1 00:00:00,880 --> 00:00:09,799 Speaker 1: Crime Stories with Nancy Grace, Savannah Guthrie's mother, Nancy Guthrie missing. 2 00:00:10,360 --> 00:00:16,800 Speaker 1: New video surfaces of cars flying past in Nancy's neighborhood 3 00:00:17,480 --> 00:00:21,400 Speaker 1: in the critical hours between twelve am and six am, 4 00:00:21,560 --> 00:00:28,600 Speaker 1: significantly one vehicle speeding by just eight minutes after Nancy's 5 00:00:29,200 --> 00:00:34,960 Speaker 1: pacemaker disconnects from bluetooth, flying like a bat out of 6 00:00:35,400 --> 00:00:41,840 Speaker 1: h E double l fly and online sleuths identify a star, 7 00:00:42,440 --> 00:00:47,839 Speaker 1: a small star black or blue in color on the 8 00:00:47,880 --> 00:00:50,520 Speaker 1: porch guy's jacket. 9 00:00:51,320 --> 00:00:52,200 Speaker 2: Is it real? 10 00:00:52,360 --> 00:00:55,800 Speaker 1: And if so, can it be used to track down 11 00:00:56,080 --> 00:01:01,160 Speaker 1: the kidnapper? And in another development AI artificial intelligence, was 12 00:01:01,200 --> 00:01:04,560 Speaker 1: it used to write two of the ransom notes? And 13 00:01:04,600 --> 00:01:08,680 Speaker 1: if so, there's a way to track it? I mean, 14 00:01:08,760 --> 00:01:11,160 Speaker 1: sy Grace, this is Crime Stories. I want to thank 15 00:01:11,200 --> 00:01:23,080 Speaker 1: you for being with us. Dave Matt what is the 16 00:01:23,200 --> 00:01:24,080 Speaker 1: latest in the search? 17 00:01:24,400 --> 00:01:28,080 Speaker 3: Savannah Guthrie took to Instagram and posted a clip from 18 00:01:28,120 --> 00:01:31,920 Speaker 3: The Today Show in a segment about her mom and writes, 19 00:01:32,000 --> 00:01:35,280 Speaker 3: please be the one that brings her home, and she 20 00:01:35,480 --> 00:01:39,039 Speaker 3: also added, you know tips can be anonymous and the 21 00:01:39,160 --> 00:01:42,040 Speaker 3: reward can be paid in cash. I don't think that's 22 00:01:42,040 --> 00:01:45,119 Speaker 3: been said before, but we all know that tips can 23 00:01:45,160 --> 00:01:48,960 Speaker 3: be anonymous if you want, but the reward can be 24 00:01:49,040 --> 00:01:53,560 Speaker 3: paid in cash. She coupled that with releasing a shortened 25 00:01:53,640 --> 00:01:56,840 Speaker 3: version of what Should the Family released the other day, 26 00:01:56,840 --> 00:02:01,640 Speaker 3: but Savannah Guthrie reminding everyone that tips are anonymous and 27 00:02:01,680 --> 00:02:03,520 Speaker 3: the reward can be paid in cash. 28 00:02:03,960 --> 00:02:10,400 Speaker 1: New video surfaces of cars flying past in Nancy's neighborhood. 29 00:02:11,040 --> 00:02:16,600 Speaker 1: That video found on a neighbor's cam, the door cam, 30 00:02:16,880 --> 00:02:19,960 Speaker 1: the surveillance video at the edge of their yard, also 31 00:02:20,440 --> 00:02:26,440 Speaker 1: catching twelve vehicles flying by at the time Nancy Guthrie 32 00:02:26,680 --> 00:02:27,440 Speaker 1: is kidnapped. 33 00:02:27,800 --> 00:02:29,680 Speaker 2: Dave Matt what are we seeing. 34 00:02:29,440 --> 00:02:33,040 Speaker 3: Well, you're actually seeing ring camera footage of a car 35 00:02:33,600 --> 00:02:36,600 Speaker 3: about two thirty six in the morning, and Nancy, this 36 00:02:36,800 --> 00:02:39,840 Speaker 3: is a home located about two and a half miles 37 00:02:39,919 --> 00:02:44,040 Speaker 3: from Nancy Guthrie's home. It's a back road that leads 38 00:02:44,160 --> 00:02:47,280 Speaker 3: out of her neighborhood and it doesn't see a lot 39 00:02:47,320 --> 00:02:51,680 Speaker 3: of traffic, not on a regular basis. Between midnight and 40 00:02:51,800 --> 00:02:56,160 Speaker 3: six am February first, about twelve cars went down that 41 00:02:56,360 --> 00:02:57,680 Speaker 3: road in front of this camera. 42 00:02:58,240 --> 00:02:59,360 Speaker 2: But right there. 43 00:03:00,600 --> 00:03:05,120 Speaker 3: Eight am a car goes flying by that camera. Nancy, 44 00:03:05,480 --> 00:03:09,240 Speaker 3: that would be enough time from the time or two 45 00:03:09,320 --> 00:03:13,560 Speaker 3: thirty six am. I apologize. Eight minutes after Nancy Guthrie's 46 00:03:13,600 --> 00:03:18,359 Speaker 3: pacemaker connected via bluetooth to her Apple Watch, that car 47 00:03:18,440 --> 00:03:22,440 Speaker 3: goes flying by that ring doorbell camera and you can 48 00:03:22,440 --> 00:03:26,200 Speaker 3: see it. It's heading away. So that's what we're looking at, 49 00:03:26,240 --> 00:03:30,360 Speaker 3: and that is really important that it's just outside of 50 00:03:30,400 --> 00:03:33,959 Speaker 3: that two mile radius that law enforcement put up as 51 00:03:34,000 --> 00:03:36,600 Speaker 3: the search area. This is two and a half miles 52 00:03:37,120 --> 00:03:39,640 Speaker 3: but there it goes right there, away from the. 53 00:03:39,640 --> 00:03:43,280 Speaker 1: Neighborhood, straight out to Brian Fitzgibbons, joining US Director Operations 54 00:03:43,440 --> 00:03:49,560 Speaker 1: USPA Nationwide Security. He leads a team of investigators, seasoned 55 00:03:49,680 --> 00:03:52,440 Speaker 1: investigators that find missing people. 