Act, and more than twenty other regulations.
Securiti AI materials reviewed did not provide a public claim for adversarial testing or release assurance for AI systems.
Securiti AI materials reviewed did not provide a public claim for model and AI component supply-chain inspection.
Securiti AI materials reviewed did not provide a public claim for inline model, agent, tool, application programming interface (API), or Model Context Protocol (MCP) policy enforcement.
Veeam and Securiti claim Agent Commander can discover shadow agents and provide visibility into data-use risk.
Bring unsanctioned agents under governance with visibility into data use risk.
Securiti AI materials reviewed did not provide a public claim for trust or policy enforcement between agents.
Securiti AI materials reviewed did not provide a public claim for non-human identity, service-account, secret, or workload credential lifecycle controls.
Securiti AI materials reviewed did not provide a public claim for agent registration, delegated authorization, task-scoped access, and revocation.
Securiti AI materials reviewed did not provide a public claim for coding-agent, integrated development environment (IDE), CLI, workstation, skill, hook, or package-action governance.