TENET: Telegram Mini App (in)security
Andrea Ciccotelli, Federico Zappone, Roberto Di Pietro
Abstract
Telegram, with over 450 million daily active users, has introduced Mini Apps---web-based applications running directly within its client. However, this integration introduces notable security risks. As we demonstrate, many Mini Apps store authentication materials---such as session tokens and wallet mnemonic phrases---in plaintext on client devices, exposing users to unauthorized access, impersonation, and financial exploitation. While insecure client-side storage is a known risk in web applications, the Telegram Mini App ecosystem presents a uniquely dangerous combination of factors absent from prior work: no platform-level security review, no storage access restrictions, a financially motivated user base handling live cryptocurrency assets, and a WebView environment that offers weaker protections than standalone browsers. To investigate this threat, we present TENET, a purpose-built auditing tool whose design decisions---pattern selection, entropy thresholds, and charset validation---are grounded in the structural properties of the secrets targeted and empirically validated against a ground-truth dataset. We screened 61 Mini Apps using a stratified, popularity-weighted sampling strategy based on popularity. Of the 37 applications that met our processing criteria and were analyzed, 30 exhibited security flaws, which we classify into three severity tiers: plaintext storage, recoverable encryption, and replayable tokens. Notably, even Telegram's official Wallet exhibits a severe vulnerability that may lead to full account compromise. Following our responsible disclosure, Telegram implemented two new secure-storage APIs, and our post-remediation verification confirmed that its official Wallet no longer exposes the recovery mnemonic in plaintext. Finally, we propose mitigation measures and best practices for both Telegram platform developers and third-party Mini App creators.
Create a lesson
Related papers
Analog Pin Directionality as an Exfiltration Attack Surface in Mixed-Signal ICs
Ramana Ranganatham, Chirag Adiga, Michael Zuzak et al.
Characterizing Network Centralization and Observability in the Remote MCP Ecosystem
Muhammad Abdullah Sohail
When Agents Look Like Beacons: NIDS Evasion by Model Context Protocol Traffic
Muhammad Abdullah Sohail
Hamming Ideals and Grobner Bases for ISD-like Syndrome Decoding
Roberto La Scala, Marco Marchesin, Sharwan K. Tiwari
ASLEval: Measuring Privacy Exposure Displacement in LLM Agent Sessions
Guosen Wu, Huizhen Huang, Guoxiong Long et al.
CASHEWS: Source Preprocessor for LLM-based Malicious Package Detection
Jean-Charles Noirot Ferrand, David Adei, Anders Møller et al.