56 00:03:52,240 --> 00:03:53,840 Speaker 4: All around the world. 57 00:03:54,840 --> 00:04:03,680 Speaker 1: Former marine Iraqi war vet one expertise extracting people from Mexico. Brian, 58 00:04:03,720 --> 00:04:05,560 Speaker 1: thank you for being with us. What do you make 59 00:04:05,720 --> 00:04:06,360 Speaker 1: of the video? 60 00:04:06,920 --> 00:04:11,520 Speaker 5: Yeah, this is a really good development here in this case. 61 00:04:11,680 --> 00:04:15,440 Speaker 5: And what you see is as this search is expanding 62 00:04:15,520 --> 00:04:18,320 Speaker 5: beyond the crime scene, this is two and a half 63 00:04:18,360 --> 00:04:22,240 Speaker 5: miles away from missus Guthrie's house. This is just a 64 00:04:22,400 --> 00:04:26,400 Speaker 5: sampling of the leads that the FBI and PMA County 65 00:04:26,440 --> 00:04:29,800 Speaker 5: have developed, and I want to mention that they are 66 00:04:29,880 --> 00:04:35,960 Speaker 5: currently analyzing over ten thousand hours of surveillance video. So 67 00:04:36,040 --> 00:04:39,720 Speaker 5: this is one small tip of the iceberg here that 68 00:04:39,800 --> 00:04:42,479 Speaker 5: we're seeing. But they're going to start tracking down this 69 00:04:42,600 --> 00:04:46,640 Speaker 5: vehicle as it was in the area at the right time. 70 00:04:47,160 --> 00:04:49,680 Speaker 5: This is certainly a great lead for investigators. 71 00:04:50,120 --> 00:04:54,040 Speaker 1: Todd Shipley joining US digital cybercrime expert former Detective Sergeant 72 00:04:54,120 --> 00:04:59,400 Speaker 1: Reno PD, twenty five years in law enforcement, author of 73 00:04:59,440 --> 00:05:05,000 Speaker 1: Survive Being a Cyber Attack, also author investigating Internet crimes. 74 00:05:05,839 --> 00:05:10,320 Speaker 1: You can find him at dark intel dot info. Todd Schiffley, 75 00:05:10,360 --> 00:05:10,680 Speaker 1: thank you. 76 00:05:10,640 --> 00:05:11,320 Speaker 2: For being with us. 77 00:05:11,440 --> 00:05:15,080 Speaker 1: How will the fans go about enhancing this video? 78 00:05:15,400 --> 00:05:17,880 Speaker 6: Well, they're going to take the screenshots out of it 79 00:05:17,920 --> 00:05:20,360 Speaker 6: and try to figure out what they can find from 80 00:05:20,400 --> 00:05:24,240 Speaker 6: that one particular shot and identify if there's anything that's 81 00:05:24,360 --> 00:05:27,440 Speaker 6: usable in that shot. It's a pretty quick shot that's moving, 82 00:05:27,560 --> 00:05:29,800 Speaker 6: so it's not something that's going to be an easy 83 00:05:29,839 --> 00:05:32,000 Speaker 6: thing to do, but they're going to take that video 84 00:05:32,320 --> 00:05:35,039 Speaker 6: in the stills and try to enhance whatever they can 85 00:05:35,440 --> 00:05:41,240 Speaker 6: to find anything descriptions, bumper stickers, the license plate obviously, 86 00:05:41,720 --> 00:05:43,800 Speaker 6: if they can figure any of that out. The year 87 00:05:43,800 --> 00:05:46,720 Speaker 6: making model obviously is important because then they can start 88 00:05:46,760 --> 00:05:49,960 Speaker 6: tracking down who owns those in the state and try 89 00:05:50,000 --> 00:05:53,760 Speaker 6: to figure out, you know what potential list of suspects 90 00:05:53,800 --> 00:05:56,159 Speaker 6: they might have who own that kind of car, and 91 00:05:56,200 --> 00:05:57,760 Speaker 6: then start contacting each one. 92 00:05:57,960 --> 00:06:01,839 Speaker 2: Straight back to Brian Fitzgibbons. Brian Mani. 93 00:06:01,920 --> 00:06:06,560 Speaker 1: Online sleuths have identified the vehicle as being a Kia Soul. 94 00:06:07,000 --> 00:06:10,159 Speaker 1: Let's see the mock up of the Kia Soul now, Brian, 95 00:06:10,400 --> 00:06:13,560 Speaker 1: As you and I have discussed on many many occasions, 96 00:06:14,720 --> 00:06:20,839 Speaker 1: car manufacturers change, either ostensibly or subtly, the design of 97 00:06:20,880 --> 00:06:26,360 Speaker 1: a car nearly every year, and that appeals to those 98 00:06:26,400 --> 00:06:28,560 Speaker 1: individuals that like to buy a new car every year 99 00:06:28,600 --> 00:06:32,640 Speaker 1: and always drive a new car. That said, it can 100 00:06:32,680 --> 00:06:36,320 Speaker 1: be subtle or very obvious. It can be a tilt 101 00:06:36,400 --> 00:06:39,480 Speaker 1: up in the front lights. It can be a change 102 00:06:39,480 --> 00:06:41,800 Speaker 1: in the number of tail lights. It can be any 103 00:06:41,920 --> 00:06:47,000 Speaker 1: number of things, a subtle slope in the front windshield. 