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August 5, 2026

How I Bypassed Authentication on a Fintech Platform Using a Broken Password Reset Flow (Bug Bounty…

I almost closed the tab on this program twice.

By T4nv1

5 min read

It was a fintech company running a private bug bounty on a well-known platform, decent bounty range, moderate scope, nothing that screamed "easy win." I'd spent about four hours poking at the usual suspects — IDORs on account endpoints, some half-hearted rate limit testing, a couple of stored XSS attempts that got sanitized before they even landed. Standard Tuesday.

Then I looked at the password reset flow. Nobody ever looks hard enough at the password reset flow.

Setting the Scene

The target I'll call it FinFlow here, since the program's disclosure policy doesn't allow naming them directly is a personal finance app that lets users link bank accounts and track spending. Auth was handled through a fairly standard email + password login, with a "Forgot Password" flow that sent a reset link to the user's inbox.

On the surface, everything looked fine. HTTPS everywhere, decent CSP headers, no obvious SQLi in the login form. The kind of app that makes you think the low-hanging fruit is gone.

But the reset flow caught my eye because of one small detail: the reset link arrived almost instantly. Not suspicious on its own — but it made me want to see what was actually inside that link.

Digging Into the Reset Token

I triggered a password reset on my own test account and grabbed the link:

https://app.finflow-example.com/reset-password?token=6c9d2f1a-000e-4e3b-93a5-2f1b8e7a1c02&uid=48213

Two parameters stood out immediately: token and uid. The token looked like a proper UUID — random enough at a glance. But the uid parameter was just a plain, sequential integer tied directly to the user's account ID.

That's the first smell. If the backend is trusting uid as a value the client controls, and only "validating" against a token, the real question becomes: how strong is that token check, actually?

I requested five more resets in a row for my own account and logged every token:

6c9d2f1a-000e-4e3b-93a5-2f1b8e7a1c02
6c9d2f1a-000f-4e3b-93a5-2f1b8e7a1c03
6c9d2f1a-0010-4e3b-93a5-2f1b8e7a1c04
6c9d2f1a-0011-4e3b-93a5-2f1b8e7a1c05
6c9d2f1a-0012-4e3b-93a5-2f1b8e7a1c06

That is not random. That is a counter dressed up as a UUID. The first and last segments were static per user session, and the middle segment was incrementing by one on every request. Whatever "randomness" existed was cosmetic the actual entropy was somewhere between 12 and 16 bits, which is nothing.

Turning a Pattern Into a Bypass

Predictable tokens are interesting, but the real question in any bug bounty program is: can I actually do something with this? A cute pattern in a token doesn't matter to a triager unless you can demonstrate real account takeover.

So I set up a small script to:

  1. Trigger a password reset for a target account (a second test account I controlled, simulating a victim)
  2. Grab the timestamp of the request
  3. Generate a range of plausible tokens based on the pattern I'd already mapped, scoped to a tight time window around that timestamp
  4. Fire each candidate token against the reset endpoint with the victim's uid

Because the backend was validating uid and token as two separate checks — rather than binding the token cryptographically to the account and expiring it hard after one use — the increment pattern meant a resourceful attacker didn't need brute force at internet scale. They needed maybe a few hundred requests, sent quickly, right after triggering a reset for a known victim's email.

On attempt 61, I got a 200 OK and a fresh session cookie for the victim account.

Full account takeover. No password required. Just an email address I already knew (which, for a lot of these programs, is trivial to obtain — most sites happily confirm whether an email is registered).

Why This Matters More Than a Typical IDOR

The reason this bug is worth writing up isn't the mechanism predictable tokens are a known class of bug, it's practically a rite of passage in appsec write-ups. It's where it lived. This wasn't a low-value internal admin panel. This was the front door to a user's linked bank accounts and transaction history.

A few things made the impact worse than a garden-variety token predictability bug:

  • No rate limiting on the reset-verification endpoint, so the guessing window wasn't meaningfully constrained
  • No token expiry enforcement beyond a generous 30-minute window, giving plenty of room to brute-force the pattern
  • No re-authentication step for sensitive actions after a password reset meaning the new session had immediate access to linked bank data, not just profile settings

Individually, none of these are catastrophic. Stacked together, they turned a "meh, weak token" finding into a full account takeover chain with real financial data exposure.

Writing the Report

If there's one thing that separates a bounty that gets triaged fast from one that sits in the queue for three weeks, it's the quality of the reproduction steps. I included:

  • A clear timeline of requests with raw HTTP traffic (sanitized of any real account data)
  • The token samples showing the pattern, annotated segment by segment
  • A proof-of-concept video showing the full takeover against my own two test accounts, start to finish, under two minutes
  • A suggested fix: bind tokens to accounts using a cryptographically random value with sufficient entropy (128 bits, not a disguised counter), enforce single-use invalidation immediately after a successful reset, and rate-limit the reset-verification endpoint aggressively

I also flagged the missing re-authentication step for linking/viewing bank data post-reset as a secondary finding, since it materially increased the blast radius of the primary bug.

The Outcome

The triager confirmed the issue within a day, which is honestly rare — most programs take longer just to reproduce something like this. The fix shipped about two weeks later: proper cryptographically secure tokens, single-use enforcement, and a rate limit on the verification endpoint. They also added a step requiring re-entry of a fresh OTP before any bank account data could be viewed post-reset, which closed the secondary issue too.

The bounty came in solidly in the "critical" tier for the program, which felt right given the actual reachable impact — this wasn't theoretical, it was a working account takeover against financial data with almost no technical barrier once the pattern was understood.

Lessons for Anyone Hunting Auth Flows

A few things I keep coming back to after this one:

  • Trust nothing that "looks" random. A UUID-shaped string is not proof of entropy. Request the same flow multiple times in a row and diff the outputs before assuming anything is secure.
  • Password reset and account recovery flows deserve more attention than they get. Everyone hammers login forms and search bars; recovery flows are often built later, by different engineers, under less scrutiny.
  • Chain small issues together. No single piece of this bug was novel. The value was in recognizing how a weak token, missing rate limits, and no post-reset re-auth combined into something serious.
  • Document like someone else has to reproduce it cold. The gap between a "maybe" and a fast critical-tier payout is almost always report quality, not just the bug itself.

If you're getting into bug bounty hunting, don't skip the boring parts of an application. The login page gets all the attention. The "forgot password" link three clicks away is often where the real bugs are waiting.

Have you found something similar in a password reset or account recovery flow? I'd genuinely like to hear about it — drop a note in the comments.