As attention-deficit/hyperactivity disorder (ADHD) is a feasible target for individuals aiming to procure stimulant medication or accommodations, there is a high clinical need for accurate assessment of adult ADHD. Proven falsifiability of commonly used diagnostic instruments is therefore of concern. The present study aimed to develop a new, ADHD-specific infrequency index to aid the detection of non-credible self-report. Disorder-specific adaptations of four detection strategies were embedded into the Conners’ Adult ADHD Rating Scales (CAARS) and tested for infrequency among credible neurotypical controls (n = 1001) and credible adults with ADHD (n = 100). The new index’ ability to detect instructed simulators (n = 242) and non-credible adults with ADHD (n = 22) was subsequently examined using ROC analyses. Applying a conservative cut-off score, the new index identified 30% of participants instructed to simulate ADHD while retaining a specificity of 98%. Items assessing supposed symptoms of ADHD proved most useful in distinguishing genuine patients with ADHD from simulators, whereas inquiries into unusual symptom combinations produced a small effect. The CAARS Infrequency Index (CII) outperformed the new infrequency index in terms of sensitivity (46%), but not overall classification accuracy as determined in ROC analyses. Neither the new infrequency index nor the CII detected non-credible adults diagnosed with ADHD with adequate accuracy. In contrast, both infrequency indices showed high classification accuracy when used to detect symptom over-report. Findings support the new indices’ utility as an adjunct measure in uncovering feigned ADHD, while underscoring the need to differentiate general over-reporting from specific forms of feigning.