104 00:06:47,440 --> 00:06:50,039 Speaker 1: But the point is, isn't it true? 105 00:06:50,279 --> 00:06:50,960 Speaker 2: Fitz Gibbons. 106 00:06:52,200 --> 00:06:57,839 Speaker 1: Major metropolitan areas New York, Chicago, La Atlanta. They've got, 107 00:06:57,839 --> 00:07:01,200 Speaker 1: of course, homicide, they've got robbery, they've got crimes on children, 108 00:07:01,240 --> 00:07:04,440 Speaker 1: They've got six crimes, they've got white collar crimes. They 109 00:07:04,520 --> 00:07:09,560 Speaker 1: have an entire fleet of people investigators, they deal with 110 00:07:09,720 --> 00:07:15,840 Speaker 1: nothing but car theft and recovery, often busting wide open 111 00:07:16,000 --> 00:07:19,520 Speaker 1: car theft rings that make millions and millions of dollars 112 00:07:19,560 --> 00:07:23,440 Speaker 1: a year. Those guys and ladies can look at a 113 00:07:23,480 --> 00:07:26,240 Speaker 1: car at a distance and tell you, oh, yeah, that's 114 00:07:26,280 --> 00:07:28,360 Speaker 1: a Kia Soul, that's a twenty twenty four. 115 00:07:28,640 --> 00:07:31,000 Speaker 4: And this is how I know it. How do they 116 00:07:31,040 --> 00:07:31,280 Speaker 4: do it? 117 00:07:31,360 --> 00:07:36,200 Speaker 5: Mis Gibbons, Oh absolutely, and that's from thousands of hours 118 00:07:36,240 --> 00:07:41,560 Speaker 5: of surveillance on the job that they're finally tuned to 119 00:07:41,920 --> 00:07:46,160 Speaker 5: identified make model a year. And what I will say is, 120 00:07:46,400 --> 00:07:51,720 Speaker 5: you know, while this video is not necessarily the highest 121 00:07:51,760 --> 00:07:54,360 Speaker 5: resolution that you would want, a lot of those key 122 00:07:54,440 --> 00:07:57,840 Speaker 5: identifiers are there, the shape of the windows, the locations 123 00:07:57,840 --> 00:08:00,360 Speaker 5: of the tail lights. They can get a relative height 124 00:08:00,400 --> 00:08:03,520 Speaker 5: and size of the tires, size of the vehicle in general. 125 00:08:03,640 --> 00:08:06,880 Speaker 5: So a lot can be deduced from this, and I 126 00:08:06,920 --> 00:08:09,720 Speaker 5: think that their assumptions would be pretty accurate. 127 00:08:09,720 --> 00:08:15,560 Speaker 2: Here, guys, let's take another look at the video. How 128 00:08:15,840 --> 00:08:18,840 Speaker 2: do they do it? How do they enhance it? 129 00:08:19,960 --> 00:08:23,840 Speaker 1: It's amazing to me, but it's been done over and 130 00:08:23,880 --> 00:08:26,640 Speaker 1: over and over. You think you can't see a tag, 131 00:08:27,200 --> 00:08:30,160 Speaker 1: they may find a way to find that tag. Although 132 00:08:30,960 --> 00:08:34,880 Speaker 1: typically in an operation like this Shipley, I doubt the 133 00:08:34,920 --> 00:08:38,080 Speaker 1: person has their true tag, if any tag on the 134 00:08:38,080 --> 00:08:41,280 Speaker 1: back of the car or the front Shipley in mind. 135 00:08:41,240 --> 00:08:47,160 Speaker 6: That any part of that identification can be important, the color, 136 00:08:47,679 --> 00:08:50,160 Speaker 6: the making model. Like we said, they're going to be 137 00:08:50,160 --> 00:08:53,000 Speaker 6: able to go to the D and B locally and 138 00:08:53,080 --> 00:08:56,960 Speaker 6: identify who has that. If it's a thousand cars, if 139 00:08:57,000 --> 00:09:00,720 Speaker 6: there's one distinctive feature that can limit the that they've 140 00:09:00,760 --> 00:09:03,240 Speaker 6: got to research, then they'll knock that down and that 141 00:09:03,320 --> 00:09:05,000 Speaker 6: can go after those people. But even if it's a 142 00:09:05,000 --> 00:09:07,400 Speaker 6: thousand cars, they've got to try to figure out where 143 00:09:07,440 --> 00:09:10,640 Speaker 6: those people are in this case because of what's happened, 144 00:09:10,880 --> 00:09:14,040 Speaker 6: and identify who was there and whether they potentially were 145 00:09:14,080 --> 00:09:15,240 Speaker 6: in that city or not. 146 00:09:16,200 --> 00:09:18,560 Speaker 1: And don't think you've gotten away with anything if this 147 00:09:18,720 --> 00:09:22,760 Speaker 1: is you in this vehicle, because Brian Fus Gibbons, you 148 00:09:22,800 --> 00:09:27,080 Speaker 1: and I have covered together and investigated many others separately. 149 00:09:26,920 --> 00:09:30,079 Speaker 4: Of cases that were cracked by the vehicle. 150 00:09:30,160 --> 00:09:31,160 Speaker 2: And here are just a few. 151 00:09:31,240 --> 00:09:33,960 Speaker 1: Okay, of course, the poster boy for so many evil 152 00:09:34,080 --> 00:09:35,960 Speaker 1: and nefarious things, Brian Coburger. 153 00:09:36,800 --> 00:09:38,319 Speaker 4: That whole case started. 