1 00:00:03,100 --> 00:00:08,440 There are a couple of terms that you'll hear when you're talking about Retime as an ethical hacker. 2 00:00:08,980 --> 00:00:13,570 The first one is a numeration and the other is scanning where we're going to see how to do scanning 3 00:00:13,570 --> 00:00:15,190 the active recon in just a moment. 4 00:00:15,700 --> 00:00:21,220 But there are lots of types of a numeration we can do passively, like we might want to enumerate the 5 00:00:21,340 --> 00:00:23,910 email accounts inside an organization. 6 00:00:24,010 --> 00:00:29,410 So if I were trying to research an organization like a an attacker would, I would want to know who 7 00:00:29,410 --> 00:00:32,500 works in that organization and how I could get in touch with them. 8 00:00:33,200 --> 00:00:37,840 This you can see how this would be immediately useful for a phishing campaign like we learned how to 9 00:00:37,840 --> 00:00:39,370 do back in the previous section. 10 00:00:39,790 --> 00:00:45,520 But the harvester is one of the tools built into Kalli that will help us enumerate those e-mail accounts. 11 00:00:45,550 --> 00:00:48,820 It'll help you see for your organization as an ethical hacker. 12 00:00:49,270 --> 00:00:52,630 How many people's contact information is freely available out there? 13 00:00:52,930 --> 00:00:54,790 Of course, you can do a regular Web search. 14 00:00:55,120 --> 00:01:00,570 You can do a LinkedIn search to see who is posting one information about your organization. 15 00:01:00,820 --> 00:01:05,410 But the harvester is a really handy tool built into Caleigh that will automatically compile results 16 00:01:05,410 --> 00:01:10,240 from LinkedIn, from Google, from Twitter, from dozens of other sources out on the Internet. 17 00:01:10,540 --> 00:01:15,500 So let's switch back over to Caleigh and FUBU, the Kelly up fresh. 18 00:01:15,520 --> 00:01:17,950 We're going to go Kalli as the user name. 19 00:01:18,040 --> 00:01:19,300 And Kelly is the password. 20 00:01:19,630 --> 00:01:25,700 If you're on an older version of Caleigh Linux, you may use the username route and the password tours 21 00:01:25,870 --> 00:01:27,100 t double o r. 22 00:01:27,490 --> 00:01:32,060 I'm running a 20-20 a newer version of Caleigh after 2020 dot two. 23 00:01:32,090 --> 00:01:39,880 It's Caleigh, Caleigh, everything 20-20 dot one and earlier will be route and tour. 24 00:01:39,910 --> 00:01:41,950 Just roup spelled backwards as the username. 25 00:01:42,400 --> 00:01:43,060 So Kalli. 26 00:01:46,190 --> 00:01:49,130 And I'm going to click on the Caleigh menu at the top. 27 00:01:51,260 --> 00:01:53,750 And find information gathering. 28 00:01:55,180 --> 00:02:03,490 And I want to do some o cent analysis or open source intelligence analysis. 29 00:02:03,940 --> 00:02:07,030 That means it's freely available, publicly available information. 30 00:02:07,450 --> 00:02:09,700 And I'm going to use the tool called the Harvester. 31 00:02:10,070 --> 00:02:12,490 Now, the harvester can also be run from the command line. 32 00:02:14,920 --> 00:02:20,590 But the nice thing is when we run the harvester from the command line, from the Caleigh menu option, 33 00:02:20,950 --> 00:02:24,040 it automatically gives us a help page for the harvester. 34 00:02:24,580 --> 00:02:26,440 We can increase the size here just a bit. 35 00:02:27,310 --> 00:02:28,030 There we go. 36 00:02:28,990 --> 00:02:33,910 So you can see that the harvester has a help option and it gives us some information. 37 00:02:33,940 --> 00:02:37,570 It takes a few options dash D for the domain. 38 00:02:38,020 --> 00:02:43,090 So if I wanted to search information about the University of North Georgia, I would say dash d n g 39 00:02:43,090 --> 00:02:43,900 Dudi to you. 40 00:02:44,560 --> 00:02:47,500 We can limit the number of results if we only want a certain number. 41 00:02:47,500 --> 00:02:50,320 So if you're at a big organization, you might do a dash l. 42 00:02:50,410 --> 00:02:52,450 That's a lowercase L a 50. 43 00:02:53,620 --> 00:02:56,180 And then we can use various sources. 44 00:02:56,200 --> 00:02:58,870 We see the dash B right down here. 45 00:02:59,440 --> 00:03:05,750 So with this information, we know just enough to be able to do a quick the harvester search. 46 00:03:05,860 --> 00:03:08,890 I'll do a control l to clear the screen. 47 00:03:08,920 --> 00:03:19,850 I'm going to say the harvester, the H-E Harvester and it's a capital H and the harvester dash d u n 48 00:03:20,010 --> 00:03:21,130 g Dudi to you. 49 00:03:21,580 --> 00:03:25,940 And here you should put the organization you're interested in gathering more information about whether 50 00:03:25,960 --> 00:03:31,180 that CNN dot com, whether that's a company that's hired you, whether it's your school. 