1 1 00:00:00,300 --> 00:00:02,190 Vulnerability reports. 2 2 00:00:02,190 --> 00:00:03,090 In this lesson, 3 3 00:00:03,090 --> 00:00:05,700 we're going to dig into those vulnerability reports 4 4 00:00:05,700 --> 00:00:07,500 and understand a little bit more about them. 5 5 00:00:07,500 --> 00:00:08,610 Now, before we do that, 6 6 00:00:08,610 --> 00:00:10,920 we have to remember that a vulnerability report 7 7 00:00:10,920 --> 00:00:14,160 that is not validated is essentially useless. 8 8 00:00:14,160 --> 00:00:16,410 If I run the scanning tool, and I take that report, 9 9 00:00:16,410 --> 00:00:17,880 and I hand it into my boss, 10 10 00:00:17,880 --> 00:00:19,680 that doesn't do my boss any good 11 11 00:00:19,680 --> 00:00:21,990 because that report has not been validated. 12 12 00:00:21,990 --> 00:00:23,430 Nobody has looked through it to see, 13 13 00:00:23,430 --> 00:00:25,080 is it actually accurate? 14 14 00:00:25,080 --> 00:00:27,000 All we've done is trust the system. 15 15 00:00:27,000 --> 00:00:29,340 And our job as analysts is to look at these reports 16 16 00:00:29,340 --> 00:00:30,720 and validate them. 17 17 00:00:30,720 --> 00:00:31,590 Now, when we do that, 18 18 00:00:31,590 --> 00:00:33,540 we are looking to look at each of those things 19 19 00:00:33,540 --> 00:00:34,920 that are found in that report 20 20 00:00:34,920 --> 00:00:37,560 and identify them as one of four categories. 21 21 00:00:37,560 --> 00:00:41,700 Are they a true positive, a false positive, a true negative, 22 22 00:00:41,700 --> 00:00:43,050 or a false negative? 23 23 00:00:43,050 --> 00:00:44,880 Now, you may not understand what all of these are, 24 24 00:00:44,880 --> 00:00:46,320 but if you've taken Security+, 25 25 00:00:46,320 --> 00:00:49,020 these concepts should be familiar with you. 26 26 00:00:49,020 --> 00:00:52,230 Now, for many students, this is an area that confuses them. 27 27 00:00:52,230 --> 00:00:53,580 They don't understand the difference 28 28 00:00:53,580 --> 00:00:55,080 between these four categories, 29 29 00:00:55,080 --> 00:00:56,973 and it's really important that you understand them. 30 30 00:00:56,973 --> 00:00:59,460 Now, I covered this in-depth in Security+, 31 31 00:00:59,460 --> 00:01:01,110 but I'm going to go through it again here 32 32 00:01:01,110 --> 00:01:03,360 because it really is an important concept. 33 33 00:01:03,360 --> 00:01:04,680 In fact, on the exam, 34 34 00:01:04,680 --> 00:01:06,300 they may give you some issues, 35 35 00:01:06,300 --> 00:01:07,740 some things from a security report, 36 36 00:01:07,740 --> 00:01:10,500 and ask you to classify them as true positive, 37 37 00:01:10,500 --> 00:01:13,047 false positive, true negative, or false negative. 38 38 00:01:13,047 --> 00:01:14,700 And if you don't understand the concepts, 39 39 00:01:14,700 --> 00:01:16,470 you're not going to be able to get that right. 40 40 00:01:16,470 --> 00:01:18,030 So let's talk about them. 41 41 00:01:18,030 --> 00:01:19,530 First, true positive. 42 42 00:01:19,530 --> 00:01:21,360 What is a true positive? 43 43 00:01:21,360 --> 00:01:23,940 Well, this is an alert that matches a vulnerability 44 44 00:01:23,940 --> 00:01:26,280 and that vulnerability actually exists 45 45 00:01:26,280 --> 00:01:27,900 on the system you scanned. 46 46 00:01:27,900 --> 00:01:30,300 So this is something that really happened. 47 47 00:01:30,300 --> 00:01:31,470 So what I like to think about 48 48 00:01:31,470 --> 00:01:33,120 when I think about these four categories is 49 49 00:01:33,120 --> 00:01:34,590 I like to think about pregnancy, 50 50 00:01:34,590 --> 00:01:36,330 because if you're married 51 51 00:01:36,330 --> 00:01:37,710 and you've tried to have kids before, 52 52 00:01:37,710 --> 00:01:39,900 you probably have gone through taking a pregnancy test 53 53 00:01:39,900 --> 00:01:40,890 at some point in your life, 54 54 00:01:40,890 --> 00:01:42,780 either you or your spouse has. 55 55 00:01:42,780 --> 00:01:44,880 For me, it was my spouse who had to take them. 56 56 00:01:44,880 --> 00:01:46,470 But the same concept is there. 