← Palo Alto Networks Prisma AIRS
Palo Alto Networks Prisma AIRS — agentic threat model
Prisma AIRS is a security-focused runtime protection platform and SDK rather than an autonomous agent, presenting low inherent agentic risk but holding high systemic risk as a critical security control point for enterprise AI workflows.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.30 | |
| Non-Determinism | 0.20 | |
| Opacity & Reflexivity | 0.30 |
Scored with the canonical OWASP AIVSS formula (AIVSS calculator reference); agentic risk factors estimated from the agent’s described capabilities.
MAESTRO 7-layer threat model
Per-layer threats for this agent. Layers tagged “not certain from listing” are general, caveated commentary where the public description didn’t pin that layer.
Not certain from the listing — The listing does not specify which foundation models Prisma AIRS itself uses (if any) to perform threat detection, though it secures other models against adversarial examples and prompt injection.
Not certain from the listing — While it prevents data leakage and memory poisoning, the listing does not detail Prisma AIRS's own training data, vector stores, or data operations.
Prisma AIRS provides a Python SDK and integrates with the Model Context Protocol (MCP) Server to secure agent frameworks against tool misuse, memory poisoning, and insecure integrations.
Not certain from the listing — It is a SaaS-based platform with SDK integration, designed to run in production environments, but specific sandboxing or hosting infrastructure details of the SaaS itself are not detailed.
Acts as a runtime security and threat detection layer, integrating with enterprise SecOps platforms to monitor, log, and prevent prompt injection, malicious code, and data leakage.
It is a dedicated security platform designed to harden AI agents, detect malicious URLs, and prevent tool misuse, serving as a core security control for enterprise AI compliance.
Secures agentic workflows and multi-agent environments via the Prisma AIRS MCP Server, protecting against cascading failures and rogue agent behaviors in production.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology. Are you the vendor? Factual corrections are free.