154 00:09:38,679 --> 00:09:44,640 Speaker 1: The identification of Coburger started with a it's not a 155 00:09:44,640 --> 00:09:47,200 Speaker 1: circle k not a quick trip. I went to the 156 00:09:47,240 --> 00:09:52,400 Speaker 1: gas station. A clerk at the gas station takes it 157 00:09:52,480 --> 00:09:55,800 Speaker 1: upon herself to come through hours and hours of video, 158 00:09:56,200 --> 00:10:00,720 Speaker 1: she spots a white Alantra flying by. Had been to 159 00:10:00,760 --> 00:10:03,600 Speaker 1: the King Road address where the murders occurred. To get there, 160 00:10:03,880 --> 00:10:06,640 Speaker 1: you come to an intersection and over on the left 161 00:10:07,400 --> 00:10:08,400 Speaker 1: is this gas station. 162 00:10:09,320 --> 00:10:10,560 Speaker 2: You go up the hill. 163 00:10:10,400 --> 00:10:12,480 Speaker 1: And go down a very circuitous route to get to 164 00:10:12,559 --> 00:10:15,360 Speaker 1: the eleven twenty two King Road address. God said, that's 165 00:10:15,400 --> 00:10:18,480 Speaker 1: the only way to get in there. She finds a 166 00:10:18,480 --> 00:10:21,640 Speaker 1: white Alauntra speeding by around four o'clock in the morning, 167 00:10:22,280 --> 00:10:27,280 Speaker 1: and she alerts police. They in turn alert all police 168 00:10:27,280 --> 00:10:31,400 Speaker 1: forces around them, including campus police, including Washington State University 169 00:10:31,440 --> 00:10:37,360 Speaker 1: in Pullman. The Washington State University Police. Campus police go 170 00:10:37,400 --> 00:10:39,360 Speaker 1: through all the records and they go, oh, white Elantra. 171 00:10:39,880 --> 00:10:42,480 Speaker 1: Who has a white Alaunchra that's registered, you know with 172 00:10:42,559 --> 00:10:43,680 Speaker 1: a car sticker? 173 00:10:43,720 --> 00:10:45,720 Speaker 2: Here, Oh, Brian Coburger's one. 174 00:10:45,840 --> 00:10:47,760 Speaker 1: They go to his place, they see the car, they 175 00:10:47,800 --> 00:10:50,640 Speaker 1: take a picture, and that's how the name first comes up, 176 00:10:50,880 --> 00:10:54,760 Speaker 1: Brian Coburger. Then there's a Molly Tibbets case. In the 177 00:10:54,760 --> 00:10:58,840 Speaker 1: Molly Tibbitts case, she is a gorgeous young coed studying late. 178 00:11:00,000 --> 00:11:02,480 Speaker 2: He goes out for a jog. She's murdered. 179 00:11:03,360 --> 00:11:06,400 Speaker 1: You know how they find the purp through distinctive markings 180 00:11:06,400 --> 00:11:12,160 Speaker 1: on his vehicle taken from a door cam as he 181 00:11:12,240 --> 00:11:15,400 Speaker 1: drives by. He kept driving by her, back and forth, 182 00:11:15,440 --> 00:11:18,000 Speaker 1: trying to engage her in conversation. When she says, I'm 183 00:11:18,040 --> 00:11:20,640 Speaker 1: calling nine one one, buddy, he kills her. 184 00:11:21,080 --> 00:11:21,760 Speaker 2: And in the. 185 00:11:22,000 --> 00:11:26,440 Speaker 1: Recent history, bryf It's Gibbons, the Teppie murders. You and 186 00:11:26,520 --> 00:11:28,800 Speaker 1: I have come through that case with a fine tooth comb. 187 00:11:29,240 --> 00:11:34,440 Speaker 1: Remember beautiful Monique and her husband dead in their beds. 188 00:11:35,679 --> 00:11:40,040 Speaker 1: Brayf It's Gibbons, the purp who has been arrested, not 189 00:11:40,160 --> 00:11:46,600 Speaker 1: convicted yet. Doctor Michael McKee on his first of all 190 00:11:46,679 --> 00:11:51,160 Speaker 1: surveillance video catches him in the area tag plates he 191 00:11:51,200 --> 00:11:54,360 Speaker 1: had stolen tags switched him out. But guess what was 192 00:11:54,400 --> 00:11:56,679 Speaker 1: on his car. You're going to love this Where he 193 00:11:56,720 --> 00:11:59,760 Speaker 1: worked at the hospital. The sticker was still in the 194 00:11:59,760 --> 00:12:03,440 Speaker 1: car when they get to the car. Finally, he scratched it. 195 00:12:03,480 --> 00:12:07,439 Speaker 4: Off, ding ding ding, red bell of alarm. 196 00:12:07,679 --> 00:12:10,800 Speaker 1: Why scratch off your parking sticker? So you heard what 197 00:12:10,840 --> 00:12:13,679 Speaker 1: Shipley just said. It may not be the tag. It 198 00:12:13,720 --> 00:12:16,840 Speaker 1: may be a sticker, It may be an identifiable scratch 199 00:12:16,880 --> 00:12:17,880 Speaker 1: along the side. 200 00:12:17,640 --> 00:12:19,840 Speaker 2: Of the vehicle. It could be anything that s Gibbons 201 00:12:19,920 --> 00:12:20,640 Speaker 2: helped me out. 202 00:12:20,440 --> 00:12:25,760 Speaker 5: Here absolutely time and again, the vehicle is the lynchpin 203 00:12:26,000 --> 00:12:30,960 Speaker 5: to cracking a case wide open. You just listed off 204 00:12:30,960 --> 00:12:33,880 Speaker 5: a litany of those such cases, and I think what 205 00:12:33,960 --> 00:12:37,480 Speaker 5: we're seeing here with all of this video, this new 206 00:12:37,559 --> 00:12:41,760 Speaker 5: video that's been collected as of yesterday and now there 207 00:12:41,800 --> 00:12:45,280 Speaker 5: will be thousands of hours of more video in with 208 00:12:45,320 --> 00:12:50,960 Speaker 5: this new reward up to over one million dollars, this 209 00:12:51,080 --> 00:12:52,360 Speaker 5: vehicle could crack the case. 210 00:12:52,360 --> 00:13:02,359 Speaker 4: So crime Stories with Nancy Grace. 