How to Extract HTTP Headers From a Raw Request or curl Dump

Most of the time a header lives inside a wall of other text. You run curl -v, you copy a block out of the browser network panel, or someone pastes a full response into a ticket. The headers you actually care about are buried between a request line, a status line, a body, and a pile of timing and TLS noise. Reading them by eye is slow, and copying them one at a time is error-prone.

The job here is small and specific: take that raw dump and turn it into a clean list of Key: Value pairs you can read, copy, or diff. That is exactly what the HTTP Header Extractor does, and it does it without sending your text anywhere.

What the extractor actually does

The tool runs a browser-side parser over whatever you paste or drop in. It scans for Name: value header lines and pulls only those out. The request line, the status line, the response body, and the prose around them get dropped. What you get back is a deduplicated list where each header is one clean row, with the original line number, a normalized value, a validity flag, and a reason when something looks off.

That last part matters more than it sounds. Real captures are messy. A header line with no colon, a Cache-Control value that wrapped onto the next row, an empty header name — the parser keeps those rows and tells you why they are flagged, so you can go back and patch the source instead of silently losing data.

Because everything happens locally, there is no upload step. You can paste a production response that contains a Set-Cookie or an Authorization value and nothing leaves the page. Sensitive value types like tokens and card numbers get masked in the output while you still keep the validation signal.

A worked example: a raw response reduced to its headers

Here is a response the way it lands in your terminal after curl -i:

HTTP/1.1 200 OK
Date: Fri, 13 Jun 2026 09:14:22 GMT
Content-Type: application/json; charset=utf-8
Content-Length: 1182
Cache-Control: public, max-age=300
ETag: "9b2c4f-4a"
Vary: Accept-Encoding
X-Request-Id: 7f3a9c01-22de-4b8a-9f10-1c2e

{"id":42,"name":"Toolora","ok":true}

Paste that in and the status line and the JSON body fall away. What stays is just the headers, one per row:

Date: Fri, 13 Jun 2026 09:14:22 GMT
Content-Type: application/json; charset=utf-8
Content-Length: 1182
Cache-Control: public, max-age=300
ETag: "9b2c4f-4a"
Vary: Accept-Encoding
X-Request-Id: 7f3a9c01-22de-4b8a-9f10-1c2e

Seven clean pairs, ready to read. The 200 OK status line is gone, the body is gone, and the colon inside the Date value did not trick the parser into splitting it in the wrong place. From there you can sort the list, keep only unique rows, or switch the output format.

Three jobs this is built for

Documenting an API. When you write reference docs, you want the exact headers a real call returns, not a hand-typed approximation. Run the call, capture the response, extract the headers, and paste the clean block straight into your doc. No retyping, no missed Vary header, no guessing at the casing.

Diffing two responses. This is where the clean list pays off. Capture a response from staging and one from production, extract the headers from each, and put the two lists side by side. Because every header is normalized into the same Key: Value shape and the lists are sorted, a real difference — a missing Strict-Transport-Security, a Cache-Control that says no-store on one side and max-age=300 on the other — jumps out instead of hiding inside formatting noise.

Debugging. When a request misbehaves, the headers usually hold the answer. Pull the headers out of a curl -v trace, line them up against what the docs promise, and the mismatch is right there: a wrong Content-Type, a stale Authorization, a Host that does not match. Having the line numbers preserved means you can jump back to the raw capture to confirm context.

Why local processing is the right default

I spend a lot of my debugging time inside responses that I would never paste into a random web form. Real captures carry session cookies, bearer tokens, internal request IDs, and customer identifiers. A tool that ships that text to a server to "process" it is a tool I cannot use at work. So the extractor parses everything in the browser with the File API and plain string work — paste a response, drop a .log file, and the bytes stay on your machine. That single design choice is what makes it safe to point at production traffic instead of a sanitized sample.

It also keeps things fast. There is no round trip, so a few requests' worth of headers come back instantly. The practical ceiling is the size of a normal paste, well under a megabyte. For a full access-log archive, slice the header lines out locally first, then extract.

Tips for cleaner output

A few habits make the result tidier:

• Normalize before you dedupe. Text copied from a browser or a PDF often carries hidden whitespace, so two headers that look identical can read as different rows until you normalize them.
• Keep the invalid rows on screen while you are cleaning a capture. They point straight at the broken lines in your source.
• When you need an audit trail, download CSV or Markdown with the line numbers rather than copying only the final block. The line numbers are what let a reviewer trace each header back to the raw dump.

Once you have a clean list, you rarely stop there. If you need the same headers as a JSON object, a SQL IN clause, or a TypeScript union, hand the list to the HTTP Header List Converter and skip the manual quoting and comma-wrangling entirely.

Extracting headers is one of those tasks that feels too small to deserve a tool until you have done it badly fifty times. Pulling each header into a clean pair, separating it from the body and the status line, and keeping the whole thing local turns a fiddly copy-paste chore into something you stop thinking about.

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Made by Toolora · Updated 2026-06-13