Anatomy of a Footprint Report: Every Risk Label Decoded

A footprint report is the first thing you see after running a digital footprint check on your X (Twitter) archive. It takes years of old tweets and boils them down to one privacy score plus a list of flagged posts. The catch is that most people open the report, see labels like phone, address, or sensitive topic, and have no idea which ones actually matter. This guide breaks down every section of a footprint report and decodes each risk label, so you can decide what to clean instead of guessing.

What a footprint report is actually made of

The report comes straight from your X data export, parsed on your own device. It does not pull anything new from X's servers. Two numbers do most of the work: a 0-100 health score where higher means safer, and a count of flagged tweets grouped by label. Underneath sits the per-tweet list, the part you'll spend real time in. None of it leaves your machine, which is the whole point of a privacy check.

Report sections explained, top to bottom

Read the report in order and you save time. The header shows the score and the total flagged count. The category breakdown groups those flags so you can see at a glance whether your risk is contact info, location, or content. The tweet list is sorted by severity, so the worst posts sit at the top. Last is a filter bar where you can narrow by label, year, or keyword. If you already know what you're hunting for, skip to the filter.

Every risk label decoded

Here is what each label means and roughly how worried you should be:

Risk label	What it catches	Typical risk
Phone	Phone numbers in tweet text or images	High: direct scam and spam entry
Email	Email addresses, including old ones	High: account takeover attempts
Address	Home or workplace addresses	High: real-world safety
Location	Check-ins, city tags, travel posts	Medium: reveals your routine
Sensitive topic	Rants about employers, politics, identity	Medium: hiring and reputation

These labels are guesses from pattern matching, not verdicts. A phone hit on a joke like "call me at 555" is a false positive you can ignore. The address and email hits are the ones to take seriously.

Risk labels on Twitter and why old tweets get flagged

Most posts a footprint report flags are old. Twitter keeps your history indexed for years, and a single 2015 tweet with your old address is still reachable through Google today. That's why the report surfaces tweets you forgot you posted. The risk labels on Twitter are not about what you post now; they're about what has sat public the whole time. A hiring manager or a stranger can read it without you ever knowing.

What to fix first

Start with phone, email, and address labels. Those are the concrete, exploitable ones. Location comes next if you posted a regular routine. Sensitive topic posts matter most when you're job hunting or in a visible role, so weigh them against your situation instead of deleting everything in a panic. Use the filters to batch the genuinely dangerous ones, then reconsider the rest.

Does a footprint report delete anything?

No. The report is read-only. It shows you what's there and scores the risk. Deleting is a separate step you choose, tweet by tweet, and you can stop at any time.

Can I open the report offline?

Yes. Parsing happens on your device, so the report works without a connection. Nothing about it is stored in the cloud.

How accurate are the risk labels?

Good enough to act on, not perfect. Pattern matching catches real phone numbers and addresses reliably, but it also flags joking references. Read each hit before you clean it.

Is my report shared with anyone?

No. The report lives in your browser memory and your local downloads. It is never uploaded, and there is no server copy of your archive.

Want to see your own footprint report? Upload your X archive on the digital-footprint-health.shop homepage and get a privacy score plus a labeled risk list in minutes, all processed on your computer. Your data never leaves the device.