 I would be talking about the other project, and particularly on the technology angle about the real quality, but not about anything else, right, fair enough. So as part of this presentation, you can see the blue links. I've also linked all the articles, public research that we've done as part of that. So if you have any questions, you can go look at it, right, thank you, huh? It is on the talk funnel, right? About myself, I exist. So I haven't found a need to have another yet, okay? I'm a dependent for the petitioners in the Supreme Court of India in the ongoing cases. So most of the technical arguments on the project has been drafted by me, right? I'm a security researcher, and I do a lot of financial modeling, and I also program. That's basically my background. So what is a big point I want to drive in today's talk? If you're talking about a data acquisition system which is countrywide, eventual consistency is a big weakness. That's basically the point I want to keep driving towards, okay? And this part is important because why is eventual consistency a weakness? Because it's going to be exploited, and the way in which you think about Aadhaar, it's much more easier if you think about it like an identity platform. And one platform that you are very, very aware of is what we call as a currency node, right? So if you have a currency node, you already know about what a platform is. An identity document is something like a permanent currency node, which does not have double spend problems, right? So if you historically look at all the bank scams and fake node scams, you can basically think of currency nodes as having read access and having write access, okay? So if you look at most of the common ATM frauds and SIM card frauds and what kind of stuff, it's basically about getting read access to your money. And the guy basically comes in your pocket and takes the money and goes on, right? However, fake currency scams where someone is basically printing nodes is a lot harder, okay? Because of the entire process involved. And this is basically how the bank nodes work. The way in which you can think about Aadhaar is that, what if you had write access to the entire database, okay? So I'm not gonna talk about the leaks. I'm not gonna talk about all the various data leaks. And it leaked there, it leaked there. I'm gonna talk about only write access, right? So what it really means by having write access is that, if you are able to compromise the write process, you basically have a permanent currency node that does not have double-spend problems, that's basically the impact of it, fair enough. This is again reiterate my point, which says that if you're able to control what right into the database, I mean, you're basically a very rich person, okay? So to illustrate this problem of write access, we have four existing case studies from the field, which I call as the four horsemen. So in case you look at the X-men apocalypse, usually records four horsemen before the acapecalypse, right? That's basically the four horsemen studies. All these are real, these are not made up. And we have extensive public documentation that these things happened and we also know about the impact, right? And the first one is what is called as an explorer, because this happened on 2012. And this was probably the first template I've seen where people had write access to the database to control what is being written into it. The second one is what is called as a 2016 lineage. It started at 2016, it's still ongoing, it has not been stopped. And this I call as a patch maker, who specialized in trading patches to get into the database. The third one is what is called as a fingerprint forger. The fingerprint forger is primarily used not for creating entries, but for updating existing entries using fake fingerprints, right? And the last one I heard is on Delhi, which I call as a mixer, who basically mixes all these techniques together and create what we call as a super write access. And finally, I will also tell you who is the apocalypse at the end of the talk, right? Before we go further into the four horsemen, I want you to understand about how the enrollment process itself works and the various checks and balances that are there in the system. So if you look at the data acquisition, there's a very specific reason why I call it data acquisition. Every enrollment that has happened in Aadhaar so far is a data acquisition. There had been as per the official documentation by the Aadhaar authority, 1.2 billion data acquisitions. However, they did not actually tell you the amount of rejects, okay? So if you consider the rejects, it's much, much more. Almost all the enrollment is done using what is called as an offline mode. And the reason why it is called as an offline mode is because basically they wanted enrollments to be done even in places where there's no internet connectivity. So what they basically have is it is done through a software and a packet is created and it is uploaded later. That's why we call it as an offline generation process. That's why it takes a long time for you to get another, maybe 16 days, 90 days, right? So what does the enrollment really mean? It contains three different set of documents, right? One is what we call as an XML, which is basically your demographic data in an XML format, right? And then there's what is called as