Now that South America was a priority, hundreds of agents were working those messages, most of them with significantly better computer skills than I had. The ones in Johurá had gotten the most attention. Katherine Wyatt had, apparently, continued to work tirelessly on interpreting them and even held classes to teach agents how to understand a little of the language. Those weren’t indecipherable anymore, and so not my concern.
My job was to do what computers couldn’t do: either crack a new coding scheme, like I had with the original Johurá messages, or else recognize some pattern in the chaos that could help the army of agents focus their efforts to find the needles in the haystack. The first option would require me to choose a message, more or less at random, that after hours or days of work would probably turn out to be somebody’s illicit love letter. I decided to try the second.
Fortunately, in my months on the job I had learned how to use many of the software tools available to aid in such an analysis. I could pull the metadata from millions of messages and run a bank of statistical tools against them. I was pretty good at statistics, which in my book was still a branch of mathematics, even though I knew statisticians who would take offense at me lumping their science into my field.
What I wanted to characterize was the difference between South American message traffic before and after the appearance of the fungus. Of course, there were many differences, as there would be from any comparison of distinct sets. Some of the differences were obvious, and thus uninteresting. Some of the differences would be normal random variation, or else seasonal or population-based trends, and thus also uninteresting. I was looking for the significant differences, those that were both unintuitive and important.
For lack of a better metric, I chose the date of the attack on Paul’s riverboat as the turning point after which I would deem messages to be “fungus influenced.” My null hypothesis would be that the messages before that time and the messages after that time would be perfectly correlated, shaped by the same basic forces and trends. I set about trying to disprove that hypothesis.
Four hours later, I had a spreadsheet full of numbers and no conclusions. My head was starting to spin. I had promised myself I would remember to eat, so instead of pressing on I picked up the phone and called Mike Scaggs. Before I left for Brazil, joining up with him for lunch had turned into a habit, at least when both of us could get away from our duties.
“Scaggs,” he said, with his usual soft professional tone.
“Hey, Lieutenant,” I said. “They still let you eat over there in cyber com?”
“Neil. You’re back.”
“Been crying into your pillow every night since I left, haven’t you?”
“Something like that. You hungry?”
“That’s why I’m calling.”
“You must have quite some stories to tell.”
“I’ll regale you over lunch. See you there.”
I opted for a grilled chicken panini, and Scaggs chose a cheeseburger and fries. I dumped five sugar packets into the too-sour lemonade and stirred while I told my story. I started from the assassinations and explosions, through the cross-country drive with the CIA, to the crop dusters and the defection of soldiers at São Luis and the 11th Bomb Squadron.
“I have to hand it to you,” Scaggs said. “We send you down to Brazil for a few days, and the whole country falls apart.”
“I’m just a bad luck charm, I guess.”
“You sure you don’t want to work for our enemies?”
Technically, the cafeteria was an insecure zone, where no discussion of classified material was supposed to go on. Sometimes uncleared visitors were escorted through the facility, and you never really knew who would be eating lunch there or how much they were supposed to know. In practice, however, classified topics were often discussed, only in roundabout ways and without using specific code words or program names.
“We’ve been focusing a lot of our efforts on South America,” Scaggs said. He was USCYBERCOM, so he would be concerned both with cyberattacks on US secure facilities and with trying to breach the tightly protected information repositories of others. Such attacks could be purely for the purpose of obtaining information, or they could be used to introduce destructive viruses or worms and destroy an enemy’s infrastructure or ability to communicate.
“Despite everything that’s happening, we haven’t seen any increased cyber activity. It’s still China that’s the biggest threat on that front. My guess is that Brazil, Venezuela, Colombia, and Peru never had much of a cyber capability, and so even on a wartime footing, they don’t have anything to use. Though with so much chaos, there are probably capabilities that the Ligados don’t know about or haven’t been able to organize.”
“I wouldn’t bet on that,” I said. “My impression of the Ligados is that they’re pretty streamlined. It’s not a top-down hierarchy so much as a crowdsourced one. Since everyone has the same goals, they can coordinate to an extraordinary degree.” I told him about the timing and coordination required for the various successful assassinations.
“On the other hand,” Scaggs said, “we’ve pretty much got the run of their systems. We’ve disrupted a lot of their military comms, and crashed the computer systems at munitions factories, defense contractors, satellite ground stations. They were pretty vulnerable in a lot of their core systems.”
“And if this were a conventional war,” I said, “that would probably give us a big advantage. But they’re not ultimately fighting us with guns and bullets. They’re turning us against ourselves and taking over our country from within. I’m beginning to suspect, too, that the Ligados have other ways of communicating with each other that we’re not aware of.”
“What makes you think that?”
“The message statistics I’m looking at. They’re too… normal. I don’t exactly know what changes to expect from wartime, but what I’m seeing is a whole lot of ordinary. It makes me wonder if… hmmm.”
“Uh, oh, here it comes,” Scaggs said. “Half the time when I eat lunch with you, you shout ‘Eureka’ and run off back to your lab.”
“I don’t shout ‘Eureka,’” I said. “I only did that once, and it wasn’t in the cafeteria.”
“Well, maybe you should try it.”
I munched my panini, thinking. It was no Eureka moment, just a feeling that I was looking at things wrong. I was trying to find pattern differences from before and after the emergence of the fungus. But what about pattern differences that ought to exist but didn’t? What about the changes you would expect from nations at war that weren’t evident in their message traffic?
After lunch, I returned to my spreadsheets and statistical analysis, keeping the idea in mind. After another six hours pounding away at the numbers, I thought I had something. Not an epiphany, exactly, but I thought it could be important. Melody’s office was empty, so I told Andrew instead.
“There’s a blank space,” I said. “Most of Amazonas, a lot of Pará, and a little less than half of Roraima.” These were the Brazilian states that covered the Amazon rainforest. “There’s almost no traffic in those regions. No email, no cell phone, nothing.”
Andrew looked confused. “But that’s the same as before any of this happened,” he said. “Those states are sparsely populated, with the exception of a few tourist cities. There just isn’t much technology there.”
“There wasn’t. But this is the center of the Ligados movement. The highest concentration of infection per capita is in these states. We also show a population shift from Venezuela, Colombia, Peru, Brazil, and Bolivia into the rainforest areas. I checked with the CIA—they keep track of stuff like that, and it’s a significant migration, millions of people. But there’s no commensurate rise in message traffic, nor in any other technological measure—energy production, building construction, roads, telephone lines. Satellite images of the area look the same as ever, just thousands of acres of trees.”