57 57 00:01:46,470 --> 00:01:47,520 And so if we look at that, 58 58 00:01:47,520 --> 00:01:49,350 it makes it really easy to understand. 59 59 00:01:49,350 --> 00:01:51,330 For instance, I have two children. 60 60 00:01:51,330 --> 00:01:53,250 That means at least twice in my life, 61 61 00:01:53,250 --> 00:01:55,290 my wife had taken a pregnancy test 62 62 00:01:55,290 --> 00:01:56,490 and she showed me the results, 63 63 00:01:56,490 --> 00:01:57,870 and it was positive. 64 64 00:01:57,870 --> 00:02:00,780 The test said it was positive, that means it was positive. 65 65 00:02:00,780 --> 00:02:02,550 And then she actually was pregnant. 66 66 00:02:02,550 --> 00:02:04,110 She had a baby inside of her. 67 67 00:02:04,110 --> 00:02:06,570 So therefore it was a true positive. 68 68 00:02:06,570 --> 00:02:08,250 That's the idea of a true positive. 69 69 00:02:08,250 --> 00:02:10,080 So in terms of cybersecurity, 70 70 00:02:10,080 --> 00:02:12,210 if you have some bad thing on the network 71 71 00:02:12,210 --> 00:02:15,060 and your sensor detected that bad thing and reported on it, 72 72 00:02:15,060 --> 00:02:16,290 that's a true positive. 73 73 00:02:16,290 --> 00:02:17,700 That's what we want to see. 74 74 00:02:17,700 --> 00:02:20,040 We want our tools to be giving us true positives. 75 75 00:02:20,040 --> 00:02:21,390 Those are the most helpful for us 76 76 00:02:21,390 --> 00:02:23,250 because we know there's a bad thing, 77 77 00:02:23,250 --> 00:02:25,530 and we now know it really exists. 78 78 00:02:25,530 --> 00:02:28,080 Now, the next one we have is what's called a false positive. 79 79 00:02:28,080 --> 00:02:30,390 This is when an alert matches a vulnerability 80 80 00:02:30,390 --> 00:02:31,380 and reports on it, 81 81 00:02:31,380 --> 00:02:32,940 but when you look at that system, 82 82 00:02:32,940 --> 00:02:35,040 the vulnerability doesn't exist. 83 83 00:02:35,040 --> 00:02:37,500 So going back to my pregnancy example, 84 84 00:02:37,500 --> 00:02:38,880 my wife thought it would be really funny 85 85 00:02:38,880 --> 00:02:40,680 when she was taking the pregnancy test 86 86 00:02:40,680 --> 00:02:42,330 to have me take one, too. 87 87 00:02:42,330 --> 00:02:44,970 And so she had me do the little urine test, 88 88 00:02:44,970 --> 00:02:47,400 and of course it came back negative, right? 89 89 00:02:47,400 --> 00:02:49,290 Well, if it showed up positive, 90 90 00:02:49,290 --> 00:02:51,090 then that would mean it was a false positive. 91 91 00:02:51,090 --> 00:02:52,590 Because I'm a guy, 92 92 00:02:52,590 --> 00:02:54,600 there's no way that I can be pregnant, right? 93 93 00:02:54,600 --> 00:02:56,280 I am just not going to have that capability 94 94 00:02:56,280 --> 00:02:58,350 because I don't have the body parts to do that. 95 95 00:02:58,350 --> 00:02:59,820 And so that would be a false positive 96 96 00:02:59,820 --> 00:03:02,070 if I had a test that showed positive, 97 97 00:03:02,070 --> 00:03:04,020 but it was my test because I'm a guy. 98 98 00:03:04,020 --> 00:03:05,670 So going back to our computers, 99 99 00:03:05,670 --> 00:03:06,900 if we're thinking about something, 100 100 00:03:06,900 --> 00:03:07,950 I scan a computer, 101 101 00:03:07,950 --> 00:03:08,783 and it says, 102 102 00:03:08,783 --> 00:03:11,640 "You have a Windows vulnerability on this system." 