Currently, the Web3 Meme coin ecosystem faces three new security technology challenges during the processes of user scale expansion, technical architecture iteration, and scenario boundary expansion: first, the explosive growth in user scale (for example, the addition of over 100,000 users in a certain period) leads to a mismatch between the computational power and response speed of security services, resulting in protection delays; second, the Meme coin technical architecture extends to Layer 2 (such as Optimism, Arbitrum) and modular public chains (such as Celestia), making it difficult for traditional security solutions to be compatible with the technical characteristics of the new architecture; third, security capabilities are concentrated in core transaction scenarios, failing to cover edge scenarios such as on-chain governance, community voting, and token staking, creating protection blind spots. Bubblemaps relies on three core designs: a security service architecture dynamically adapted to user scale, a security compatibility system for technical architecture iteration, and security capability extension solutions for edge scenarios to construct a more resilient and comprehensive security support network for the Meme coin ecosystem from three dimensions of 'scale adaptation, technical compatibility, and scenario extension,' focusing on the dynamic responsiveness, architectural compatibility, and scenario integrity of security technology that aligns with the industry's core demand for the sustainability of security systems.
1. Security service architecture dynamically adapted to user scale: solving the resilience problem of protection under scaling
The Meme coin ecosystem often experiences sudden increases in user scale due to community enthusiasm and market cycles (for example, a short-term increase of 5-10 times in the number of new users), while traditional security services often use fixed computing power and response processes, which can lead to 'risk detection delays due to insufficient computing power' or 'cost waste due to resource redundancy'—when the frequency of user interactions rises from an average of 100,000 times per day to 1 million times, the fixed power security module may have a risk identification lag of more than 30 minutes, affecting the protection effectiveness. The user scale dynamically adapted security service architecture built by Bubblemaps achieves real-time matching of security services and user scale through the design of 'elastic computing power allocation, tiered response mechanisms, and load prediction optimization.'
The core technical design of the architecture includes:
• Elastic computing power allocation module: Based on distributed cloud-native technology, decompose security services into microservice units such as 'risk detection, rule determination, and early warning push,' each unit can independently call computing power resources. Through a 'dynamic load balancing algorithm,' continuously monitor the computing power usage of each microservice (such as CPU usage and memory consumption of the risk detection unit), and when the usage of a certain unit exceeds 80%, automatically expand computing power nodes (for example, from 10 nodes to 30 nodes); when the usage drops below 30%, automatically reduce nodes to ensure that computing power resources dynamically adjust with user interaction scale, avoiding overload or waste;
• Tiered response mechanism: Set differentiated response processes based on risk levels (high, medium, low), prioritizing the processing efficiency of high-risk events. High-risk events (such as abnormal contract permission calls, large asset abnormal transfers) trigger a 'millisecond-level response process,' directly calling dedicated computing power nodes, bypassing non-essential verification steps, ensuring risk identification and preliminary interception are completed within 100 milliseconds; medium-risk events (such as user interactions with low-risk addresses, small transaction anomalies) use a 'second-level response process,' integrating regular computing power resources for processing; low-risk events (such as slight deviations in user operation habits from the baseline) enter a 'minute-level response process,' focusing on processing during non-peak periods to balance response efficiency and resource consumption;
• Load prediction optimization tools: Based on historical user scale data (such as user growth curves from the past three months, interaction frequency fluctuation patterns) and real-time market signals (such as community activity levels, search popularity), construct AI prediction models to predict user scale peaks 12 hours in advance (for example, predicting that user interaction frequency will peak between 14:00-16:00 the next day), and expand computing power resources in advance to avoid protection delays during peak periods.
The core value of this architecture lies in enhancing the scalability elasticity of security services. Data shows that it can reduce risk detection delays during explosive user scale increases to within 500 milliseconds, increase the utilization rate of computing power resources by over 60%, while reducing security service operating costs by 35%.
2. Security compatibility system of technical architecture iteration: adapting to the protection needs of the new public chain architecture
As the Meme coin projects gradually deploy to Layer 2 (Optimism, Arbitrum) and modular public chains (Celestia, Cosmos), the technical characteristics of the new architecture (such as the Rollup data compression mechanism of Layer 2 and the separation architecture of 'execution layer-consensus layer-data layer' of modular public chains) significantly differ from traditional public chains, resulting in 'compatibility failure' of traditional security solutions— for example, contract vulnerability detection tools developed based on the Ethereum mainnet cannot identify vulnerabilities in the 'data on-chain verification logic' of Layer 2 Rollup contracts; risk monitoring modules designed for monolithic public chains struggle to adapt to the security risks of 'cross-layer data interaction' in modular public chains. The security compatibility system iterated by Bubblemaps' developed technical architecture achieves security coverage of the new public chain architecture through the design of 'architecture feature adaptation modules, cross-architecture security rule transformation, and compatibility verification mechanisms.'
The core technical design of the system includes:
• New architecture characteristic adaptation module: Develop dedicated protection modules for different new architecture technical logics.
