Physical and OSINT
Walk through the door and build the story that gets you there, using only public data.
What you will learn
- -Describe common physical intrusion techniques like tailgating
- -Explain how badge cloning works at a conceptual level
- -Run an OSINT sweep to feed a credible pretext
Not every attack arrives over the wire. Sometimes the fastest path to a room is a friendly face at the front door. Physical social engineering and open source intelligence (OSINT) are the two halves of getting inside a building: one is the entry, the other is the homework that makes the entry look routine.
Getting through the door
Physical operators rely on human courtesy far more than on lock picks:
- Tailgating: follow an authorized employee through a door before it closes. Carry a coffee in each hand and someone will hold it open for you.
- Piggybacking: the same, but the employee actively lets you in after a word.
- Pretext props: a hi-vis vest, a clipboard, a laptop bag, and a lanyard read as "belongs here" to almost everyone.
- Impersonation: pose as a delivery driver, an auditor, or the fire inspector.
The defense you are testing is whether staff challenge a stranger. Most will not, which is exactly the finding a report needs to change behavior.
Badge cloning, at a glance
Many offices use low-frequency 125 kHz proximity cards (like HID Prox) that were never designed to be secure. They broadcast a static ID with no . A long-range reader hidden in a bag can capture that ID from a badge in someone's pocket, and a cheap tool can then replay it.
$proxmark3 /dev/ttyACM0$lf search$lf hid readModern 13.56 MHz smart cards (like DESFire) support real cryptographic authentication. Plenty of buildings never upgraded from the old 125 kHz prox cards, so the ID is trivial to read and clone. If your assessment finds prox cards in use, the fix is a card technology migration, not a memo.
OSINT: the homework
Before any of that, you research. OSINT is intelligence gathered from public sources, and it is what makes a pretext land. Names, org charts, badge photos, email formats, and even the type of coffee in the lobby all come from open data.
$theHarvester -d targetcorp.com -b bing$whois targetcorp.com$exiftool company-brochure.pdfPair those with LinkedIn for the org chart, the company's own site for the email
format (first.last@ versus flast@), and image search for what real badges look
like. Every detail you collect is one less thing the target has to take on faith.
theHarvester returns j.smith@targetcorp.com and a.patel@targetcorp.com. What is the likely email format, and what would you guess for an employee named Maria Gomez?
The format is first-initial dot last name. Maria Gomez would likely be m.gomez@targetcorp.com. Confirm before relying on it, but this is enough to seed a spear phishing list.
Why is tailgating so effective against most offices?