103 103 00:03:11,640 --> 00:03:12,870 And I look at that system, 104 104 00:03:12,870 --> 00:03:15,180 and it's a Linux or a Macintosh system. 105 105 00:03:15,180 --> 00:03:18,750 Well, those systems aren't running Windows operating system. 106 106 00:03:18,750 --> 00:03:20,940 So therefore I can't have a Windows vulnerability 107 107 00:03:20,940 --> 00:03:22,290 on a Mac system. 108 108 00:03:22,290 --> 00:03:23,940 So that would be a false positive. 109 109 00:03:23,940 --> 00:03:25,597 We can mark that off in our system and say, 110 110 00:03:25,597 --> 00:03:26,430 "Ignore that. 111 111 00:03:26,430 --> 00:03:28,800 We understand it's not really real." 112 112 00:03:28,800 --> 00:03:30,720 That's the idea of a false positive. 113 113 00:03:30,720 --> 00:03:32,130 Now, when you're dealing with false positives, 114 114 00:03:32,130 --> 00:03:34,710 the problem with them is that they are very time-consuming 115 115 00:03:34,710 --> 00:03:36,630 because I now have to go investigate them 116 116 00:03:36,630 --> 00:03:38,580 and I start wasting a lot of resources. 117 117 00:03:38,580 --> 00:03:40,110 So if I had 50 things pop up 118 118 00:03:40,110 --> 00:03:41,610 that told me there was Windows vulnerabilities 119 119 00:03:41,610 --> 00:03:42,720 across my network, 120 120 00:03:42,720 --> 00:03:44,400 and I start going and looking at each of those machines 121 121 00:03:44,400 --> 00:03:46,950 and then I find out there's no Windows on that machine, 122 122 00:03:46,950 --> 00:03:47,940 that's a false positive 123 123 00:03:47,940 --> 00:03:50,760 and I wasted time looking at each of those 50 things. 124 124 00:03:50,760 --> 00:03:51,593 Now, what can you do 125 125 00:03:51,593 --> 00:03:53,550 if you start getting a lot of false positives? 126 126 00:03:53,550 --> 00:03:54,690 Well, one of the things you can do is 127 127 00:03:54,690 --> 00:03:56,190 you can start adjusting your scans 128 128 00:03:56,190 --> 00:03:57,960 to a more appropriate scope. 129 129 00:03:57,960 --> 00:04:01,050 Maybe I'm going to have one scope of all my Windows machines, 130 130 00:04:01,050 --> 00:04:03,000 and another scope for all my Linux machines, 131 131 00:04:03,000 --> 00:04:05,340 and another scope for all my Mac machines. 132 132 00:04:05,340 --> 00:04:07,920 That way I can quickly identify false positives 133 133 00:04:07,920 --> 00:04:09,090 based on operating system 134 134 00:04:09,090 --> 00:04:11,460 because of the use cases of those areas. 135 135 00:04:11,460 --> 00:04:13,440 Another thing you can do is create a new baseline 136 136 00:04:13,440 --> 00:04:14,790 for a heuristic scan. 137 137 00:04:14,790 --> 00:04:16,530 If you're using a heuristic scanning engine, 138 138 00:04:16,530 --> 00:04:19,050 a lot of those will generate more false positives. 139 139 00:04:19,050 --> 00:04:21,420 Signature-based tends to be a little bit more accurate. 140 140 00:04:21,420 --> 00:04:23,610 So if you're getting a lot of false positive 141 141 00:04:23,610 --> 00:04:24,870 and you're using heuristics, 142 142 00:04:24,870 --> 00:04:26,430 go ahead and create a new baseline 143 143 00:04:26,430 --> 00:04:28,920 because obviously your baseline is so out of date 144 144 00:04:28,920 --> 00:04:30,090 from what you're currently doing, 145 145 00:04:30,090 --> 00:04:32,220 it's creating a lot of false positives for you. 146 146 00:04:32,220 --> 00:04:33,480 Another thing you might want to do is 147 147 00:04:33,480 --> 00:04:36,030 add the application to an exception list. 148 148 00:04:36,030 --> 00:04:38,310 For instance, if there's a particular application 149 149 00:04:38,310 --> 00:04:40,410 on my system that is throwing up that report 150 150 00:04:40,410 --> 00:04:41,940 and giving me that flag, 151 151 00:04:41,940 --> 00:04:42,773 I might say, 152 152 00:04:42,773 --> 00:04:44,610 "Hey, I understand I'm running Microsoft Word 153 153 00:04:44,610 --> 00:04:46,320 on this particular Mac machine, 154 154 00:04:46,320 --> 00:04:48,510 but it doesn't mean I'm running Word for Windows." 