◦ For Layer 2 (Optimism/Arbitrum): Develop a 'Rollup data security verification module' to adapt to its 'off-chain computation, on-chain verification' characteristics, focusing on monitoring the integrity during the Rollup data compression process (such as whether there is data tampering) and the compliance of on-chain verification logic (such as whether verification nodes correctly execute verification rules), while constructing a 'Layer 2-Layer 1 cross-layer risk linkage detection tool' to identify data inconsistency risks during cross-layer asset transfers;
◦ For modular public chains (Celestia): Develop a 'layered security monitoring module' to specifically monitor the 'data layer' (data availability verification), 'execution layer' (contract execution safety), and 'consensus layer' (compliance of consensus node behavior), while designing 'cross-layer interaction security verification rules' to prevent interaction logic vulnerabilities between the execution layer and data layer (such as data not being on-chain but execution confirmation completed);
• Cross-architecture security rule transformation engine: Transform the security rules of traditional public chains (such as contract permission detection, risk address interception) into rule formats suitable for the new architecture. For example, transform the 'contract permission anomaly determination rules' of the Ethereum mainnet into a dual determination rule of 'Rollup contract permissions + Layer 1 verification permissions' in Layer 2 scenarios; transform the 'transaction anomaly monitoring rules' of monolithic public chains into 'cross-layer transaction data + execution results' linked monitoring rules in modular public chains, ensuring the logical consistency of security rules across different architectures;
• Compatibility verification mechanism: Establish a 'new architecture security compatibility testing library,' which includes typical technical scenarios of the new architecture (such as batch transaction processing of Layer 2, cross-layer asset transfer of modular public chains) and known risk cases. Before the security solution goes live, it must pass more than 200 compatibility tests from the testing library (such as rule transformation accuracy, monitoring coverage rate), while jointly verifying with the official team of the new architecture and third-party security agencies to ensure that the security solution has no compatibility conflicts with the new architecture.
The implementation of this system can solve the security compatibility issues under the new architecture, increasing the security risk coverage rate of Meme coin projects on the new architecture to over 88%, while shortening the security adaptation cycle for new architecture deployment by more than 70%.
3. Security capability extension solutions for edge scenarios: covering the protection blind spots of non-core scenarios
Currently, the security capabilities of the Meme coin ecosystem are mainly concentrated in core scenarios such as 'transactions, cross-chain, and asset storage,' while the security protection of edge scenarios such as on-chain governance (e.g., proposal voting), community voting (e.g., community decision-making), and token staking (e.g., staking unlocking rules) is relatively weak, leading to risks such as 'governance voting being manipulated' or 'abnormal modifications of staking rules'—for example, in a certain project’s on-chain governance voting, due to the lack of verification of the voting account's identity compliance, a large number of fake accounts participated in the voting, affecting the fairness of the decision-making. The edge scenario security capability extension solution launched by Bubblemaps extends security capabilities to edge scenarios through the design of 'scenario risk decomposition, security node embedding, and full-process monitoring.'
The core scenarios and technical designs of the program include:
• On-chain governance scenarios: Decompose core security requirements into 'voting account compliance, proposal content security, voting process fairness.' In terms of technical solutions, develop 'governance voting security verification modules' to verify the 'on-chain behavior history' of voting accounts (such as whether they are long-term active accounts, whether there are abnormal associated addresses), filtering out fake or zombie accounts; also conduct 'security impact assessments' on proposal content to identify terms that may affect user assets (such as contract parameter modifications, staking rule adjustments), generating assessment reports for voting users to reference; during the voting process, real-time monitoring of 'abnormal voting frequencies, concentrated voting by large accounts' occurs to prevent voting manipulation risks;
• Community voting scenarios: For non-on-chain voting within the Meme coin community (such as project direction, event planning), decompose core security requirements into 'voting identity authenticity, voting data tampering prevention.' In terms of technical solutions, adopt a 'off-chain identity-on-chain certificate' binding mechanism, requiring users to verify community identity through wallet signature to avoid anonymous false voting; voting data is synchronized in real-time to 'distributed storage nodes,' using blockchain hash verification technology to ensure data is tamper-proof, while supporting users to query voting records and data verification results at any time;
• Token staking scenarios: Decompose core security requirements into 'staking rule compliance, unlocking process safety, staking asset monitoring.' In terms of technical solutions, develop 'staking contract security detection modules' to focus on verifying the logical integrity of staking rules (such as lock-up period, return rate calculation, unlocking conditions) to avoid user asset losses due to rule vulnerabilities; during the staking process, real-time monitoring of 'staking asset flow, contract call anomalies' occurs, automatically triggering early warnings when anomalies appear (such as 'staking assets not entering the designated custody address' or 'unlocking conditions not met but unlocking is triggered'); simultaneously provide a 'staking asset security dashboard' where users can view the status of staking assets, unlocking progress, and potential risk alerts in real time.
The core value of this solution lies in eliminating protection blind spots in edge scenarios, increasing the security scenario coverage rate of the Meme coin ecosystem from 60% to over 92%, while the occurrence rate of security incidents in edge scenarios decreases by more than 80%.
Future: The 'elasticity, compatibility, and full-scenario coverage' of security will become the main axis of industry development
The core breakthrough of Bubblemaps lies in breaking out of the traditional framework of 'static security' and constructing a more adaptive security system tailored to the characteristics of the Meme coin ecosystem—responding to scaling challenges through dynamic adaptive architecture, covering new architectures through compatibility systems, and eliminating protection blind spots through edge extension solutions, always focusing on the sustainability and ecological adaptability of security technology.
From the perspective of industry development trends, as the user scale of the Meme coin ecosystem further expands (such as penetrating into Web2 users), the technical architecture evolves into more complex forms (such as the integration of AI and blockchain), and scenario boundaries extend into more fields (such as on-chain social interactions, lightweight services), 'elasticity of security services,' 'standardization of technical compatibility,' and 'full-link coverage of scenarios' will become core directions. It is expected that Bubblemaps will further deepen the technical path: on one hand, optimizing the AI prediction accuracy of the dynamically adaptive architecture to enhance the rationality of computing power allocation; on the other hand, promoting the joint construction of industry standards for new architecture security compatibility, working with public chain teams to formulate security adaptation guidelines for modular public chains and Layer 2; while continuously expanding the coverage of edge scenarios to extend security capabilities to emerging scenarios such as 'on-chain social interactions' and 'lightweight asset services.' