Over a 24-hour period of testing, which executed approximately 22 billion operations, no successful surge attacks were initially identified under existing conditions. However, after an optimization was introduced to the fuzz test, numerous instances of surge attacks were discovered, including a notable case where a victim node lost 50% of its revenue. This outcome underscores a fundamental flaw in the algorithm's ability to adequately protect against such manipulations, particularly in scenarios involving fan-in topologies, where incoming nodes contribute to outgoing revenue but struggle to build sufficient reputation due to disproportionate calculation periods for incoming reputation and outgoing revenue.

The core issue lies in the algorithm's design, which calculates incoming reputation over a 24-week period and outgoing revenue over just a 2-week period. This discrepancy means that if there are more than 12 incoming nodes contributing equally to a node's outgoing revenue, it becomes practically impossible for any of them to accrue enough reputation to access endorsed slots, making the system inherently vulnerable to surge attacks. These attacks exploit the algorithm's imbalance by overwhelming the system with a volume of transactions or interactions that skews the intended equilibrium of reputation and revenue contribution.

To mitigate these vulnerabilities, several strategies are proposed. For custodial wallets, which typically do not encounter fan-in or fan-out topologies frequently, the current reputation algorithm may suffice without modification. However, for Lightning Service Providers (LSPs), which often deal with high volumes of both incoming and outgoing transactions, adapting or developing LSP-specific reputation algorithms could offer a solution. Existing efforts by entities such as eclair/phoenix to create bespoke algorithms are highlighted as steps in the right direction. Additionally, the adoption of trampoline routing is suggested as a potential remedy, allowing LSPs to endorse payments regardless of the previous node's reputation and navigate around the limitations of the current bidirectional algorithm. Nonetheless, this approach might also face challenges, especially when payments' destinations involve user accounts associated with other LSPs, reintroducing the fan-out problem at the receiving end.

The discussion of these surge attacks and their implications for network security and efficiency points to a need for ongoing refinement of reputation algorithms to address the evolving landscape of threats and operational challenges. The exploration of tailored solutions for different network participants and transactional frameworks highlights the complexity of ensuring robust security measures while maintaining the functionality and scalability of these systems.