CVE-2026-48080
Description
OpenReception's appointment booking software provides an end-to-end encrypted appointment booking platform. Prior to version 1.0.2, the `GET /api/tenants/{id}` endpoint returns the full tenant record to any authenticated `TENANT_ADMIN` of that tenant, including the `databaseUrl` field. This field contains the live PostgreSQL connection string the application uses to connect to that tenant's database. In the tested official `docker-compose.prod.yml` deployment, the connection string contained the user `postgres` with `rolsuper=true` and the plaintext password from `secrets/postgres_password.txt`. Operators who configure a non-superuser PostgreSQL user via `secrets/postgres_user.txt` would expose a less privileged credential, but the disclosure of the connection string itself is independent of that choice. The same credential applies to every database managed by that PostgreSQL instance: the central `appointment_booking` database, every per-tenant database (one per tenant), and the postgres administrative database. A `TENANT_ADMIN` of one tenant who can reach `postgres:5432` (directly via internal network, indirectly via any SSRF, RCE, or file-read in the application) can read every other tenant's appointment ciphertexts, key shares, and metadata; read the central user table, including all `GLOBAL_ADMIN` accounts, password hashes, and session records; modify or delete any data in any tenant database; and/or i a superuser-scoped deployment: use PostgreSQL's `pg_read_server_files`, `COPY ... FROM PROGRAM`, and `CREATE EXTENSION` for further escalation inside the database container. This breaks the per-tenant database isolation that is otherwise the primary cross-tenant control in the application. The application code carefully scopes most queries to the calling tenant's database, but those scopings are irrelevant once the attacker holds the credentials that bypass the application entirely. Version 1.0.2 fixes the issue.
EPSS (Exploit Prediction Scoring System)
EPSS (Exploit Prediction Scoring System)
Prevede la probabilità di sfruttamento basata su intelligence sulle minacce e sulle caratteristiche della vulnerabilità.