Cysteine residues undergo various oxidative modifications, acting as key sensors of reactive oxygen species (ROS) and reactive nitrogen species (RNS). Given that ROS and RNS have known roles in many pathophysiological processes, numerous proteome-wide strategies to profile cysteine oxidation state have emerged in the last decade. Recent advancements to traditional redox profiling methods include incorporation of costly isotopic labeling reagents to allow for more quantitative assessment of oxidation states. These methods are typically carried out by using sequential thiol capping and reduction steps in order to label redox-sensitive cysteines, often found in di-cysteine motifs (‘CXXC’ or ‘CXXXC’). Tailored, pricy algorithms are commonly used to analyze redox-profiling datasets, the majority of which cannot accurately quantify site-of-labeling in redox-motifs; moreover, accurate quantification is confounded by excess labeling reagents during sample preparation. Here, we present a low-cost redox-profiling workflow using newly synthesized isotopic reagents compatible with SP3-bead technology, termed SP3-ROx, that allows for high throughput, rapid identification of redox-sensitive cysteines. We optimize cysteine labeling quantification using the FragPipe suite, an open source GUI for MSfragger-based search algorithm. Application of SP3-ROx to naive and activated T cells identifies redox-senstive cysteines, showcasing the utility of this workflow to study biological processes.