211 00:13:06,840 --> 00:13:07,560 Speaker 2: Todd Shipley. 212 00:13:08,240 --> 00:13:13,240 Speaker 1: If a civilian can identify this as being a kisol, 213 00:13:14,200 --> 00:13:18,320 Speaker 1: what can the FEDS do a lot more? We have 214 00:13:18,400 --> 00:13:22,400 Speaker 1: seen them enhanced video like nobody's business. I mean, it's 215 00:13:22,720 --> 00:13:27,880 Speaker 1: possible and everybody tonight. There are reports this is connected 216 00:13:27,920 --> 00:13:31,239 Speaker 1: to Guthrie. There are reports it's not connected to Guthrie, 217 00:13:31,400 --> 00:13:35,960 Speaker 1: all citing FBI sources. We don't know the answer, but 218 00:13:36,120 --> 00:13:40,400 Speaker 1: todd Shipley in reality not guessing. 219 00:13:40,000 --> 00:13:41,679 Speaker 2: Whether this is going to be connected or not. 220 00:13:42,240 --> 00:13:45,959 Speaker 1: I don't quite understand the process of how they can 221 00:13:46,040 --> 00:13:49,240 Speaker 1: lighten the picture how they can zoom in, how do 222 00:13:49,320 --> 00:13:52,080 Speaker 1: they do it? And have you ever been part of 223 00:13:52,520 --> 00:13:54,920 Speaker 1: catching a purp through the car? 224 00:13:56,640 --> 00:13:59,880 Speaker 6: Well, you know the fact that the FBI has got 225 00:14:00,000 --> 00:14:03,800 Speaker 6: digital forensic experts and video experts that can do this, 226 00:14:03,920 --> 00:14:07,360 Speaker 6: it is something that you know is well known. They've 227 00:14:07,360 --> 00:14:10,440 Speaker 6: been parsing through this. I don't know that they've got 228 00:14:10,440 --> 00:14:12,080 Speaker 6: the speed to be able to do the things that 229 00:14:12,160 --> 00:14:16,720 Speaker 6: people do online when they do a community driven review 230 00:14:16,760 --> 00:14:19,080 Speaker 6: of these things, I want to say, release the video. 231 00:14:19,560 --> 00:14:21,960 Speaker 6: People are looking at this trying to identify things and 232 00:14:22,000 --> 00:14:24,680 Speaker 6: matching things at a speed that we've never seen before 233 00:14:24,680 --> 00:14:28,240 Speaker 6: in law enforcement because this whole community driven, you know, 234 00:14:28,400 --> 00:14:33,880 Speaker 6: approach to identifying information in these videos and photos is 235 00:14:34,040 --> 00:14:37,040 Speaker 6: changed how law enforcement has to look at this. And 236 00:14:37,120 --> 00:14:40,440 Speaker 6: sometimes they're on their heels trying to catch up with 237 00:14:40,480 --> 00:14:43,280 Speaker 6: what the community is doing viause the communities identifying stuff 238 00:14:43,560 --> 00:14:47,480 Speaker 6: sometimes correctly, sometimes incorrectly, and then they've got to spend 239 00:14:47,520 --> 00:14:50,280 Speaker 6: time trying to figure out whether what the public is 240 00:14:50,320 --> 00:14:53,080 Speaker 6: saying is pricked or not. That can take away from 241 00:14:53,080 --> 00:14:55,280 Speaker 6: what they're doing. So sometimes it's hard to do that, 242 00:14:55,560 --> 00:14:57,320 Speaker 6: but they've got the skills to be able to get 243 00:14:57,320 --> 00:15:00,800 Speaker 6: the information and identify what's there and. 244 00:15:00,840 --> 00:15:05,920 Speaker 1: Tonight to Dave Matt Crime Story's investigative reporter. According to 245 00:15:06,000 --> 00:15:11,880 Speaker 1: Sleuth's a star is visible on the porch guy the 246 00:15:11,920 --> 00:15:17,680 Speaker 1: perpetrator's jacket near his there you go, thank you, near 247 00:15:17,840 --> 00:15:19,760 Speaker 1: the backpack strap. 248 00:15:19,920 --> 00:15:21,280 Speaker 2: What do we know, Dave mac. 249 00:15:21,680 --> 00:15:25,200 Speaker 3: Well, we know exactly that you're looking at the photo there, Nancy, 250 00:15:25,240 --> 00:15:30,280 Speaker 3: and it looks like there could be a star on 251 00:15:30,480 --> 00:15:36,240 Speaker 3: that backpack strap. But when there are other photos that 252 00:15:36,560 --> 00:15:39,720 Speaker 3: don't show anything, So what we're looking at I think 253 00:15:39,800 --> 00:15:41,960 Speaker 3: is a shadow from what he's holding up in front 254 00:15:41,960 --> 00:15:44,360 Speaker 3: of the camera. If it's not a shadow, if it 255 00:15:44,440 --> 00:15:48,040 Speaker 3: really is a black or blue star on that strap, 256 00:15:48,320 --> 00:15:52,800 Speaker 3: well that adds to our ability to identify this particular person. 