media, which is basically your fingerprints and address. And the third is what is called as a derived documentation or your original P-O-I, P-O-A scans, right? So these three things are basically what gets captured as part of the enrollment, okay? Fair enough. So if you look at this end-to-end process, I want you to pay special attention towards data transfer to CIDR with a pin drive, okay? So that is a part that you're to pay special attention towards. It's very important for all that you're seeing today, later, right? So if you look at it, it just explains about how the whole thing works. But for us, the most important thing is there is devices, hardware, software, and there's verification procedures, and there's data transfer, okay? So as part of any data generation process or data capture process, you have to ensure that there's a human checks that are performed on it. So some of the checks that they have is an introducer. So in case you are one of those people, rare people who never had an existing ID document before, there has to be an introducer who would introduce you into the system, right? And there's also a document verifier and a supervisor. And the reason why these two gentlemen are very important is because you have to think about other as a derived identifier. So the only new thing it actually adds into your existing documentation is the biometrics, okay? So you are supposed to submit your PO, a proof of identity, proof of address, and the date of birth, and that's basically what gets into your EK, BC, et cetera. And the only new thing that it is actually adding is the biometrics. So in order to verify that your derived IDs are actually real, you need to have a, I mean, enrollment, you need to have a document checker, okay? There is also a lot of incentives for successful generation. This is basically for the operators. So basically the structure works is by saying that if you generate, if you capture data properly, there is, and you get another number successfully, you get 50 bucks. And if you make a mistake and there are a whole bunch of process errors, et cetera, et cetera, there is a penalty for it. This is basically the structure that has been set up. Now, the software checks is important because if you look at what they have done is they have rolled out an enrollment software, and thus there are checks on the software about data capture and quality. So if you look at the software, you can actually say the basic minimum biometric quality required for fingerprint analysis is 52%. Just don't ask me why it is not 80%, okay? And then there is onboarding for supervisor and operators using their own fingerprints and passcords. And there is GPS and parameter synchronization. So I'll come back and tell you why you need operator and supervising onboarding using fingerprints because they figured out a long time ago that how do I know if I were an operator who's enrolling people, how do I know it is me who's enrolling but not some random person? So you need username and passcords, but it is done offline because you just basically take a round in a mobile one and move around. So they've wanted the guy's fingerprint, okay? So the prerequisite for being an operator is that you need to have another number, okay? And when you actually enroll people, you basically are given a username, password, and you have to put your fingerprint on it. That's basically what we call as onboarding, okay? The GPS and parameter synchronization are important because unless until you put a GPS, how do you know the person whom you're recruiting is not in Pakistan? Because it's offline, enough. That's really the reason why the GPS was added in. The parameter synchronization is fundamentally a method to update some parameters of the enrollment client from the backend. It's usually about how much of data, packets are pending, how much of them are not uploaded, how much of them failed checks, et cetera, et cetera. So once you generate this enrollment, before it even hits the deduplication, there are a series of checks that are done on an enrollment packet. And these are basically structure validation, demographic checks, operator checks. Is a guy, is the operator really blacklisted? Is he allowed to enroll people? Then is the supervisor proper? Is it, if it is a biometric exception, you need a supervisor approval. So is the guy really there? And then there's an introducer check, and then finally there is a resident deduplication, right? So at this point of time is when you basically get another number. So I will now touch upon what the explorer has found, which is case tree number one. So the first version of the explorer found a very interesting bug on the enrollment software. So remember I told you that before an operator enrolls anyone, he has to give us fingerprint, okay? So what the explorer figured out is that you can give any person's random fingerprint. It's gonna fail the first three times, but the fourth time it's gonna accept it, okay? So that's basically what it is, right? This is 2-0-1-2, right? Now let's go further. So the other interesting bug that the explorer had figured out is, so remember when it started on 2-0-1-2, they were using what is called as a document management agency, which is heavily packered. So basically you have a guy, hang on, basically you have a guy to whom you go and give your documents. You