Healthtech bundles deserve paranoid verification
Patient-facing apps ship the same JS risks at higher stakes. Privacy model front-loaded: GET-only, masks, salted fingerprints.
Your stack, your exposures
Healthtech frontends integrate EHR APIs, notification providers, telephony, analytics — under obligations making “we didn’t know” indefensible.
The three leaks we keep finding here
EHR tokens in intake widgets
Third-party form builders initialized with broad-scope tokens to save an integration ticket.
Notification provider keys
Appointment-reminder systems wired client-side during rollout sprints.
Analytics configs
Session-replay tools receiving identifiers they should never see because config lived client-side.
The check, time-boxed
Set aside ten minutes and run the audit yourself before trusting anyone’s dashboard, ours included:
- Open the deployed site in a browser you do not usually use, logged out.
- View source, then search the built JavaScript for
eyJ— any hit is a JWT; decode its payload and read the role claim before reacting. - Repeat for provider prefixes:
sk_live_,sk-proj-,sk-ant-,AKIA,xoxb-,SG.,whsec_. - Search for connection schemes —
postgres://,postgresql://,mongodb+srv://— and for-----BEGIN PRIVATE KEY-----. - For every hit, classify: public-by-design (anon keys, publishable keys, Firebase web keys) or genuinely secret. Only the second category is an incident.
That routine works, with two caveats: it only covers what the landing page loads unless you chase route-manifest chunks yourself, and it says nothing about yesterday’s deploy. Automation exists precisely because the check decays.
After the first scan
Our privacy model leads here because trust precedes features: GET-only fetching, SSRF-hardened, masks plus salted fingerprints, no stored live values.
Boundaries, stated plainly
KeyDrift scans deployed web artifacts — URLs and pasted bundle source. It does not scan mobile binaries, private networks, or repositories; code behind a login is covered by paste mode, and runtime-assembled keys are outside every bundle scanner’s honest reach.
Why this failure class persists
Zoom out and the pattern is bigger than one repo. AI-assisted output has outgrown review capacity everywhere at once, which means thousands of teams are making the same reasonable-looking tradeoffs in the same week. Nobody using modern tooling is uniquely exposed. The failure mode documented above is the modal outcome of velocity without verification, not evidence of carelessness.
How KeyDrift reports this exact finding
Report anatomy matters during incidents, so it is worth reading once calmly: masked string (never the live value — it ceases to exist outside the detection engine), salted fingerprint (trackable within your workspace, useless to strangers), chunk path (your starting point for a "git log -S" hunt), disposition (secret versus public-by-design), confidence (matches below 0.5 never reach the page at all).
Manual check, step by step
The full manual drill, for readers who want zero dependence on any tool: open the deployed site in a private window; launch DevTools → Sources; use Search-all-files (Ctrl/Cmd+Shift+F) for eyJ; then repeat for the other marker families — eyJ, sk_live_, sk-proj-, AKIA, postgres, BEGIN PRIVATE KEY. Decode anything JWT-shaped before reacting, and classify public-by-design formats as expected guests rather than intruders.
Close the loop with monitoring
If you take one operational step from this page, make it this: put the URL under continuous monitoring (free tier covers one project daily). The first scan tells you whether you have a problem today; the schedule tells you whether the problem comes back next month after someone re-adds the convenient line.
What the plans change
- Free $0 — 1 project · daily scans · email alerts · findings always visible.
- Indie $29/mo — 3 projects · hourly · Slack added · 80 chunks per scan.
- Team $89/mo — 15 projects · every 15 minutes · Discord + webhooks · 150 chunks.
- Growth — from $249/mo, quoted display-only until checkout ships.
The constant across every tier: plans limit how much is watched, never what a scan found. Visibility is structural, not promotional — asserted by tests over the entitlements model itself.
Common questions
HIPAA statements?
Certification claims avoided entirely — evidence supports YOUR compliance narrative, written by counsel.
Run a free scan at keydrift.dev/scan — paste a URL or the bundle source itself, no account. Findings arrive masked, with the exact chunk they live in.