257 00:15:53,160 --> 00:15:57,720 Speaker 3: Because we know that we know the brand of this backpack, 258 00:15:58,400 --> 00:16:01,120 Speaker 3: we can search the brand and see if any of 259 00:16:01,160 --> 00:16:03,000 Speaker 3: these backpacks come with a star. 260 00:16:03,160 --> 00:16:05,760 Speaker 1: I would have nothing to do with the star. The 261 00:16:05,800 --> 00:16:08,280 Speaker 1: star is on the jacket, Isn't that right, Dave. 262 00:16:09,320 --> 00:16:11,880 Speaker 3: I'm looking at it and it's either on the strap 263 00:16:12,000 --> 00:16:15,560 Speaker 3: round the jacket, Nancy. It appears to me. 264 00:16:16,000 --> 00:16:18,479 Speaker 2: It looks to me like it's on the jacket. 265 00:16:18,760 --> 00:16:21,560 Speaker 1: What about it, Brian fitz Gibbons, And how would we 266 00:16:21,760 --> 00:16:25,920 Speaker 1: use that star if it's real to punt to find 267 00:16:25,920 --> 00:16:26,320 Speaker 1: the purpose. 268 00:16:27,000 --> 00:16:29,800 Speaker 5: Yeah, this looks like it's on the jacket, and you know, 269 00:16:29,880 --> 00:16:33,320 Speaker 5: I'll say two things first that this is either a 270 00:16:33,360 --> 00:16:36,960 Speaker 5: brand of jackets, so it will help us identify exactly, 271 00:16:37,400 --> 00:16:40,280 Speaker 5: you know, what item that is. You know, the FBI 272 00:16:40,400 --> 00:16:42,600 Speaker 5: can do their thing to track down where the purchase 273 00:16:42,680 --> 00:16:46,320 Speaker 5: might have taken place. Better yet, it could be a 274 00:16:46,400 --> 00:16:50,720 Speaker 5: custom embroidered piece for a business or a school or 275 00:16:50,720 --> 00:16:54,080 Speaker 5: something like that. And if it is a custom made piece, 276 00:16:54,200 --> 00:16:58,000 Speaker 5: that's going to really narrow things down for us, because 277 00:16:58,400 --> 00:17:01,800 Speaker 5: these items aren't one of one, right, There'll be fifty 278 00:17:01,880 --> 00:17:05,159 Speaker 5: mad or one hundred and twenty made, and you know, 279 00:17:05,200 --> 00:17:07,160 Speaker 5: people will be able to quickly identify that. 280 00:17:08,320 --> 00:17:11,479 Speaker 1: This post that we are showing you is from trill 281 00:17:11,880 --> 00:17:16,800 Speaker 1: Tril on X. Video from Nancy Guthrie's home obviously shows 282 00:17:16,840 --> 00:17:19,800 Speaker 1: a mass suspect, the eighty four year old taken out 283 00:17:19,800 --> 00:17:24,040 Speaker 1: of her home, but now a distinguishing mark on the jacket. 284 00:17:24,600 --> 00:17:28,960 Speaker 2: Is it real? Is it a shadow? Take a look. 285 00:17:29,040 --> 00:17:32,480 Speaker 1: The FBI working on the case released this video footage 286 00:17:32,480 --> 00:17:36,159 Speaker 1: the night Nancy Guthrie was taken. And now, what do 287 00:17:36,200 --> 00:17:41,280 Speaker 1: we know about a black star? On the jacket, an 288 00:17:41,320 --> 00:17:46,040 Speaker 1: individual spots it and immediately it hits the internet like 289 00:17:46,359 --> 00:17:51,160 Speaker 1: wild fire. I'm trying to figure out how the FEDS 290 00:17:51,200 --> 00:17:55,760 Speaker 1: are going to go about isolating this, determining if it's real, 291 00:17:56,359 --> 00:18:01,800 Speaker 1: and then finding it in their vast FBI a texture 292 00:18:02,320 --> 00:18:07,800 Speaker 1: and clothing database that they keep, and in that they 293 00:18:07,920 --> 00:18:11,760 Speaker 1: input everything from prior cases, whether it turned out to 294 00:18:11,760 --> 00:18:15,320 Speaker 1: be real or not connected to the case or not. Example, 295 00:18:15,880 --> 00:18:19,879 Speaker 1: in the Wayne Williams serial killings of young men throughout Atlanta. 296 00:18:19,800 --> 00:18:23,240 Speaker 4: The case was cracked by first time ever out. 297 00:18:23,160 --> 00:18:25,639 Speaker 1: Of my old district attorney's office the use of fiber 298 00:18:25,720 --> 00:18:30,160 Speaker 1: comparisons on the bodies of many of the young boys 299 00:18:30,240 --> 00:18:34,400 Speaker 1: and teen victims. There were odd fibers that were later 300 00:18:34,480 --> 00:18:38,679 Speaker 1: traced back to the carpet in Wayne Williams's parents' home 301 00:18:39,280 --> 00:18:41,040 Speaker 1: and the carpet. 302 00:18:40,960 --> 00:18:44,560 Speaker 2: In his vehicle where he would put the bodies. 303 00:18:44,160 --> 00:18:47,760 Speaker 1: After killing them, just before disposing of them in the 304 00:18:47,800 --> 00:18:48,680 Speaker 1: Chattahoochee River. 305 00:18:49,720 --> 00:18:52,400 Speaker 2: So the FBI has a huge. 306 00:18:52,280 --> 00:18:57,600 Speaker 1: Database of all sorts of materials, clothing, textures, you name it, 307 00:18:57,840 --> 00:19:00,639 Speaker 1: and I guarantee you if this is real, they're pouring 308 00:19:00,680 --> 00:19:04,520 Speaker 1: through it right now. Straight back out to Dave Matt, 309 00:19:04,640 --> 00:19:08,080 Speaker 1: what can you tell me about the guy that drives 310 00:19:08,080 --> 00:19:10,960 Speaker 1: by Nancy Guthrie's home in the dark of the night 311 00:19:11,320 --> 00:19:14,480 Speaker 1: up to one hundred times, all the time staring at 312 00:19:14,480 --> 00:19:15,760 Speaker 1: a photo of her. 313 00:19:16,359 --> 00:19:18,040 Speaker 4: In the car. Nancy. 