will just put it on the printer, take a scan, and he also has original documents, and all of them are piled up together, and they're basically sent to the CRDR for digitization, okay? So if you look at on 2-0-1-2 or even until last year, you would see in any other center a big pile of documents, right? Just don't ask me what happened to those documents. Those documents have their own history, right? But the key thing you have to remember is if you look at the process workflow, basically from the start, which is one, to the end, it's about 12 steps. It takes three months a day. I mean, three months is the best number that I've seen. It takes three months for the documents to actually get digitized and go to the CRDR, okay? So what happens during the time is it is like your passport. You can apply for the call passport, and basically they will give you the passport now and the police verification comes later, right? So what these guys do is, when you basically make an enrollment, give all these documents, right? If your biometric checks are done and all the structure validations are done, you will get another number, but probably in about two weeks or four weeks, but the documents may take a long time for you to reach the CRDR. So ideally they're supposed to audit, but they don't, but that's a different story, right? So now here's the interesting part. What is the other interventional consistency thing that I wanna tell you about? This is basically an email that was basically sent to all the operators and just look at what they're saying. Any non-synced packets, please take back up and upload to Google Drive, okay? Right? This is 2017. So what do you mean by a non-synced packet? A non-synced packet is basically the operator during enrollment and they are pending documents and sometimes it so happens that they lose hard drives, they miss it and whatever is left over, they say please put it on Google Drive. Okay, enough. So the interesting thing about the Explorer is that he used these two weaknesses, which is the fourth-time fingerprint logover and it works and the long tail of documents. He made 870 biometric exemptions with missing documents of 30,000, okay? So what happened was you already run a backend and they figured out that there was a single operator called Muhammad Ali who made 30,000 enrollments in 20 days, right? Which they thought was probably improbable and they said, okay, how can the guy who'd have made it? They did computation and said, oh, he must be enrolling 50 per hour. Oh, that's not possible, okay? So let's go and figure out what he did and it turned out that the operator Muhammad Ali has been deactivated long time ago but his fingerprint was invalidated but someone is basically using the fourth fingerprint thing and just putting all this stuff, okay? Right? And because of the long tail, they figured out, they said, okay, let's go audit everything what this guy has done. They went and figured out that of all the 30,000 enrollments he did was fraudulent and they were supposed to give a ration card as a P-O-I, P-O-A, but those ration cards does not exist, right? The document management agency did not find the ration card, okay? So what it really means is that he got all those other numbers. So finally, if you look at the last week which I reported, what I reported is there was a whistleblower who sent a set of documents of the Supreme Court justices after the right of privacy judgment in which he had basically said out of the 115 crore other numbers that were generated, 46 crore other numbers generated do not have any documents, okay? That's basically what it is, right? So as usual, what the whistleblower says we need an official source, right? The URA admits in their own website that they don't have documents for 7.82 crores of enrollments. So between 7.82 crores of what the government admits and what the whistleblower says is 46 crores, that's basically a range, okay? Now the patchmaker, so we're gonna talk about a very interesting thing about the eventual consistent software. So the patchmaker operated by patching the enrollment software, okay? So let's go back to what is the enrollment client. The enrollment client is basically a Java SC application and it is optimized for no internet connectivity. So it's another way of saying it's eventually consistent with the CRDR and if you actually think about it, it's a brilliant, right? What is an enrollment, really speaking? An enrollment is basically a zip file, right? What if we can create the zip file by modifying the enrollment client, right? That's basically what the patchmaker is all about, okay enough? So what did the patchmaker do? So he basically looked at the Java SC client, he looked at all the jars. So if you understand Java SC, basically almost all the functionality resides in the jars in the lib directory. So he just replays all the jars in the lib directory with your own versions, you know, with the interface, the matching interfaces. So what are the checks that have been removed? The checks that have been removed are local logins. So the earlier one, the explorer, at least have to put four times wrong fingerprint. This guy beat it by just removing the biometrics himself, okay? So basically what you had was just login and password, which of course they used to publish it on, cac.gov.n, right? I mean, I still have those