Smallppt — agentic threat model

Not certain from the listing — the specific underlying LLMs or multimodal models used for slide generation and chat are not disclosed, leaving them potentially vulnerable to prompt injection, adversarial inputs via uploaded documents, or model-reprogramming attacks.

The agent processes diverse user inputs including TXT, DOCX, PDF, URLs, and audio. This introduces significant risks of malicious file parsing exploits (e.g., buffer overflows in PDF/DOCX parsers), data exfiltration, and SSRF when fetching external URLs.

Not certain from the listing — the orchestration framework for converting text/files to structured slides is proprietary, presenting risks of insecure tool integration or prompt injection during the parsing and summarization phases.

Not certain from the listing — the hosting environment, sandboxing of file conversion tools (PDF/DOCX parsers), and network isolation are undisclosed, raising concerns about container compromise or SSRF via URL ingestion.

Not certain from the listing — there is no mention of guardrails, input/output filtering, or continuous monitoring to detect malicious payloads in uploaded files or generated slide content.

Not certain from the listing — compliance certifications (e.g., SOC 2, GDPR) and access control mechanisms for the 'Team Edition' collaborative features are not detailed, presenting risks of unauthorized data access.

The 'Team Edition' enables real-time collaboration among multiple users, which introduces risks of horizontal privilege escalation, unauthorized sharing of generated assets, or collaborative workspace compromise.