155 155 00:04:48,510 --> 00:04:50,130 So I can put an exception in there 156 156 00:04:50,130 --> 00:04:52,860 to ignore that report every time it comes up. 157 157 00:04:52,860 --> 00:04:54,240 Another thing you might find is 158 158 00:04:54,240 --> 00:04:57,000 that the vulnerability really does exist on that system, 159 159 00:04:57,000 --> 00:04:59,940 but that vulnerability isn't really exploitable. 160 160 00:04:59,940 --> 00:05:01,350 Now what do I mean by this? 161 161 00:05:01,350 --> 00:05:03,750 Maybe I really do have Windows on that system 162 162 00:05:03,750 --> 00:05:05,520 because I'm running a virtual machine, 163 163 00:05:05,520 --> 00:05:06,990 but there's a firewall in place 164 164 00:05:06,990 --> 00:05:09,210 that no inbound or outbound connections can get to it. 165 165 00:05:09,210 --> 00:05:10,950 So therefore it's protected, 166 166 00:05:10,950 --> 00:05:14,250 and therefore we can say that thing is not exploitable, 167 167 00:05:14,250 --> 00:05:15,510 and we can move on. 168 168 00:05:15,510 --> 00:05:18,210 That's just a silly example, but you get the idea here. 169 169 00:05:18,210 --> 00:05:19,560 Now, when you're dealing with this 170 170 00:05:19,560 --> 00:05:21,210 and you start dealing with exceptions 171 171 00:05:21,210 --> 00:05:22,680 because you have a vulnerability that exists 172 172 00:05:22,680 --> 00:05:23,610 but isn't exploitable 173 173 00:05:23,610 --> 00:05:25,950 or an application that you want to do exceptions on, 174 174 00:05:25,950 --> 00:05:28,650 this falls under the idea of exception management. 175 175 00:05:28,650 --> 00:05:31,260 Now, exception management is a defined process 176 176 00:05:31,260 --> 00:05:32,580 to closely monitor systems 177 177 00:05:32,580 --> 00:05:34,650 that cannot be patched or remediated 178 178 00:05:34,650 --> 00:05:37,140 and must be exempted from those scans. 179 179 00:05:37,140 --> 00:05:38,970 Now, the reason we have exception management is 180 180 00:05:38,970 --> 00:05:40,620 because otherwise you would be buried 181 181 00:05:40,620 --> 00:05:42,930 in these false positives all of the time. 182 182 00:05:42,930 --> 00:05:45,390 There are things that would require a valid exception, 183 183 00:05:45,390 --> 00:05:48,900 but, again, a thinking analyst needs to go through them, 184 184 00:05:48,900 --> 00:05:50,670 figure out if they should be an exception, 185 185 00:05:50,670 --> 00:05:51,930 and then follow the process 186 186 00:05:51,930 --> 00:05:54,660 to get them added to that exception list. 187 187 00:05:54,660 --> 00:05:56,010 The next category we have is 188 188 00:05:56,010 --> 00:05:57,960 what's known as a true negative. 189 189 00:05:57,960 --> 00:06:00,330 This occurs when an alert is not generated 190 190 00:06:00,330 --> 00:06:03,540 because there is no matching vulnerability on that system. 191 191 00:06:03,540 --> 00:06:05,850 So going back to my pregnancy example, 192 192 00:06:05,850 --> 00:06:07,200 I am a man. 193 193 00:06:07,200 --> 00:06:10,260 If I take one of those tests, I expect it to be negative. 194 194 00:06:10,260 --> 00:06:13,410 If the test comes back negative, that is a true negative. 195 195 00:06:13,410 --> 00:06:16,620 I have a negative result and I am truly not pregnant 196 196 00:06:16,620 --> 00:06:18,810 because I'm a man and I'm not pregnant. 197 197 00:06:18,810 --> 00:06:20,340 Same thing on cybersecurity. 