logins and passwords, okay? So at the end of it what happens is you basically have a zip file and you upload to the CRDR and you get another, right? Which of them are real, right? So are these guys successful? So this is basically an interview we did with the IPS officer who basically cracked the scam on 2017 September. His name is Triveni Singh. This is an official document. So we were asking why would they collect all the data? How are they benefiting from this? And the guy says one of it is for profit maximization because he's able to just distribute 25 more times and get more money to him. And of course the other thing is misuse because he had figured out how to generate two other numbers by defeating biometrics. Okay, so the duplication thing is also gone because your data capture is gone. Fair enough. So from when is this active? The first known incident I have tracked on the web is on Telangana, which is on 2016. So this is the first time ever I had seen a public version of the cracked ECMP software, right? And for how long has it continued? It has continued until April 20, sorry, June 30, 2018 until it is on Delhi. So if you basically draw a map of India, I would probably say I found close to about 25 incidences officially recognized all over the North India as well as Karnataka. So this is basically the cracked ECMP software, right? And the best part about the cracked ECMP software is it comes with a YouTube support channel, right? So if you look at the first one, it is basically Digiseva Center. Digiseva Center is the official government-run CSE website. You can even Google, and the guy is fantastic. He actually put his phone number and a PTM number, okay? You can actually call him and say, oh, man, I'm not doing any work. And he says, yeah, put it here, put it here, right? And so this is what. So the next time, the next one is Bina Mobile Bina operator's ECMP print order, okay? So whatever that is, okay? Fair enough. So this I will show you an official cracked video that is on YouTube. So this is not something I made up. Hey, look at the version 3.3. Okay, here I'm opening the portal, software. Okay, here software is opening, which is not going to ask for a fingerprint. Yeah, we're not going to ask for a fingerprint. That's basically what you want to know about, okay? How do I get this back? So that completes the patch maker, right? The fingerprint forges are a slightly low version of the technology. And remember, all of it is still not read access, it's write access, right? So what these guys do is, as part of 2017, when all the stuff came out, URII said, I'm gonna remove all the operators, enrollment operators, everyone is out of the system, only bank official is supposed to actually allow to operate the other enrollment, right? So what these guys did is, they basically tracked the bank chairman in Gujarat, Suraj, Surat is a Varsha bank chairman. He had access, right, to the fingerprint, to the other edits, right? They got a fingerprint without him knowing about it, and they basically gave it to a lot of other guys, right? So what these guys figured out is, some impression of the authorizer, I mean, other officer was used to actually edit. So if you have a problem changing your name to Anand to Dayanand, you just go to these guys, pay them 500 bucks, they will make your change. That's basically what it is, right? Okay, so when they caught him, this is a very interesting thing, which is not reported in national media, but is reported extensively in Gujarat media. You can basically call these guys and say, bank chairman, the guy says 25,000 bucks, he'll give you bank chairman, okay? And you can basically call a guy and say, hey, MP, 50,000 bucks, MLA, 75,000 bucks. So it's basically on-call demand service, right, for fingerprints. That's basically Gujarat biometric leaks, right? So the next interesting thing about these guys is, when you basically call them and get them, you basically get their other number, username, passwords, and also their fingerprint in raw format. And if you're one of those guys who don't know how to convert a raw format image into this gel thingy, it's 10% extra, right? And from then, this has been going on, this is basically an official RTI request which we got. It's been going on from 2014 or 13, so that's basically the level of how these guys have been operating, right? Our final horseman is the mixer. So now, what he basically did was he created, his name is, so again, when I go back and ask you this, it's basically a three-ring crime network. The first ring which we had caught so far, or at least know of so far, is basically the operators themselves, okay? But these are not the guys who made all this stuff, right? The operators are getting all this from distributors. This is ring two, right? The distributors is how we have gotten so far, right? We really do not know who's actually the kingpin number one, who's basically making all this, right? All we know is they got it from Bihar, that's where the trail ends, okay? So the assembly factory, as we call it, is basically a self-organized unit, which if you call an order, will give you all the information that you need to run and fake other enrollment center, which actually works, right? So it contains a fake fingerprints of bank officers, it gives you crack software, and it gives you also techniques to basically, you