How to change a multi-level nested list into a tibble to avoid an error with filter?

In a nested list with three levels, I need to reach the third level (i.e., resources) and check whether some special characters exist in the data. I tried to make a similar sample of data but there is still a difference I could not address. While level1 (foo) and level 2 (e.g., obj1) are lists, level 3 (resource) is list(s3:data.frame). I run the code below but as you can see there is an error when it comes to the second part (i.e., filter). Could you please tell me how to avoid this error?

    obj1 <- list(resource = list(bodyPart = c("leg", "arm", "knee"),side = "RIGHT", device = "SENS"))
    obj2 <- list(resource = list(bodyPart = c("leg", "arm", "knee"), side = "LEFT", device = "GOM"))
        
    x <- list(foo = obj1, bar = obj2)
        
Dat <- lapply(x, function(tb) tb[sapply(tb, function(z) any(grepl("[^\x01-\x7F]", z), na.rm = TRUE))]) %>% 
dplyr::filter(if_any(everything(), ~ grepl("[^\x01-\x7F]", .)))
        
        Error in UseMethod("filter") : 
          no applicable method for 'filter' applied to an object of class "list"

you could recursively scan the list nodes with rapply:

x |> rapply(f = \(node) grepl("[^\x01-\x7F]", node))

to generate a tibble from above:

library(tibble)

data.frame(has_invalid_character = x |> rapply(f = \(node) grepl("[^\x01-\x7F]", node)),
           content =  x |> rapply(f = \(node) node)
           ) |>
  rownames_to_column('item') |>
  as_tibble()

# A tibble: 10 x 3
   item                   has_invalid_character content
   <chr>                  <lgl>                 <chr>  
 1 foo.resource.bodyPart1 FALSE                 leg    
 2 foo.resource.bodyPart2 FALSE                 arm    
 3 foo.resource.bodyPart3 FALSE                 knee   
 4 foo.resource.side      FALSE                 RIGHT  
 5 foo.resource.device    FALSE                 SENS        
## etc.