Look at the 120,000 nodes. Not on a blockchain ledger, but on a proprietary network run by a private company called Flock Safety. That is the number of AI-powered cameras the firm claims to have deployed across American suburbs and cities. The error isn't in the code—it's in the assumption that this is merely a tool for catching car thieves.
Senator Bernie Sanders recently promised to introduce legislation to stop this mass surveillance network. The political signal is loud. But tracing the gas trails back to the root cause reveals a system-level design flaw that most privacy advocates are too busy yelling about to actually audit.
Context: The Private Ledger of Vehicle Movements
Flock Safety is not a tech company in the traditional sense. It is a surveillance-as-a-service business. Founded in 2017, it has raised over $380 million, and its valuation has hovered in the billions. The core product is a network of automatic license plate recognition (ALPR) cameras, combined with audio sensors for gunshot detection.
The cameras capture license plates, vehicle make, model, and color. The data is stored in a centralized database. It is searchable by law enforcement agencies, community associations, and private businesses. The default retention period is 30 days, but that can be extended. The network effect is the killer feature: the more cameras installed, the more valuable the data becomes for tracking vehicle trajectories across jurisdictions.
This is not hypothetical. Flock's marketing materials and public statements confirm that its system is used by over 5,000 law enforcement agencies. The company has also begun testing facial recognition technology, which is banned in several states but is a clear escalation path.
Sanders' framing is that this leads to a "surveillance state." He is partially right, but his diagnosis misses the deeper architectural issue. The problem is not the cameras. The problem is the lack of a trustless, verifiable system for how this data is accessed and used.
Core: The Architecture of a Centralized Oracle
The code does not lie, but the auditor must dig. When I look at Flock's infrastructure from a Layer 2 researcher's perspective, I see a centralized oracle problem. It is a single point of failure for data integrity, access control, and privacy.
Let me break this down technically. ALPR systems use optical character recognition (OCR) and convolutional neural networks (CNNs) to identify plates and vehicle attributes. This is mature technology. The innovation, if you can call it that, is the aggregation layer. Flock's servers index every capture and allow for pattern matching across its entire network.
Here is the contrarian angle that many privacy advocates miss: The legal precedent is murkier than you think. In Carpenter v. United States (2018), the Supreme Court ruled that the government violates the Fourth Amendment if it accesses seven days of cell-site location data without a warrant. But Flock's argument is that license plates are public information. They argue that filming a car on a public road is not a search. This argument has held up in several district courts.
Sanders' legislative promise would need to override this legal interpretation. That is a heavy lift. The Fourth Amendment Is Not For Sale Act, which has been sitting in the Senate, would require a warrant for third-party data. Sanders could push for that, but it faces stiff opposition from law enforcement lobbies.
Based on my audit experience with smart contracts, I see a parallel. The issue is not that the data exists. The issue is that there is no consensus mechanism to verify who queried what, when, and why. There is no immutable audit trail that is publicly verifiable. Flock operates like a private blockchain with a single validator. It tells you what it wants you to know. It provides transparency reports when it is convenient.
The systemic risk is not just the government. It is the data brokers. Flock could theoretically sell trajectory data to insurance companies, marketing firms, or immigration enforcement. The reports indicate potential ICE collaboration, which is a major concern for progressive lawmakers. But we have no way to verify these claims because the system is closed.
The Contrarian Blind Spots
Shifting the consensus layer, one block at a time, reveals blind spots in the public debate. The most glaring one is the assumption that Sanders' legislation will solve anything. Even if Sanders passes a federal law restricting ALPR data retention to seven days, the business model survives. Flock's core value is not the historical data. It is the real-time alerting and the network effect. A seven-day retention policy reduces the data's forensic value but does not kill the network.
The second blind spot is the "community" angle. Flock sells to homeowners associations. It sells to private businesses. This is not just a government surveillance issue. This is privatized surveillance. Rich neighborhoods can buy protection, while poor neighborhoods are either over-policed or under-protected. This creates an uneven enforcement landscape that is worse than a simple state monopoly.
The third blind spot is the response of the industry. If Flock comes under regulatory pressure, it will adapt. It will shorten data retention to appease legislators. It will publish transparency reports. It will promise not to use facial recognition. But the underlying infrastructure is still centralized, still proprietary, and still unaccountable.
In the chaos of a crash, the data remains silent. Similarly, in the noise of a political campaign, the technical reality remains unexamined. The real fix is not legislation that bans a specific company. The real fix is requiring technical protocols that ensure verifiable provenance and consent. This is where blockchain-based identity and access management systems could actually shine.
Imagine an ALPR system where every query is logged on a public, permissioned ledger. Where access is granted via zero-knowledge proofs, proving that an officer has a valid warrant without revealing the data itself. Imagine a system where data minimization is not a policy decision but a hard-coded constraint. That is the Layer 2 solution. That is the bridge, not the destination.
The problem is not that Flock exists. The problem is that it operates in a vacuum of accountability. The technology exists to fix this. But the industry has no incentive to build it unless the regulatory pressure is precise enough to require it.
The Takeaway: A Fork in the Road
The consensus layer is fragile. What Sanders is doing is important, but it is only the first block in a new chain of governance. The question is whether we build a system that is transparent and verifiable, or one that relies on the goodwill of a private company.
The likely outcome is a compromise. Flock will make concessions to avoid a total ban. It will limit facial recognition. It will shorten data retention. It will add audit logs. But the fundamental architecture will remain unchanged. And in 24 months, when a breach occurs or an abuse is uncovered, we will have another political firestorm.
The code does not lie. But the code is hidden. And until we demand a transparent protocol layer that verifies every access, we are just shifting the consensus layer from one opaque authority to another. The question is not whether Sanders can win this fight. The question is whether the industry will be forced to build a better system before the public loses trust entirely.
I have seen this pattern before. In 2017, I audited a multisig wallet that had a critical kill function vulnerability. The code was secure in its intent but flawed in its implementation. The solution was not to ban multisig wallets. The solution was to demand better code. The same applies here. The cameras are not the enemy. The lack of verifiable, decentralized accountability is the enemy.
