replace diffent column values with regex

i have the following dataframe

import pandas as pd
import numpy as np

data = {'data.cmd0': {0: "exec sp_add_job 'sc.exe'",    1: "exec sp_add_job 'sc'",        2:"EXEC sp_droplogin 'mms'"},
        'data.cmd1': {0: "exec sp_add_job 'dbdotas2'",  1:"exec sp_add_job 'regs1.exe'",  2:"EXEC sp_droplogin '2dbdotas'"},
        'data.cmd2': {0: "exec sp_add_job '2dbdotas'",  1: "exec sp_add_job 'gaibian!@'", 2:"EXEC sp_droplogin 'mms.exe'"},
                     }
       
df1 = pd.DataFrame(data)
df1.head()

        data.cmd0                         data.cmd1                        data.cmd2
0   exec sp_add_job 'sc.exe'    exec sp_add_job 'dbdotas2'    exec sp_add_job '2dbdotas'
1   exec sp_add_job 'sc'        exec sp_add_job 'regs1.exe'   exec sp_add_job 'gaibian!@'
2   EXEC sp_droplogin 'mms'     EXEC sp_droplogin '2dbdotas'  EXEC sp_droplogin 'mms.exe

What i want is to replace these SQL commands with some other words. Expected outcome:

      data.cmd0                       data.cmd1                        data.cmd2
0   exec sp_add_job              exec sp_add_job                   exec sp_add_job
1   exec sp_add_job              exec sp_add_job                   exec sp_add_job
2   EXEC sp_droplogin'           EXEC sp_droplogin                 EXEC sp_droplogin

For the first command exec sp_add_job 'sc.exe' i was able to generate the following regex along with a dictionary and then using replace method:

df1.replace({"exec sp_add_job '[a-zA-Z]+\.[a-zA-Z]+'":'exec sp_add_job'}, regex=True)

But inside of the ' ' there exist different values which start with number or letter or have special characters in different place.

How can i come to a universal solution to match all the possible commands using on line of regex?

Any ideas?

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