198 198 00:06:20,340 --> 00:06:23,010 For instance, if I scan Windows vulnerabilities 199 199 00:06:23,010 --> 00:06:24,750 against my Mac system, 200 200 00:06:24,750 --> 00:06:26,790 I expect those results to come back negative. 201 201 00:06:26,790 --> 00:06:28,890 There should be nothing found in that report 202 202 00:06:28,890 --> 00:06:30,780 because if I'm scanning a Mac system 203 203 00:06:30,780 --> 00:06:32,010 for Windows vulnerabilities, 204 204 00:06:32,010 --> 00:06:33,510 I should find nothing 205 205 00:06:33,510 --> 00:06:35,610 because there is no Windows environment there 206 206 00:06:35,610 --> 00:06:36,690 for it to scan. 207 207 00:06:36,690 --> 00:06:38,160 That would be a true negative. 208 208 00:06:38,160 --> 00:06:39,600 That's a good thing. 209 209 00:06:39,600 --> 00:06:40,860 Now, the other side of this is 210 210 00:06:40,860 --> 00:06:42,570 what we call a false negative. 211 211 00:06:42,570 --> 00:06:44,700 This is something that's actually really scary for us 212 212 00:06:44,700 --> 00:06:45,723 in the cybersecurity world. 213 213 00:06:45,723 --> 00:06:47,370 When we talk about a false negative, 214 214 00:06:47,370 --> 00:06:49,410 this is an alert that is not generated 215 215 00:06:49,410 --> 00:06:52,740 even though there's a matching vulnerability on the system. 216 216 00:06:52,740 --> 00:06:55,470 So if I go back to my pregnancy example, 217 217 00:06:55,470 --> 00:06:57,180 this would be a really sad case. 218 218 00:06:57,180 --> 00:06:59,250 There's a couple who's been trying to have a baby. 219 219 00:06:59,250 --> 00:07:01,890 They take a pregnancy test and it comes back negative. 220 220 00:07:01,890 --> 00:07:02,723 And they're really sad 221 221 00:07:02,723 --> 00:07:03,870 because they think they're not pregnant. 222 222 00:07:03,870 --> 00:07:05,940 And they've been trying for months and months. 223 223 00:07:05,940 --> 00:07:07,350 Couple more weeks go by, 224 224 00:07:07,350 --> 00:07:10,110 and then we find out that the woman actually is pregnant. 225 225 00:07:10,110 --> 00:07:11,790 Well, she actually was pregnant the whole time, 226 226 00:07:11,790 --> 00:07:13,620 but the test didn't generate a result for it 227 227 00:07:13,620 --> 00:07:15,180 because it didn't detect it. 228 228 00:07:15,180 --> 00:07:17,460 That's what we're talking about here with a false negative. 229 229 00:07:17,460 --> 00:07:18,750 She got a negative result, 230 230 00:07:18,750 --> 00:07:21,090 but she was actually pregnant the whole time. 231 231 00:07:21,090 --> 00:07:22,590 That is a false negative. 232 232 00:07:22,590 --> 00:07:25,080 Now, when we talk about this in the cybersecurity world, 233 233 00:07:25,080 --> 00:07:26,640 we talk about false negatives, 234 234 00:07:26,640 --> 00:07:28,650 meaning that there is a potential vulnerability 235 235 00:07:28,650 --> 00:07:29,520 in that system 236 236 00:07:29,520 --> 00:07:32,250 or there's a missing patch that hasn't been installed 237 237 00:07:32,250 --> 00:07:34,950 and it's not being identified during scanning. 238 238 00:07:34,950 --> 00:07:37,170 That's what makes these so dangerous. 239 239 00:07:37,170 --> 00:07:39,660 The problem here is you don't know you're vulnerable 240 240 00:07:39,660 --> 00:07:42,060 because your report says you're not vulnerable, 241 241 00:07:42,060 --> 00:07:43,170 but yet there's vulnerabilities 242 242 00:07:43,170 --> 00:07:44,790 that really do exist on the system. 243 243 00:07:44,790 --> 00:07:47,520 So this is actually probably the worst of these four cases. 244 244 00:07:47,520 --> 00:07:48,480 So something to keep in mind 245 245 00:07:48,480 --> 00:07:49,620 as you're going through and working 246 246 00:07:49,620 --> 00:07:51,420 as a cybersecurity analyst. 