BlissBot — agentic threat model
BlissBot is a conversational AI companion for mental and emotional health. Its primary security risks stem from the highly sensitive nature of the personal health information (PHI) it processes and the potential for unsafe or unaligned mental health advice if the underlying model is compromised or bypassed.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.70 | |
| Opacity & Reflexivity | 0.60 |
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 third-party or open-source LLMs. The primary threat is prompt injection or jailbreaking that could bypass safety guardrails, leading the bot to provide harmful, toxic, or medically unsafe mental health advice.
Not certain from the listing — likely stores highly sensitive user chat histories and emotional state logs. Threats include unauthorized data exfiltration, lack of encryption at rest/in transit for conversational logs, and potential privacy leaks.
Not certain from the listing — likely uses a simple conversational agent framework. Threats include insecure session state management and memory poisoning if the bot retains harmful user inputs across a session.
Not certain from the listing — deployed as a 24/7 support app. Vulnerable to standard cloud infrastructure threats, API abuse, and unauthorized access to backend databases containing user profiles.
Not certain from the listing — no mention of real-time monitoring or safety guardrails. A lack of robust crisis-detection guardrails (e.g., failing to detect self-harm intent) represents a critical safety gap.
Not certain from the listing — claims 'Secure Privacy Protection' but lacks explicit mention of healthcare-specific compliance frameworks (such as HIPAA or GDPR) necessary for handling sensitive mental health data.
Not certain from the listing — appears to operate as a standalone horizontal application with no multi-agent or ecosystem integrations described.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).