In the field of malware detection, method based on syntactical consideration are usually efficient. However, they are strongly vulnerable to obfuscation techniques. This study proposes an efficient construction of a morphological malware detector based on a syntactic and a semantic analysis, technically on control flow graphs of programs (CFG). Our construction employs tree automata techniques to provide an efficient representation of the CFG database. Next, we deal with classic obfuscation of programs by mutation using a generic graph rewriting engine. Finally, we carry out experiments to evaluate the false-positive ratio of the proposed methods.