The shape of the problem
Open the bottom of a router your ISP shipped you. There’s a sticker with a default Wi-Fi network name and a default WPA passphrase. In a meaningful fraction of cases, that passphrase is not actually random — it is derived from data that’s also visible on the air, like the BSSID (MAC address) or the SSID itself. Sometimes there’s also a serial-number component that isn’t on the air, which raises the bar; sometimes there isn’t.
If the derivation function is recoverable, the passphrase becomes a function of public information, and the security of the network reduces from “an attacker needs to crack a strong passphrase” to “an attacker needs to call a function.” That is a substantially different threat model, and it is the threat model some default configurations have actually been in.
This is well-trodden research at this point — the academic and
hobbyist literature has covered specific vendor families in detail for
years, and tools like PSKracker
exist as one-stop implementations of the well-understood families. What
I want to talk about here is the shape of the work, because the
methodology is more transferable than any individual algorithm.
The recurring pattern
The pattern repeats across vendor families with almost-comical consistency:
- A seed visible on the air. Usually BSSID, sometimes SSID, sometimes both. Occasionally combined with something less-visible (serial number from the sticker, manufacture date encoded into the MAC range).
- A derivation function. Sometimes a hash, sometimes a hash truncated to N characters, sometimes a custom mixing function, sometimes a selection-from-charset indexed by hash bytes. Almost always something that looks like it was designed by someone who knew it was a bad idea but went ahead anyway.
- A character set. “Letters and digits, length 10” or similar. Frequently chosen for the readability of the sticker rather than for any cryptographic property.
- Per-firmware-revision drift. The same vendor will sometimes change the function between firmware revisions, leaving a vulnerable window for the older firmware versions until a fleet upgrade rolls out.
Knowing the pattern means you know what to look for the next time you encounter a new vendor family. Knowing it well means you can predict which families are likely to have a derivation function before you’ve even started looking.
Abstract methodology
I have done a few of these from scratch. The methodology I keep coming back to:
- Collect. Acquire a corpus of (BSSID, SSID, passphrase) triples for the target vendor family. The hardest part of the project is almost always this one — you need enough variation to distinguish a real relationship from a coincidence.
- Look for the obvious. Hash the visible identifiers with each common hash function, take the first N characters in each character set, compare. A frightening number of vendor algorithms are literally “SHA-1 of the BSSID, take the first ten hex digits.”
- Slice by firmware. If the obvious doesn’t work corpus-wide, slice by firmware revision. Vendors change algorithms.
- Reverse the actual firmware if it does. Once you suspect there is a derivation function, the binary that ships on the device contains it. This is where Binwalk and Ghidra come in.
- Validate. A candidate algorithm has to predict the passphrase for every triple in your corpus, not just enough of them to be encouraging. The discipline that catches you when you’ve found a coincidence rather than a function is testing against a held-out set.
- Compare to public. Once you have something that validates, check against the public literature for that vendor. If someone has already published the same algorithm, your work is independent confirmation rather than novel disclosure — which is the responsible position to be in.
Why this matters for the defender side
The reason any of this is worth doing as a personal-research line — beyond it being interesting — is that defenders need to know what attackers know. If you are a network operator handing out devices to end users, you need to know whether the firmware you’re shipping has its own default-key algorithm waiting to be reversed. If you are an auditor, you need to know which vendor families’ defaults are already public so you can flag them in field surveys without doing the work again. If you are a researcher, you need to be able to recognize the pattern when it crosses your desk.
I’ve kept a small private collection of from-scratch Python
implementations for the families I’ve worked through, plus a working
knowledge of PSKracker’s coverage of the well-documented families.
The private implementations don’t add anything to the public corpus —
they’re independent confirmations of work others have already done —
but doing them is what built the intuition.
What I won’t write down here
The specific vendor families I’ve worked on personally — and any implementation details that aren’t already in the public literature — stay off this page. The methodology generalizes; novel algorithm disclosure belongs in a coordinated-disclosure track, not on a personal blog.
Closer
“Default credentials are bad” is the kind of advice that has been boring for so long that people stop hearing it. Reversing a default-key algorithm is the visceral version of the same lesson: the only way for a default to be safe is for it to be the output of a real RNG, written down at provision time and recoverable nowhere else. Anything else eventually gets reversed by someone with a corpus and a weekend.