know, create fingerprint gels and whatnot, enough. So what is really the implication of it? The implication of this is, the UNI says that all these people are in the database. That's basically their claim. In reality, I don't know what is in the database. There is just a database, right? So the question that we have to go further is what is the reason why people are doing all this? We have to basically ask the question. In every crime, there is model, right? We have established process, we have established how people do it, why, but not what the what. What is really the what, right? The first and foremost thing about the other enrollment itself is that it is actually unviable, right? The reason why I call it unviable is just like many of the things that has been sold by the government, it is basically sold well to the operators that you can make a lot of money on it, right? So if you look at what is the lot of money, so if you look at what is another enrollment kit, it costs you 2 lakh for you to make it. So the per successful enrollment is about 25 to 50 rupees. So if you basically do a backup envelope calculation for an operator, you can break even in 8,000 enrollments. That's basically what you'll think about it, right? The rejection rate of enrollment, however, is 25% on an average. So what I mean by rejection rate in enrollment is for you to get 8,000 enrollments, you ought to probably make 10,000 enrollments because you only get money for generated ones but not for rejected ones, right? The distance in terms of where it starts hurting you because it is possible that the enrollment got rejected because you didn't capture someone's fingerprint properly, okay, or there was some data intricate or a quality error or a zip error, whatever, right? For every search, capture error or data entry error, you're basically fine from 300 bucks to 10,000 bucks, right? So if you look at the permutation and combination, it's six times more for rejection and 25% on average basically makes you unviable. That's basically what these guys have figured out, right? So what had really happened was when these disincentives were created because data quality issues were going higher and higher the operators basically said, and this is the important part, this was introduced around 2014 and most of these guys were saying that we were on the edge of bankruptcy because we can't actually sustain our business, right? So this is the fundamental reason why the patch software at least came into picture because there were a large demand, right? And it has to be satisfied under any circumstances because it's all puppy paid cassavall, right, okay? So the interesting part about the payment, what do you call the fake other network, as we call it as? It had a trained workforce of 60,000 operators who have been laid off, okay? They know in and out of the system, that's the reason why you see the YouTube channel, right? The capital expense is already covered. The cost of the crack software is 5,000 bucks, right? And the cost of one fake other is 5,000 bucks. So you can just see the incentive structure pretty much aligned for everyone. The disincentives, of course, is please do not get caught, okay? So then we're gonna ask, I told you the basic question, who's gonna be the, who's the, I mean, if you have the four horsemen, who's the upper calyps? The answer, unfortunately, is us, right? And the reason why I use the word as is because it's technical audience. We don't really understand the purpose and value of technology, right? I mean, we believe when we create a technology it's gonna be used only for good. We don't actually understand that we have blindnesses, we have biases, and those biases actually hurt us very bad when we load technology at a country-wide level, right? And why I'm saying that is because scale comprehension, even on fraud, is actually very hard for us, right? So if you historically notice a revolutionary path, we have been living in tribes of not more than 10 to 100 for a very, very, very, very long time, okay? So not long ago, my father knew almost every single person in his village, right? When I come to a city, I am still not completely used to the anonymized, large masses kind of living, right? So what it really means is that if you are a software engineer and you design a system, you don't really understand that your mind has probably not grown beyond the technical capability of a software you can create, right? So while Mr. Ajay Bhushan Pandey goes around and says that I'm gonna waiting for a big attack, but that's not gonna, how it's gonna work, right? You're gonna see a million small attacks, like what these guys have done on the ground, right? And remember, evolutionarily speaking, the bacteria always wins and the elephant always dies, right? So what are the data acquisition lessons that we've learned from this $6 billion episode is that computer systems add a complexity vector called control, right? So when we think about software, right? We think about possession and ownership, but we don't actually understand control. So what do you mean by control? In this particular case, who controls your endpoint of data acquisition, right? You may believe that you gave them the software, you may believe that it's generating a zip file, but who's actually controlling the software, right? And also remember, in asynchronous data