Fetch a URL via HTTP/HTTPS and return the response body as text. Lightweight entrypoint replacement for `sub-agent` steps whose only job is a single GET/POST. Supports GET (default), POST/PUT/DELETE with a stdin-piped body, configurable timeout, and a max-bytes cap — no LLM agent loop, no custom-header injection (request goes out with urllib defaults). Use for simple data-fetch steps in meta-skill DAGs; for crawling, JS-rendered pages, or complex auth chains use sub-agent + scrapling instead.
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Low
Low-risk findings worth noting
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Source text exposure occurs when the required workflow passes an outsider-provided `url` (and optional stdin `body`) into `scripts/http_fetch.py`, which fetches the remote response and prints it on stdout for downstream LLM ingestion.
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