Proposal: Pluggable Filter Framework

In a recent discussion, the topic of how to manage policy enforcement within blockchain nodes was addressed, focusing particularly on the challenges and potential solutions for Bitcoin node operators. The central issue identified is the risk associated with shipping hard-coded filters that include on/off toggles, which could lead to centralized policy control. This approach may subject operators to undue pressure from nation states and create an ongoing struggle to stay ahead of regulatory demands.

A proposed solution to this problem involves the development of a pluggable filter framework. This would allow node operators the autonomy to author and implement their own policies, thereby decentralizing the decision-making process. Such a system would enable operators to share effective filtering strategies organically, fostering a community-driven approach to policy management. However, this solution comes with specific constraints to ensure its viability and safety. These include the limitation to local policy modules, enabling operators to add custom filters possibly through configuration files or flags; the necessity of a minimal, deterministic API that operates purely over transaction/mempool contexts; safe execution environments to prevent malicious filters from compromising node operations; and sufficient observability measures like local logs and metrics to fine-tune filter performance.

Implementing a pluggable filter framework as the default setting in an inactive state ensures that no active content filters are enforced unless specified by the operator. This strategy not only enhances decentralization by distributing policy control among node operators but also eliminates a single point of failure in upstream processes. Moreover, it allows for quicker iterations and adaptations within communities without the need to wait for official node releases.

Despite these advantages, there are significant trade-offs to consider. The decentralized approach to managing abuse does not eliminate the cat-and-mouse game with malicious actors but rather distributes the responsibility for responding to such threats. Additionally, this method may increase the operational burden on node operators and raise concerns about the consistency of policy enforcement across the network, potentially leading to fragmentation.