Download and Format the FTC Robocall Complaint List for NCID
While researching how to set up multiple modems on an single NCID server, I stumbled across a forum entry describing the new robo call complaint list that the FTC began posting in October 2015. I immediately investigated and downloaded the complaint list to load it onto my Raspberry Pi NCID server. In no time, I wrote an R script to automate downloading the file and updating my ncidd.alias file with the new definitions–the FTC is updating the file on a monthly basis.
Since I will now know what numbers have been reported to the FTC, it will be easy to identify and report any new robo call phone numbers to the FTC.
R Code to Download FTC Robo Call Complaint List
To automate the process of downloading the complaint list and creating a new file to append to the complaintList, I wrote an R script to simplify the process. I took an approach of adding the complaint phone numbers to the ncidd.alias file to replace the NAME with “FTC Complaint List” as suggested by a discussion on the NCID forum. The first segment sets up some filenames and downloads the FTC complaint file:
# # Set up file name and URL arguments # outFn <- "../../data/ftc_weekly_complaintList.csv" ftccomplaintListURL <- "https://consumercomplaints.fcc.gov/hc/theme_assets/513073/200051444/Telemarketing_RoboCall_Weekly_Data.csv" aliasFn <- "../../data/ncidd.alias.ftc" complaintListFn <- "../../data/ncidd.blacklist.ftc" # # The FTC website uses a self-signed certificate for some reason, thus --no-check-certificate # wgetCmdStr <- paste("wget --no-check-certificate -O ",outFn,ftccomplaintListURL) system(wgetCmdStr) ftccomplaintListDf <- read.csv(outFn,header=TRUE) summary(ftccomplaintListDf)
## Phone.Issues ## Robocalls :18909 ## Telemarketing (including do not call and spoofing):38930 ## ## ## ## ## ## Time.of.Issue Caller.ID.Number Advertiser.Business.Phone.Number ## - : 2573 - :13782 - :44466 ## 1:00 PM : 841 248-215-0437: 187 844-279-7423: 72 ## 10:00 AM: 768 267-233-6724: 131 844-226-8637: 66 ## 11:00 AM: 688 213-217-9999: 110 281-702-8593: 53 ## 9:00 AM : 583 863-777-2311: 107 202-864-1122: 37 ## 2:00 PM : 537 609-270-0113: 103 844-279-7431: 32 ## (Other) :51849 (Other) :43419 (Other) :13113 ## Type.of.Call.or.Message..Robocalls. ## :38893 ## Abandoned Call : 3746 ## Autodialed Live Voice Call: 997 ## Prerecorded Voice :14034 ## Text Message : 169 ## ## ## Type.of.Call.or.Message..Telemarketing. State ## :19213 California : 7692 ## Abandoned Calls : 7749 Texas : 4133 ## Email : 64 Florida : 4118 ## Live Voice :16771 New York : 3369 ## Prerecorded Voice:13060 Pennsylvania: 2413 ## Text Messaage : 880 Virginia : 2111 ## Text Message : 102 (Other) :34003 ## Date..Ticket.Date.of.Issue. Date..Ticket.Created. ## 10/14/2015: 783 10/14/2015: 788 ## 10/1/2015 : 738 10/15/2015: 778 ## 10/7/2015 : 738 10/7/2015 : 770 ## 10/6/2015 : 733 10/6/2015 : 745 ## 10/27/2015: 722 10/27/2015: 741 ## 10/15/2015: 710 10/28/2015: 726 ## (Other) :53415 (Other) :53291
The next segment uses the dplyr and magrittr packages to select the two columns with phone numbers, merge them into one column and then de-dup the numbers:
# # Load required packages # require(dplyr) require(magrittr) # # Combine the phone numbers in Caller.ID.Number column and Advertiser.Business.Phone.Number column into a single column to handle nulls in either # of the columns # callerIDDf <- ftccomplaintListDf %>% select(Caller.ID.Number) phoneNbrDf <- ftccomplaintListDf %>% select(Advertiser.Business.Phone.Number) %>% rename(Caller.ID.Number=Advertiser.Business.Phone.Number) complaintListDf <- rbind(callerIDDf,phoneNbrDf) # # De-dup the list and generate the text that will go in the ncidd.alias file # complaintListDf <- complaintListDf %>% group_by(Caller.ID.Number) %>% summarise(count=n()) %>% mutate(ncidFormatPhone=gsub("-","",Caller.ID.Number)) %>% mutate(aliasLine=paste("alias NAME * = \"FTC Complaint List\" if ",ncidFormatPhone)) summary(complaintListDf)
## Caller.ID.Number count ncidFormatPhone ## - : 1 Min. : 1.00 Length:25747 ## 000-000-0000: 1 1st Qu.: 1.00 Class :character ## 000-000-0001: 1 Median : 1.00 Mode :character ## 000-000-0106: 1 Mean : 4.49 ## 000-000-0911: 1 3rd Qu.: 2.00 ## 000-000-2019: 1 Max. :58248.00 ## (Other) :25741 ## aliasLine ## Length:25747 ## Class :character ## Mode :character ## ## ## ##
The final segment writes the two files in the format that NCID can read:
# # Write the file to be appended to # write(complaintListDf$aliasLine,file=aliasFn) write("\"FTC Complaint List\"",file=complaintListFn)
To append the files to the existing lists of alias and blacklist definitions, a slightly different form of sudo is required:
cd /etc/ncid
sudo cp ncidd.alias ncidd.alias.personal
sudo cp ncidd.blacklist ncidd.blacklist.personal
sudo sh -c "cat ncidd.alias.ftc >> ncidd.alias"
sudo sh -c "cat ncidd.blacklist.ftc >> ncidd.blacklist"
In future months, I will concatenate the .personal and .ftc files.
Analysis on the FTC Complaint List
It is probably useful to look at the complaint data to find out more about how spammers go about causing problems. Figure 1 shows the proportion of robo calls vs. spoofing, do not call list violations and other hostile telemarketing practices. Robo calls are only about 1/3 of the complaints.
Print the T-shirt
You can download and print the FTC’s Zap Rachel contest and T-shirt design from the DEF CON contest in 2014.
Related Articles
For additional information, you may be interested in other articles on NCID and stopping phone spam:
- Stopping Rachel from Cardholder Services covers multiple ways to address phone spam, including setting up an NCID server.
- Download and Format the FTC Robocall Complaint List for NCID shows how to download and format the FTC complaint list to give you a list of spammers before they call you.
- Using NCID on Two Phone Lines shows how to add a second modem to your NCID configuration.