acquisition systems, drops, delays, and frauds are indistinguishable. That's basically our explorer, right? And so one way in which they tried to fix the problem was they made GPS mandatory on the enrollment software, but that has been patched out. So the GPS has been patched out in such a wonderful form that every single enrollment is made by the fake software. The guys are actually cheeky. Every single enrollment is made by the fake software actually points out to the URI office in Prakriti, Maidan, and Delhi, okay? So people look at it and say, yeah, why are there so many enrollments in Delhi? Why is it exceeding the population? We know the answers for a very long time, right? So the other interesting thing about controllers, this is not, this is probably day before yesterday's packet upload status in URIDI. You can just see that. Packet uploader today is 4 lakh. Packet director today is 29 lakh. What do you think it's happening? Give a guess. It's probably the fake enrollment software, which is DDoSing it. R is basically so much of data quality issues. I mean, it's in uploads.URIDI.gov.n. Please click on it before they bring it down, because usually they do when they report it, right? So what are the final lessons? Our final lessons is if you're running a country-wide enrollment system on which you spend $6 billion, please do not outsource it, right? Please pay for the maintenance and do not undercut them, apart from the technical staff, right? I'm pretty much done. Questions, we have time? Fine, questions if you have any? Sure. Hi, I have a question. According to your opinion, do you think the problem was with the second part which you said that we as software developers do not really go, most of the time, go beyond our scope and understand all the different nuances which are there. Was that the basic problem or was the basic problem that the developers itself were not that good? See, how do you distinguish your business and developers? So if you basically think of it like a business, let's say you actually ran a big data business capturing stuff from the entire country. What I was just trying to tell them was that when we designed it, we look for scale, but we are not very good in figuring out that such a system has side effects. So when these guys did it, they designed it for the use case of optimizing enrollment speed, not for enrollment fraud detection. Yeah, that's like basic flaw. Like there are certain, obviously there can be always ways of tricking systems like really writing hard-core viruses, but there are certain very basic security mistakes in this whole thing. So the basic security mistake, I would probably say is the offline part. Okay, and the reason why the offline part was done is because of the enrollment speed problem. Right, if it has been online, you could have just directed it a lot more faster than, I mean, see we do it all the time, right? If you log in, let's say that your account in your company is compromised. How do people detect it? They know that you can't be in Singapore when you are in your home, right? I mean, two logins which are geographically distanced can be easily directed, but not here. It's fundamentally offline, how do you direct it? And without the offline part, the system will never work. They could have actually at least done a two-factor authentication, like you use- Two-factor authentication is the operator fingerprint. No, you use a fingerprint, some code will come to your mobile, and you have to give that code also. It doesn't work like that. I'll tell you why, okay? With the mobile other linking, even if you, so if you look at the guy, right? The guy actually has a mobile number, but you can't trace him. So what is two-factor authentication when you actually control the source? Hello? Yeah? Yeah, so, sir, here. Here. Okay, why not the owner of the document update their details? It's not possible, isn't it? Let's say I have, my details are wrong. Why not the system allow me to correct my data? Excuse me, may I ask the audience to be a little quiet? The session is still on. You can carry on your discussions outside. Please take your discussions outside. The session is still on. Yeah. Is there a way the owner of the document update their own details if there is a connection, correct? See, you should ideally, because you just keep moving it on. We're all migrants, right? But the problem is who's gonna check it? Ideally not. Ideally, no, it doesn't allow. You need someone to say that you moved to a different place. There is a document that says you moved to a different place. That's how it is. So people actually are very unhappy about it. That is the reason why the fake, the crack software is of great use, because you can basically go to the guy and give him finite bucks and change your address. Here. So if this is so blatant, UADI says our database is perfectly secure and all that, on what basis? On what basis? I think denial is a far easier response and competency. Okay. Thanks. So, yeah, one question. This way. So now that, yeah. Hey. Yeah. So now that we are in a mess already, so what do we do here? From here on, because we are in a mess. The data is out there. It's leaked. It's with everyone. So we need to clean this up and say we, tomorrow the solution can be abolish, add or do whatever. But how do we do the cleanup? It's up to the tech industry