314 00:19:18,240 --> 00:19:22,080 Speaker 3: Late yesterday afternoon into the early evening hours, a man 315 00:19:22,440 --> 00:19:26,679 Speaker 3: was driving his vehicle on Nancy Guthrie Street, right in 316 00:19:26,680 --> 00:19:30,200 Speaker 3: front of her house. And he's driving by really slow 317 00:19:30,320 --> 00:19:33,640 Speaker 3: while he's looking at a picture of Nancy Guthrie on 318 00:19:33,720 --> 00:19:37,240 Speaker 3: his phone. Now we're not talking three or four times 319 00:19:37,320 --> 00:19:39,679 Speaker 3: driving up and down the street. We're talking about the 320 00:19:39,720 --> 00:19:42,600 Speaker 3: guy doing it for a long time, fifty to one 321 00:19:42,720 --> 00:19:46,639 Speaker 3: hundred times, driving in front of her house. All the 322 00:19:46,680 --> 00:19:49,959 Speaker 3: while and I'm going really, really slow. He's creeping along 323 00:19:50,160 --> 00:19:52,800 Speaker 3: looking at a picture of Nancy Guthrie on his phone. 324 00:19:53,080 --> 00:19:56,280 Speaker 3: So finally police decided it's time to take a look 325 00:19:56,320 --> 00:19:59,000 Speaker 3: at this guy, and they pull him over and police 326 00:19:59,119 --> 00:20:04,200 Speaker 3: arrest thirty f four year old Antonio DeJesus Peana compos 327 00:20:04,200 --> 00:20:13,760 Speaker 3: in front of Nancy Guthrie's home on misdemeanor DUI charges. 328 00:20:15,440 --> 00:20:17,359 Speaker 4: Crime Stories with Nancy Grace. 329 00:20:21,600 --> 00:20:26,560 Speaker 1: Joining us now Heather Barnhardt, digital forensics expert with Celebright. 330 00:20:27,320 --> 00:20:30,200 Speaker 1: You heard all about that during the Alexi Murdog trunk 331 00:20:30,640 --> 00:20:34,040 Speaker 1: in the Alex Murdog trial, the case Wide Open, and 332 00:20:34,160 --> 00:20:40,560 Speaker 1: the Sands Institute System Admin Audit, Network and Security. She 333 00:20:40,920 --> 00:20:43,840 Speaker 1: worked on the Brian Coburger case. She is a co 334 00:20:43,920 --> 00:20:50,639 Speaker 1: author of Practical Mobile Forensics, now in its fourth edition. Wow, Heather, 335 00:20:50,920 --> 00:20:52,760 Speaker 1: thank you for being with us, Heather. I want to 336 00:20:52,800 --> 00:20:55,639 Speaker 1: talk to you about the so called ransom notes. 337 00:20:56,280 --> 00:20:56,560 Speaker 2: Heather. 338 00:20:57,800 --> 00:21:02,119 Speaker 1: Is there anything about these rants notes that would suggest 339 00:21:02,480 --> 00:21:05,240 Speaker 1: that they were AI generated and what are your thoughts 340 00:21:05,240 --> 00:21:06,200 Speaker 1: about tracking that? 341 00:21:07,240 --> 00:21:11,439 Speaker 7: One thing I want investigators to think about in this 342 00:21:11,600 --> 00:21:16,199 Speaker 7: case are those ransom letters. And I remember reading and 343 00:21:16,320 --> 00:21:18,399 Speaker 7: hearing on TMZ that one of them seemed to be 344 00:21:18,440 --> 00:21:22,840 Speaker 7: written by a professional. Why was that one different? If 345 00:21:23,520 --> 00:21:26,240 Speaker 7: AI was used to help write a ransom note, which 346 00:21:26,280 --> 00:21:29,440 Speaker 7: is likely, so think about the Google searches that came 347 00:21:29,480 --> 00:21:33,320 Speaker 7: out that so many IP addresses had searched for Nancy Guthrie. 348 00:21:33,600 --> 00:21:35,520 Speaker 7: Who would know her name, who would know where she 349 00:21:35,600 --> 00:21:39,960 Speaker 7: lived prior to the kidnapping? Can you find keywords in 350 00:21:40,080 --> 00:21:43,639 Speaker 7: open AI that's available to the public that can be 351 00:21:43,720 --> 00:21:48,000 Speaker 7: searched for anything that was written specifically in those ransom notes? 352 00:21:48,440 --> 00:21:51,400 Speaker 7: And if the answer is yes, this could tie back 353 00:21:51,840 --> 00:21:54,440 Speaker 7: to a location and to a person in their home 354 00:21:54,760 --> 00:21:57,960 Speaker 7: who potentially was behind that keyboard typing those unique words. 355 00:21:58,560 --> 00:22:02,760 Speaker 1: Wow, I hadn't thought of that. Whether that's pretty amazing. 