PagerGPT — agentic threat model
PagerGPT presents a moderate-to-high risk profile due to its integration with internal communication channels (Slack, Teams) and its reliance on user-ingested RAG data, which is susceptible to indirect prompt injection and data poisoning.
OWASP AIVSS score rationale
| Autonomy of Action | 0.50 | |
| Goal-Driven Planning | 0.30 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.40 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.20 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.60 | |
| Opacity & Reflexivity | 0.50 |
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 — likely relies on OpenAI's GPT models ('ChatGPT-powered'). Threats include prompt injection, adversarial inputs bypassing system prompts, and model misalignment leading to inappropriate customer-facing outputs.
RAG-powered training via URLs, uploaded documents, and knowledge bases. Highly vulnerable to data/knowledge-base poisoning if malicious documents or compromised URLs are ingested, leading to indirect prompt injection.
Not certain from the listing — uses a proprietary no-code orchestration framework. Vulnerabilities include insecure tool integration with Slack/Teams and potential memory/state poisoning during live chat sessions.
Not certain from the listing — hosted cloud platform. Threats include container compromise, insecure API endpoints for integrations, and lack of sandboxing for document parsing/ingestion.
Provides 'advanced analytics to track performance' and a 'shared live chat inbox' for human monitoring. However, lacks explicit automated guardrails or real-time drift/anomaly detection for LLM outputs.
Not certain from the listing — no explicit mentions of SOC2, ISO, or enterprise RBAC. Risks include unauthorized access to the bot configuration dashboard and lack of data privacy compliance (GDPR/CCPA) for ingested customer data.
Integrates with Slack, WhatsApp, and Teams. Risks include horizontal escalation where a compromised bot posts malicious links or commands into internal corporate Slack/Teams channels.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).