Puch AI — agentic threat model
Puch AI is a consumer-focused WhatsApp assistant with low direct system autonomy but high public exposure. Its primary risks stem from prompt injection, potential generation of harmful or bypass-enabled media (images/videos), and the abuse of its 'Fact Check' feature to spread validated misinformation.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.40 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.70 | |
| 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 utilizes external foundation models for text, image, and video generation. Threats include prompt injection via WhatsApp chat, jailbreaks to bypass safety filters for image/video generation, and generating misaligned or toxic outputs.
Not certain from the listing — requires data ingestion for real-time news, weather, and fact-checking. Threats include data poisoning of the fact-checking reference sources and potential exposure of user chat logs or phone numbers stored in backend databases.
Not certain from the listing — orchestrates multiple tools (image/video generation, voice synthesis, web search). Threats include insecure tool integration, such as SSRF or remote code execution if input sanitization is bypassed during tool invocation.
Not certain from the listing — hosted on cloud infrastructure and integrated with the WhatsApp Business API. Threats include exposure of WhatsApp API credentials, lack of sandboxing for media processing, and denial of service via message flooding.
Not certain from the listing — no guardrails or observability mechanisms are detailed. Threats include blind spots to abusive users leveraging the bot to generate and distribute deepfakes or misinformation at scale.
Not certain from the listing — no compliance frameworks (such as GDPR or India's DPDP Act) are cited. Threats include regulatory non-compliance regarding the processing and retention of personal data (phone numbers, voice notes, and chat histories) on WhatsApp.
Not certain from the listing — operates as a standalone consumer assistant. Threats are primarily limited to upstream dependency failures (e.g., third-party image/video generation APIs going offline or being compromised).
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).