LC-HRMS-based metabolomics approach was applied to the river Nile-derived fungus Aspergillus awamori after its fermentation on four different media and using four epigenetic modifiers as elicitors. Thereafter, a comprehensive multivariate statistical analysis such as PCA, PLS-DA and OPLS-DA were employed to explain the generated metabolomic data (1587 features). PCA showed that the fungus displayed a unique chemical profile in each medium or elicitor. Additionally, PLS-DA results revealed the upregulated metabolites under each of these conditions. Results indicated that both rice and malt dextrose agar were recognized as the best media in terms of secondary metabolites diversity and showed better profiles than the four applied epigenetic modifiers, of which nicotinamide was the best secondary metabolite elicitor. Testing the antibacterial and cytotoxic effects of all A. awamori-derived extracts revealed that using epigenetic modifiers can induce antimicrobial metabolites against S. aureus and E. coli, whereas using rice, malt dextrose or nicotinamide can induce groups of cytotoxic metabolites. OPLS-DA results assisted in the putative identification of the induced metabolites that could be responsible for these observed inhibitory activities. This study highlighted how powerful the OSMAC approach in maximizing of the chemical diversity of a single organism. Furthermore, it revealed the power of metabolomics in tracing, profiling and categorizing such chemical diversity and even targeting the possible bioactive candidates which require further scaling up studies in the future.