arXiv subjects

Andrea Ciccotelli

Publications and source records attributed to Andrea Ciccotelli.

3 recordsLinked to original sources

arXiv2026

TENET: Telegram Mini App (in)security

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.

cs.CR↗

arXiv2026

I-(OT)^2: A Client-optimal Oblivious Transfer Protocol for IoT Devices

Oblivious Transfer (OT) is a fundamental cryptographic primitive enabling privacy-preserving computation and constitutes a core building block for secure multi-party computation while supporting a wide range of security-sensitive applications: private information retrieval, zero-knowledge proofs, and password-authenticated key exchange, to cite a few. While recent advances in OT extension have significantly reduced amortised costs, their reliance on batches of random base OTs and substantial pre-computation phases limits their practicality in scenarios where the number of transfers is modest or where communication latency and client-side computation are critical constraints. In such settings, efficient base OT protocols remain both relevant and necessary. In this work, we introduce $I$-$(OT)^2$, a novel base 1-out-of-2 OT protocol grounded in the quadratic residuosity problem, specifically designed to minimise receiver-side computation and interaction. Our construction is particularly appealing on client--server architectures in which the receiver operates on low-power hardware, such as Internet of Things (IoT) devices. Through a lightweight offline pre-computation phase, $I$-$(OT)^2$ shifts the on-transfer computational burden almost entirely to the Sender, while reducing online communication to only six messages and four digests exchanged. We provide a detailed description of the protocol, accompanied by a formal proof of its security. Moreover, to demonstrate the viability of $I$-$(OT)^2$, we also present an open-source proof-of-concept implementation (in C language) evaluated on real IoT hardware. Results are staggering: for 128-bit security using a 3072-bit RSA modulus, the receiver incurs an average online cost per OT as low as 2.80 {\mu}s on desktop platforms and 39.90 {\mu}s on IoT devices, more than 10$\times$ faster than the well known SimplestOT.

cs.CR↗

arXiv2022

Sanitization of Multimedia Content: A Survey of Techniques, Attacks, and Future Directions

The exploding rate of data publishing in our networked society has magnified the risk of sensitive information leakage and misuse, pushing the need to secure multimedia content from unintended exposure to potentially untrusted third parties. Data sanitization -- the process of securing multimedia by removing or obfuscating sensitive information such as personally identifiable or confidential data -- helps to mitigate the severe impact of security risks and privacy violations related to the published data. In this paper, we make several contributions. First, we classify data sanitization methods along two main dimensions: the media type (images, audio, text, and video) and the techniques used to sanitize sensitive regions, which we group into obfuscation-based (e.g., distortion, replacement) and removal-based approaches. Building on this categorization, we present a comprehensive review of technologies designed to protect multimedia content. We then broaden the scope by introducing the attacks that specifically target these technologies, followed by a discussion of potential countermeasures. Each aspect is complemented with critical discussions and lessons learned. Finally, we identify and elaborate on open research challenges in the crucial domain of multimodal multimedia sanitization. We argue that the systematization provided in this work -- together with the highlighted challenges and research directions -- offers a valuable blueprint for practitioners, industry, and academia alike, while paving the way for novel research avenues in the field.

cs.CR↗