Sluqe — agentic threat model
Sluqe presents a high data confidentiality risk due to its role as a centralized repository for sensitive voice recordings and meeting transcripts, though its low operational autonomy limits its ability to cause direct physical or transactional harm.
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 | 0.80 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.50 | |
| 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 — Sluqe likely utilizes third-party speech-to-text and LLM APIs for transcription and Q&A. Threats include prompt injection via transcribed audio to bypass guardrails or leak historical transcripts.
Sluqe relies heavily on a vector database to store and retrieve months of voice transcripts. Threats include RAG/knowledge-base poisoning (injecting malicious transcripts to alter future query results) and unauthorized data exfiltration of sensitive meeting details.
Orchestrates transcription, summarization, and RAG-based Q&A. Threats include memory poisoning where malicious spoken content in a recording manipulates the agent's context or behavior during subsequent queries.
Not certain from the listing — Sluqe is a closed-source SaaS platform. Threats include insecure storage of raw audio recordings and transcripts, and lack of tenant isolation in the cloud hosting environment.
Not certain from the listing — No details on evaluation or observability are provided. Gaps here could lead to undetected drift in transcription accuracy or silent failures in action item extraction.
Not certain from the listing — The listing claims a 'secure voice-to-knowledge pipeline' but lacks details on encryption (at rest/in transit), access controls, or compliance certifications (e.g., SOC 2, GDPR) for sensitive voice data.
Sluqe operates as a standalone horizontal tool with no mentioned multi-agent or marketplace integrations, minimizing ecosystem-level threats.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).