356 00:22:03,520 --> 00:22:09,280 Speaker 1: What about if a VPN was being used, If. 357 00:22:09,119 --> 00:22:13,320 Speaker 7: The person wasn't using some type of VPN and private 358 00:22:13,400 --> 00:22:17,600 Speaker 7: browsing and all the things that mask you from where 359 00:22:17,640 --> 00:22:20,399 Speaker 7: you're existing when you're typing things, then yes we can 360 00:22:20,520 --> 00:22:23,159 Speaker 7: find them. But keep in mind Brian Coberger tried to 361 00:22:23,200 --> 00:22:26,439 Speaker 7: do this and we still found him. So there is 362 00:22:26,520 --> 00:22:30,200 Speaker 7: always going to be a misstep that digital evidence will 363 00:22:30,280 --> 00:22:32,720 Speaker 7: lead back to the person. But if they didn't do 364 00:22:32,760 --> 00:22:34,560 Speaker 7: this and you just open a browser and you start 365 00:22:34,600 --> 00:22:38,160 Speaker 7: googling things, absolutely that can be used the exact same 366 00:22:38,200 --> 00:22:40,359 Speaker 7: way that OpenAI can be used. 367 00:22:40,800 --> 00:22:41,480 Speaker 4: And I don't want the. 368 00:22:41,400 --> 00:22:44,480 Speaker 7: Public to think, oh, no, I use chat GPT, or 369 00:22:44,520 --> 00:22:47,000 Speaker 7: I use claud or I use something else. If you 370 00:22:47,200 --> 00:22:50,879 Speaker 7: log in, your data is more protected than if you 371 00:22:51,040 --> 00:22:55,040 Speaker 7: just start typing. For the Palisades fire, That's how law 372 00:22:55,080 --> 00:22:58,600 Speaker 7: enforcement found people of interest or suspect of interest was 373 00:22:58,680 --> 00:23:01,479 Speaker 7: things that they were typing in to AI that just 374 00:23:01,680 --> 00:23:03,600 Speaker 7: existed out there in the world. 375 00:23:04,480 --> 00:23:07,800 Speaker 1: Heather, I want to circle back to the video that 376 00:23:07,840 --> 00:23:11,800 Speaker 1: has just surfaced about the video of the vehicles flying 377 00:23:11,840 --> 00:23:16,320 Speaker 1: by at the same time Nancy Guthries kidnapped in her neighborhood. 378 00:23:16,359 --> 00:23:18,359 Speaker 2: What do you make of that video? 379 00:23:18,440 --> 00:23:21,840 Speaker 7: Forensic experts will be able to slow down those vehicles 380 00:23:21,840 --> 00:23:24,840 Speaker 7: to the point of us being able to identify make 381 00:23:24,920 --> 00:23:28,320 Speaker 7: and model. They should also be able to detect speeds. 382 00:23:28,400 --> 00:23:30,840 Speaker 7: So if you think you're involved in a crime, you're 383 00:23:30,840 --> 00:23:34,320 Speaker 7: probably driving pretty quickly. And this is exactly what happened 384 00:23:34,320 --> 00:23:37,040 Speaker 7: with Brian Coberger. He tore out of that neighborhood in 385 00:23:37,080 --> 00:23:42,320 Speaker 7: that vehicle. That car was the second most important identifier 386 00:23:42,400 --> 00:23:46,520 Speaker 7: to the DNA to getting access to Brian Coberger and 387 00:23:46,600 --> 00:23:47,440 Speaker 7: leading to an arrest. 388 00:23:47,520 --> 00:23:48,960 Speaker 2: So this could be. 389 00:23:49,080 --> 00:23:53,240 Speaker 7: What investigators need all along to identify who is involved 390 00:23:53,280 --> 00:23:53,879 Speaker 7: in this crime. 391 00:23:54,560 --> 00:23:58,480 Speaker 1: So, Heather, what about the fact that to the naked 392 00:23:58,560 --> 00:24:01,000 Speaker 1: eye to us looks blurry? 393 00:24:01,720 --> 00:24:05,600 Speaker 7: Oh my goodness, and my terrorism investigations, we were able 394 00:24:05,640 --> 00:24:10,280 Speaker 7: to identify things that you can enhance this footage. Think 395 00:24:10,280 --> 00:24:12,600 Speaker 7: about what AI can do for us in forensics. This 396 00:24:12,680 --> 00:24:15,399 Speaker 7: is a perfect example of using AI to clean up 397 00:24:15,400 --> 00:24:18,600 Speaker 7: an image, remove the blur, slow it down, and have 398 00:24:19,160 --> 00:24:22,399 Speaker 7: vehicle experts say, I know that this is likely. This 399 00:24:22,480 --> 00:24:25,639 Speaker 7: make a model probably of this year, and then you 400 00:24:25,720 --> 00:24:28,399 Speaker 7: go into the records and see who in that area 401 00:24:28,520 --> 00:24:33,240 Speaker 7: owns vehicles that match that description, and it will really 402 00:24:33,320 --> 00:24:36,680 Speaker 7: pare down the amount of people that need to be 403 00:24:36,880 --> 00:24:38,240 Speaker 7: questioned at this time. 404 00:24:39,040 --> 00:24:41,840 Speaker 1: If you know or think you know anything about the 405 00:24:41,840 --> 00:24:45,960 Speaker 1: disappearance of Nancy Guthrie, please dial toll free eight hundred 406 00:24:46,040 --> 00:24:50,320 Speaker 1: two two five five three two four repeat eight hundred 407 00:24:50,920 --> 00:24:56,040 Speaker 1: two two five five three two four, or if you 408 00:24:56,040 --> 00:24:59,720 Speaker 1: wish to remain anonymous, five two zero eight eight two 409 00:25:00,359 --> 00:25:04,880 Speaker 1: seven four sixty three repeat five two zero eight eight 410 00:25:04,960 --> 00:25:09,919 Speaker 1: two seven four sixty three. There is a one point 411 00:25:10,080 --> 00:25:15,960 Speaker 1: two plus million dollar reward. Thank you to all of 412 00:25:16,000 --> 00:25:18,399 Speaker 1: our guests for being with us tonight, but special thanks 413 00:25:18,440 --> 00:25:22,679 Speaker 1: to you for joining us in the continued search for 414 00:25:22,800 --> 00:25:28,160 Speaker 1: Nancy Guthrie. There is time to bring her home.