Join us in our journey into modern Android's Data Encryption at rest, in which we study how it works and assess how resistant it is against attackers having access to a range of high end software vulnerabilities.

In this blog post we'll see a technique to gain code execution in SMM from a very limited write primitive.

Mithril Security engaged a collaboration with Quarkslab to perform an audit of the BlindAI-preview, now known as BlindAI Core, which is an open-source confidential computing solution for querying and deploying AI models while guaranteeing data privacy. The goal of the audit was to evaluate the BlindAI resiliency based on the definition of a threat model after a refresh on the latest state-of-the-art.

In this blog post we present PASTIS, a Python framework for ensemble fuzzing, developed at Quarkslab.

We present TritonDSE, a new tool by Quarkslab. TritonDSE is a Python library, built on top of Triton, that provides easy and customizable Dynamic Symbolic Execution capabilities for binary programs.

This article is about greybox fuzzing of userland targets that can be encountered in Android using AFL++ and its Frida mode. We also discuss how to target JNI functions, to test the native features invoked by Java code.

This article provides a brief overview of how Microsoft Open Management Infrastructure (OMI) works, as well as two vulnerabilities that the Quarkslab Cloud team identified through fuzzing techniques.

A journey into the Pwn2Own contest. Part 1: Netgear RAX30 router WAN vulnerabilities

Falco's maintainers, with support from Cloud Native Computing Foundation, engaged with Quarkslab to perform an audit of Falco, an open-source cloud-native runtime security tool. The goal of the audit was to assist the Falco maintainers to increase their security posture using static and dynamic analysis (fuzzing in particular) and was organized by Open Source Technology Improvement Fund, Inc.

In this blog post we discuss the details of two vulnerabilities we discovered in the Trusted Platform Module (TPM) 2.0 reference implementation code. These two vulnerabilities, an out-of-bounds write (CVE-2023-1017) and an out-of-bounds read (CVE-2023-1018), affected several TPM 2.0 software implementations (such as the ones used by virtualization software) as well as a number of hardware TPMs.