247 247 00:07:51,420 --> 00:07:53,160 Now, what can you do to mitigate the threat 248 248 00:07:53,160 --> 00:07:55,140 of these false negatives? 249 249 00:07:55,140 --> 00:07:57,960 Well, one of the things you can do is run repeated scans. 250 250 00:07:57,960 --> 00:07:59,640 Maybe your scanner was having a bad day 251 251 00:07:59,640 --> 00:08:00,870 and it just didn't catch it. 252 252 00:08:00,870 --> 00:08:02,640 So maybe you want to run another scan 253 253 00:08:02,640 --> 00:08:04,500 and it catches it the second time. 254 254 00:08:04,500 --> 00:08:06,570 Or you might use different scan types, 255 255 00:08:06,570 --> 00:08:08,130 or even a different scanner. 256 256 00:08:08,130 --> 00:08:09,990 So maybe I tried scanning it with Nessus 257 257 00:08:09,990 --> 00:08:10,830 and it didn't pick it up, 258 258 00:08:10,830 --> 00:08:12,300 but now I'm going to scan it with Qualys, 259 259 00:08:12,300 --> 00:08:13,590 and that one did pick it up, 260 260 00:08:13,590 --> 00:08:15,180 or something of that nature. 261 261 00:08:15,180 --> 00:08:16,800 Another thing you might want to do is 262 262 00:08:16,800 --> 00:08:18,510 use different sensitivities. 263 263 00:08:18,510 --> 00:08:20,670 Maybe you are running it in safe mode. 264 264 00:08:20,670 --> 00:08:22,530 Now you're going to run it in not safe mode, 265 265 00:08:22,530 --> 00:08:24,690 which will allow you to do more exploitation there 266 266 00:08:24,690 --> 00:08:26,250 and find additional vulnerabilities 267 267 00:08:26,250 --> 00:08:28,230 that weren't found the first time. 268 268 00:08:28,230 --> 00:08:30,060 Another thing you can do is use a different scanner, 269 269 00:08:30,060 --> 00:08:30,893 like I said. 270 270 00:08:30,893 --> 00:08:33,810 We switch from Nessus to Openvas, or Openvas to Qualys, 271 271 00:08:33,810 --> 00:08:34,950 or Qualys to Nikto, 272 272 00:08:34,950 --> 00:08:36,450 or whatever we want to do. 273 273 00:08:36,450 --> 00:08:37,500 We can use a different scanner 274 274 00:08:37,500 --> 00:08:39,540 and that might give us a better result. 275 275 00:08:39,540 --> 00:08:41,160 Now, we've done all of our scanning. 276 276 00:08:41,160 --> 00:08:44,130 We understand our four types of classifications. 277 277 00:08:44,130 --> 00:08:46,830 Let's start validating our scan reports. 278 278 00:08:46,830 --> 00:08:49,410 When you run a scan, you're going to get a scan report, 279 279 00:08:49,410 --> 00:08:51,060 and they look something like this. 280 280 00:08:51,060 --> 00:08:54,120 They'll give you a nice report with an executive summary, 281 281 00:08:54,120 --> 00:08:55,620 different vulnerabilities by host, 282 282 00:08:55,620 --> 00:08:58,140 and then details on each of those vulnerabilities 283 283 00:08:58,140 --> 00:09:00,870 so you can look at them and then validate them. 284 284 00:09:00,870 --> 00:09:04,020 So once we have our report, we have to validate that report. 285 285 00:09:04,020 --> 00:09:06,390 And there are four things we're going to do to validate it. 286 286 00:09:06,390 --> 00:09:08,670 First, we're going to reconcile the results. 287 287 00:09:08,670 --> 00:09:11,730 Second, we're going to correlate results with other sources. 288 288 00:09:11,730 --> 00:09:14,040 Third, we're going to compare them to best practices. 289 289 00:09:14,040 --> 00:09:16,710 And fourth, we're going to identify exceptions. 290 290 00:09:16,710 --> 00:09:18,990 So first, we want to reconcile these results 291 291 00:09:18,990 --> 00:09:21,600 because the scanners can misinterpret the information 292 292 00:09:21,600 --> 00:09:23,460 that they're receiving from their probes. 