csv-url-parser (FeedMob) — agentic threat model

Not certain from the listing — the agent's core logic of parsing URLs and rewriting CSVs is highly deterministic and may not heavily rely on a complex LLM, but if an LLM is used to guide the extraction, it is susceptible to prompt injection via malicious URLs embedded in the CSV.

The agent directly reads, processes, and rewrites CSV files. The primary threat is data poisoning or injection attacks where malformed URLs or CSV payloads exploit the parser, potentially leading to denial of service or path traversal if file-writing paths are derived from input data.

The agent possesses a 'file-rewriting skill'. Insecure tool integration or lack of input validation on the CSV source path and destination could allow an attacker to overwrite critical system files or access unauthorized directories.

Not certain from the listing — the hosting environment, sandboxing of the file-writing execution, and directory permissions are unspecified. If run without strict containerization, file-writing capabilities pose a host compromise risk.

Not certain from the listing — there is no mention of logging, input validation guardrails, or anomaly detection to monitor the volume or safety of the files being processed and rewritten.

Not certain from the listing — no authentication, authorization, or access control policies are defined to restrict who can invoke this parser or which directories it is permitted to read and write.

As a FeedMob skill plugin, this agent is designed to be integrated into a larger ecosystem. A compromised upstream agent could abuse this tool to overwrite files, or this agent could pass tainted parsed data to downstream agents.