51 00:03:31,840 --> 00:03:35,980 That's a really good place to get started, to gather some publicly available free information. 52 00:03:36,670 --> 00:03:38,830 Everything that you're doing here is still passive. 53 00:03:38,860 --> 00:03:40,180 You're not scanning their network. 54 00:03:40,210 --> 00:03:43,990 You're looking at Google results and Twitter results and LinkedIn results. 55 00:03:44,350 --> 00:03:46,290 In fact, let's do a LinkedIn search first. 56 00:03:46,300 --> 00:03:47,200 So we'll do a dash. 57 00:03:47,210 --> 00:03:49,300 B, LinkedIn. 58 00:03:51,930 --> 00:03:54,640 And let's just see what the harvester gets for us. 59 00:03:55,100 --> 00:03:59,140 Now, it may take just a few moments to run a harvester surge, depending on the source, depending 60 00:03:59,140 --> 00:04:00,610 on the size of your organization. 61 00:04:02,070 --> 00:04:02,500 All right. 62 00:04:02,530 --> 00:04:08,040 And for my organization, the University of North Georgia, you can see it covered a lot of results 63 00:04:08,040 --> 00:04:09,330 in very little time. 64 00:04:09,930 --> 00:04:15,640 So we found 61 candidates here that had some connection to UMG. 65 00:04:17,670 --> 00:04:23,890 But in our case, you can see we had several people who have a last name of UMG or own. 66 00:04:24,390 --> 00:04:29,540 So we do have some actual people who'd work at UMG. 67 00:04:29,580 --> 00:04:31,650 You'll find that by University of North Georgia. 68 00:04:32,430 --> 00:04:35,190 So get some information inside organization. 69 00:04:35,190 --> 00:04:40,320 But because you engy is also a last name, we didn't get a lot of information that we could use there. 70 00:04:40,320 --> 00:04:42,120 So let's try our next search. 71 00:04:42,810 --> 00:04:44,710 Let's run the harvester on you and. 72 00:04:45,000 --> 00:04:50,120 I'm going to do control l to clear the screen and the up arrow and I'm just going to change the source. 73 00:04:50,130 --> 00:04:51,720 And now go to B Google. 74 00:04:54,000 --> 00:04:57,620 And once again, this may take just a little bit of time to run, but it's worth the wait. 75 00:04:59,170 --> 00:05:03,450 And we can see the harvester gathered a little bit of information on our organization. 76 00:05:03,490 --> 00:05:05,710 I can see Professor Yang's information. 77 00:05:06,130 --> 00:05:08,620 I can see a help desk e-mail that may be useful. 78 00:05:08,620 --> 00:05:14,770 In fact, if I were doing a social engineering campaign and had the permission of the organization, 79 00:05:15,280 --> 00:05:18,420 I might send as an e-mail pretending to be help desk. 80 00:05:18,580 --> 00:05:20,650 Uesugi to Professor Yang. 81 00:05:21,400 --> 00:05:25,080 So that Dr. Yang might be tempted to click through that e-mail. 82 00:05:25,080 --> 00:05:25,370 Dr. 83 00:05:25,790 --> 00:05:30,580 Dr. Yang's a really good computer science professor, so I don't think he's going to do do that. 84 00:05:30,610 --> 00:05:32,530 But this is a really good example. 85 00:05:32,780 --> 00:05:35,740 How would you quickly gather just a little bit of information? 86 00:05:36,150 --> 00:05:40,590 Now, if we want a full the harvest to report on an organization, we can do that as well. 87 00:05:42,030 --> 00:05:47,480 Let's clear the screen and I'm going to type the harvester dash d. 88 00:05:47,970 --> 00:05:50,340 N g dash B all. 89 00:05:51,380 --> 00:05:53,240 And I'm going to say dash f. 90 00:05:54,230 --> 00:05:57,370 Report dot astm. 91 00:05:58,130 --> 00:06:04,790 So this F is a file and output file where we can store all of the information that the harvester gathers 92 00:06:04,790 --> 00:06:05,890 about the organization. 93 00:06:06,020 --> 00:06:06,460 Now, I just. 94 00:06:06,490 --> 00:06:10,580 You chose you, Angie, because it happens to be the university where I teach you the day. 95 00:06:10,940 --> 00:06:17,720 But that's a place where in the Dashty you put whatever organization you were looking out for as an 96 00:06:17,720 --> 00:06:18,500 ethical hacker. 97 00:06:21,350 --> 00:06:28,340 So if we give this command a run with a Dashty of your organization, the Dash B of all and the dash 98 00:06:28,430 --> 00:06:31,100 F of report, it'll take several minutes to complete. 99 00:06:31,370 --> 00:06:38,120 But when we come back, we'll be able to see that report and see what information is publicly available 100 00:06:38,240 --> 00:06:41,960 about our organization using just a couple of quick search results. 101 00:06:43,120 --> 00:06:47,830 And it's going to take several minutes to run all of the different skins that come in the harvester. 