again, right? So any views on how do we clean this up? How do you clean this up? A full audit. Yeah. A full audit. A full audit, right? So like, is there like, is someone coming up with a plan as like how the audit will be done because that again gets outsourced and then we are in a mess again. So the way in which you have to think about other asset exists today is it is a self-certified ID. You are whatever whom you say you are. So there is no cleanup, right? Like. They can do a cleanup if they want to. Exactly. It's gonna cost a lot. Yeah. Effectively not happening then. Yeah. So as you mentioned, like outsourcing is the fundamental flaw. Yeah. For data acquisition. So what do you think like, okay, let's say like they do in-house. They do the data acquisition in-house instead of outsourcing it to an external private. It would have worked. It would have worked much slowly. Slowly is one thing. Like do you think the data would be secure even then? See to a large extent, if they're done in-house, they would have gotten some control. So if you look at originally how we used to get ID certified in the past, there used to be a guested officer who would put a signature and says you are whom you say you are. Like if you wanna get a Tathkal passport for instance, one of the commonly used method is go to some IS officer or an IPS officer who certify and say, I know, I really know you. So in the past what used to happen is there used to be a status, which is like government servants are typically more trustworthy. Okay, and hence if they say that whom you are is what you are, it is like that, right? So what has now happened is, I would probably say that they have democratized trust and created distrust. Hello? I have a question here. Hello? Here. So here, here. Yeah? So in hindsight, obviously it looks, you know, like, looks like we kind of messed up. But again, to this point, we being technical people who kind of handle big projects, decently big projects, can we come up with some sort of project plan that says, okay, this is how you can go about cleaning this? It's very easy to clean it up. It's gonna cost you a lot. That's all there is to it. No, but we always make compromises somewhere and say that. The compromises got you this place. No, but you can't say that, okay, this is so uncleanable that we live with this forever. What is it? I didn't catch the last part. It sounds very unrealistic to say that this is what the state is and the fix is gonna cost a lot, so we don't do it at all. That's basically the government's call. That's basically what they're saying now, right? I mean, if you personally asked me, I'm not against an ID system per se. I'm just again, I'm just, for an ID system where things are okay, right? It is just not, that's a problem. And they did it, they just did it for speed. I mean, there's really no overarching value beyond making it too big to fail. So if you fundamentally understand the dynamics of this project, which I don't wanna go into much, but I'll just touch upon it, they were really worried it's gonna be struck down. So their basic model is to just spread it so far, so wide, so that it can't be undone. Okay, that is the reason why this is there, because when you operate at that speed, I don't think you account for fraud. You don't actually care for fraud. My question is like, the government did a reasonably good job on the voter ID collections, and we are running probably the largest democracy in the world. Why the lessons learned from the voter ID collection not used in other, and like, why we end up in this mess, why we already have a very large... So if you look at the original way in which they looked at the whole thing, this is not supposed to come this far. This is supposed to be with PDS. The original argument has always been that look, there is a lot of problems in PDS, and historically, if you look at PDS in India, even in Karnataka a long time ago, people had experimented with biometrics for deduplication. That's basically how the whole thing started. And it started there, it just went too much beyond the scope, and that's where the problems are. So if you look at it, you can increase the scope slowly over a period of time by putting a lot of sufficient safeguards. I mean, we have been doing this for a while. We know how to do this kind of stuff, except that here, the control has never been with the technical team. It's basically something else. Done? One last question which came on Slido. Do you think, why do you think Ada was the only document which was targeted? We had collection drives, data collection drives, which happened earlier. Those documents were not mandatory for going to the toilet, which apparently happens a lot. So if you look at some of the stuff that happens in, so there's a scheme for Swachh Bharat, right? For you to get some kind of aid for Swachh Bharat, you need to have another card. So literally people were making fun of it by saying that like, I mean, you're saying it's, this is what it is. None of those cards were basically being mandated for each and every single thing in your life, right? I mean, you're not told that, if you don't do this, your money is gone. That's where the problem is. So while people had done documents before, they have not had big problems because of the fact that they were not mandatory for many things, okay enough? I'm done.