RecentFollowed — agentic threat model
RecentFollowed is a low-risk, single-purpose utility for scraping public Instagram data with minimal to no agentic capabilities, presenting negligible risk of autonomous harm or lateral escalation.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.00 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.10 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.10 | |
| Opacity & Reflexivity | 0.10 |
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 — The tool likely relies on traditional web scraping scripts rather than foundation models, meaning typical LLM threats like prompt injection or model poisoning are likely non-applicable.
Not certain from the listing — The application processes real-time public Instagram data on demand. Primary threats involve data ingestion integrity, scraping blocks, or potential downstream parsing vulnerabilities if Instagram returns unexpected payloads.
Not certain from the listing — There is no evidence of an agentic orchestration framework (e.g., LangChain). The tool functions as a direct query-and-response utility, minimizing tool-misuse risks.
Not certain from the listing — Hosted as a web application. Infrastructure risks include IP blocklisting by Meta, proxy pool exhaustion, and standard web application vulnerabilities (e.g., SSRF or XSS in the UI).
Not certain from the listing — No observability or guardrail mechanisms are mentioned. Monitoring is likely limited to basic web traffic logging and scraping success rates.
Not certain from the listing — The tool requires no login or account, which eliminates credential theft risks but exposes the service to automated abuse, scraping rate-limit bypasses, and potential terms-of-service violations.
Not certain from the listing — The tool operates in isolation with no multi-agent or ecosystem integrations described.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).