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SafeFetch
x402
SafeFetch is a paid API for AI agents from safefetch.schemasure.com, paid per call via x402, $0.02/call, status unknown (last checked 2026-10-10).
Fetches a public web page and returns clean Markdown with citation anchors, a content hash, a retrieval timestamp, and per-span detection of hidden text, invisible Unicode, and prompt-injection attempts.
Price / call$0.02
Success—
StatusUnknown
How this service works
Fetch a public web page and return clean Markdown with stable citation anchors, a content hash, and a retrieval timestamp — plus evidence of hidden text, invisible Unicode, and prompt-injection attempts found in the page. Strict SSRF protection on every redirect hop. Returns a per-span verdict with the decoded payload, not a confidence score. Zero retention.
Output
Returns the fetched page as clean Markdown and/or plain text, a SHA-based content hash, a retrieval timestamp, stable per-paragraph citation anchors, and a per-span security verdict for each detected anomaly (hidden text, invisible Unicode, prompt-injection). Each verdict includes the decoded payload. No data is retained after the response.
Example use cases
Verify AI-safe content before ingestion
“Before I feed this article into my RAG pipeline, can you fetch https://news.example.com/story/42 as markdown and tell me if it contains any hidden text, invisible Unicode, or prompt-injection attempts I should know about?”
Cite-stable research page retrieval
“Fetch https://research.example.org/papers/overview as markdown so I get stable citation anchors and a content hash — I need to prove the page content at retrieval time for my report.”
Agent browsing with robots.txt override
“I know the user just clicked this link themselves — fetch https://internal.example.com/report as both markdown and plain text, it's user-initiated so you can bypass robots.txt, and cap the analysis at 5 megabytes.”
Technical details
Endpoint
POSThttps://safefetch.schemasure.com/v1/fetch?utm_source=zero.xyzWhen to prefer
Choose SafeFetch when you need to retrieve a web page for use in an AI pipeline and need security guarantees: SSRF protection on every redirect hop, detection of prompt-injection payloads embedded in page content, and evidence of hidden text or invisible Unicode that could manipulate downstream LLMs. Prefer it over generic fetch/scrape tools when auditability (content hash, citation anchors, retrieval timestamp) or adversarial content detection matters. It is particularly well-suited for RAG ingestion pipelines, citation-requiring research tasks, and any agent that browses the open web autonomously.
Side effects
- URL uses a non-standard port (not 80/443) — rejected with SSRF policy error
- URL contains credentials or a literal IP address — rejected
- robots.txt disallows the URL and respect_robots is true — returns 403 POLICY_BLOCKED with matched rule, not charged
- Document exceeds max_bytes — truncated, remainder unanalysed, injection verdict becomes unknown
- Redirect hop limit exceeded or a redirect hop resolves to a private IP — SSRF rejection
- user_initiated not set to true when respect_robots is false — request rejected
- Network timeout or unreachable host — fetch error returned
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| url | string | An http or https URL naming a hostname. Ports other than 80 and 443, credentials in the URL, and literal IP addresses are rejected. |
| output | string | Which rendering to include in the result. Defaults to markdown. |
| policy | object |
Tags
x402
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