102 00:06:48,490 --> 00:06:53,290 But if you run across an error, just as a quick troubleshooting note, you see down here, it says 103 00:06:53,290 --> 00:06:58,070 there's no such file or directory API keys dot Yamal. 104 00:06:58,780 --> 00:07:04,570 This is because there are some paid services that you can use through the harvester. 105 00:07:04,570 --> 00:07:11,800 It integrates with paid search engines and of subscription accounts so that you can search for things 106 00:07:11,800 --> 00:07:14,830 like devices through showed and other sources. 107 00:07:15,220 --> 00:07:22,080 But all we need to do to get rid of that error is to actually create an API keys dot yaml file. 108 00:07:22,540 --> 00:07:31,660 So says there's no API keys diam on a copy so that I don't misspell that control l and I'm just going 109 00:07:31,660 --> 00:07:33,190 to say echo. 110 00:07:34,640 --> 00:07:40,550 Actually, we can just say nothing into and then paste. 111 00:07:42,390 --> 00:07:42,880 Clipboard. 112 00:07:43,420 --> 00:07:49,120 And what this will do is create an empty file called API keys, dot yaml so we won't run into that error. 113 00:07:50,260 --> 00:07:54,820 And if it's taking too long for you to do the all report, you can just blend your reports by doing 114 00:07:54,820 --> 00:07:58,540 like LinkedIn and Google. 115 00:08:00,740 --> 00:08:01,370 And press enter. 116 00:08:02,350 --> 00:08:05,510 It will do a search of just Google and LinkedIn. 117 00:08:07,160 --> 00:08:09,980 Or you can look through the help and choose any of the other sources. 118 00:08:11,480 --> 00:08:18,500 And we can see that it says it's created a report and the report name that we used was just reporting 119 00:08:18,540 --> 00:08:19,400 that ASTM Al. 120 00:08:19,880 --> 00:08:25,820 So I'm going to clear the screen and I'm going to say Firefox report that a female. 121 00:08:27,240 --> 00:08:32,170 And you can see by running Firefox from the command line with the name of the file that existed report, 122 00:08:32,170 --> 00:08:33,020 not H.T. email. 123 00:08:33,480 --> 00:08:35,770 I can see some information from the harvester. 124 00:08:35,770 --> 00:08:42,990 It not only gathered some e-mail addresses, hopefully in some names from linked in it gathered hundreds 125 00:08:43,080 --> 00:08:46,410 of servers that have been used over the years. 126 00:08:46,560 --> 00:08:47,250 Domain names. 127 00:08:47,280 --> 00:08:53,740 Now, these are old entries for the most part, but they're around 130 servers on our campus network. 128 00:08:54,300 --> 00:08:57,900 So that's a really important resource to know is out there. 129 00:08:58,710 --> 00:09:02,280 We can see some emails, some hosts. 130 00:09:03,370 --> 00:09:05,290 See some things from virus total. 131 00:09:06,130 --> 00:09:07,510 We see more hosts. 132 00:09:08,770 --> 00:09:15,070 We can do a little information down here, we can see that we got a Bat 864 e-mail addresses. 133 00:09:16,200 --> 00:09:23,370 And so if we do control F and then search for mail, we will see career services, we'll see names of 134 00:09:23,370 --> 00:09:23,940 people. 135 00:09:24,390 --> 00:09:29,700 In fact, I'm wondering, is there a Bryce and pain we can control F and search for Bryson? 136 00:09:34,500 --> 00:09:35,760 And it didn't find me in there. 137 00:09:35,790 --> 00:09:36,640 But that's OK. 138 00:09:37,500 --> 00:09:40,980 Our university does a good job of keeping old information off the Internet. 139 00:09:41,010 --> 00:09:45,640 But you can see once it's on the Internet, it may be there for forever. 140 00:09:46,170 --> 00:09:50,550 So we found lots of host information, lots of IP addresses. 141 00:09:50,670 --> 00:09:52,410 A good number of email addresses. 142 00:09:52,410 --> 00:09:54,480 We have about 4000 employees, I believe. 143 00:09:54,840 --> 00:09:57,770 So about 864 were in there in some place. 144 00:09:58,200 --> 00:10:01,830 And you can see where all of the results came from, from our all search. 145 00:10:02,310 --> 00:10:04,530 So some really useful information. 146 00:10:04,680 --> 00:10:06,480 If you have trouble using the harvester. 147 00:10:06,750 --> 00:10:07,980 Feel free to rerun it. 148 00:10:08,010 --> 00:10:10,080 Just hit the up arrow and press enter again. 149 00:10:10,450 --> 00:10:11,530 It'll give it another try. 150 00:10:11,560 --> 00:10:15,150 If you have the any of the API keys errors, we showed you how to fix that. 151 00:10:15,540 --> 00:10:20,610 And in the next lesson, we're gonna see how to use the next tool recon in G together. 152 00:10:21,000 --> 00:10:23,450 Even more information about servers on the network.