Quarkslab team performed a cryptographic & security assessment of the Bulletproof protocol, a new non-interactive zero-knowledge proof protocol, to be used by the Monero open-source cryptocurrency (XMR). We found several issues, some possibly critical, during the analysis.

Quarkslab was hired by OSTIF to perform a security assessment of OpenVPN 2.4.0. We focused on code and cryptography assessment. Results are briefly described in this blog post, and full report is available at its end.

In recent weeks, Confide, a secure instant messaging application, has gained popularity in some circles. This article presents a quick assessment of the security of this application. The official website boasts the confidentiality provided by the product through three qualifiers: encrypted, ephemeral and screenshot protected. Each of these aspects will be studied.

The encryption protocol will be particularly detailed because it is tagged as battle tested, military grade cryptography. We already knew about military grade cryptography, which seems to be a synonym of put AES-256 somewhere, no matter how you use it in many applications, but we had never heard of battle tested cryptography. This article is an opportunity to present this technology.

Developing properly end-to-end communication systems is complex. As we have seen in the past with iMessage, even if cryptographic primitives are correctly implemented and encryption keys are correctly generated and protected, the design is critical to forbid the service operator from being able to eavesdrop messages.

Quarkslab made a security assessment of VeraCrypt 1.18. The audit was funded by OSTIF and was performed by two Quarkslab engineers between Aug. 16 and Sep. 14, 2016 for a total of 32 man-days of study. A critical vulnerability, related to cryptography, has been identified. It has been introduced in version 1.18, and will be fixed in version 1.19.

An optimization for the finite field multiplication on 128-bit elements for AES-GCM exists whose explanation was not published, preventing any further application with different parameters. We reverse engineered the result to 1) get the explanation and 2) be able to apply it with other parameters.