293 293 00:09:23,460 --> 00:09:24,780 Again, this is the idea 294 294 00:09:24,780 --> 00:09:27,570 of making sure we identify things as truly positive, 295 295 00:09:27,570 --> 00:09:30,990 false positives, truly negative, or false negatives, 296 296 00:09:30,990 --> 00:09:32,400 and being able to categorize these things 297 297 00:09:32,400 --> 00:09:33,780 as we reconcile those results. 298 298 00:09:33,780 --> 00:09:37,200 That is a big part of a cybersecurity analyst job. 299 299 00:09:37,200 --> 00:09:39,420 Second, we want to correlate the scan results 300 300 00:09:39,420 --> 00:09:40,950 with other data sources. 301 301 00:09:40,950 --> 00:09:44,220 And we do this by reviewing related system and network logs. 302 302 00:09:44,220 --> 00:09:46,357 So if I went and did a scan that says, 303 303 00:09:46,357 --> 00:09:47,610 "Hey, you have a vulnerability. 304 304 00:09:47,610 --> 00:09:50,040 Port 80 is open on this workstation," 305 305 00:09:50,040 --> 00:09:51,600 I'm going to going to go look at that workstation 306 306 00:09:51,600 --> 00:09:53,460 and verify if port 80 is open. 307 307 00:09:53,460 --> 00:09:55,710 And if it is open, is it supposed to be open, 308 308 00:09:55,710 --> 00:09:57,750 because maybe they are running a web server there 309 309 00:09:57,750 --> 00:09:59,280 and they were allowed to do that. 310 310 00:09:59,280 --> 00:10:00,113 If they were, 311 311 00:10:00,113 --> 00:10:02,850 then that might be something we want to add an exception to. 312 312 00:10:02,850 --> 00:10:04,200 Now, the third thing we want to do is 313 313 00:10:04,200 --> 00:10:06,480 compare the results to best practices. 314 314 00:10:06,480 --> 00:10:08,700 This allows to determine if there's a high priority 315 315 00:10:08,700 --> 00:10:11,670 or a low risk associated with this particular finding. 316 316 00:10:11,670 --> 00:10:12,750 Sometimes the findings 317 317 00:10:12,750 --> 00:10:14,550 in your report are going to be informational. 318 318 00:10:14,550 --> 00:10:15,607 It might say something like, 319 319 00:10:15,607 --> 00:10:16,680 "The best practice is 320 320 00:10:16,680 --> 00:10:18,690 not to run web servers from a workstation. 321 321 00:10:18,690 --> 00:10:21,060 You should only do this from a server-based environment 322 322 00:10:21,060 --> 00:10:23,430 like Windows Server 2019." 323 323 00:10:23,430 --> 00:10:24,420 If that's the case, 324 324 00:10:24,420 --> 00:10:25,627 you're going to have to look at that and say, 325 325 00:10:25,627 --> 00:10:27,270 "Yeah, I understand that, 326 326 00:10:27,270 --> 00:10:29,460 but my organization wants to run this web server 327 327 00:10:29,460 --> 00:10:31,290 on Windows 10." 328 328 00:10:31,290 --> 00:10:32,310 And if that's what they want to do 329 329 00:10:32,310 --> 00:10:33,570 and they've accepted the risk, 330 330 00:10:33,570 --> 00:10:35,100 then that's an acceptable thing to do. 331 331 00:10:35,100 --> 00:10:36,387 Just make sure you note it. 332 332 00:10:36,387 --> 00:10:38,310 And that brings us to our fourth category, 333 333 00:10:38,310 --> 00:10:40,380 which is identifying exceptions. 334 334 00:10:40,380 --> 00:10:42,360 Any findings whose risk has been accepted 335 335 00:10:42,360 --> 00:10:45,000 or transferred by the organization can be added 336 336 00:10:45,000 --> 00:10:46,110 to your exception list. 337 337 00:10:46,110 --> 00:10:48,930 This way, those same things don't show up week after week 338 338 00:10:48,930 --> 00:10:50,400 and month after month. 339 339 00:10:50,400 --> 00:10:52,650 This will allow your reports to be smaller in size, 340 340 00:10:52,650 --> 00:10:54,330 quicker to reconcile in the future, 341 341 00:10:54,330 --> 00:10:56,610 and you're not bringing up the same issues to management 342 342 00:10:56,610 --> 00:10:57,720 over and over again 343 343 00:10:57,720 --> 00:10:59,670 that they've already made decisions on.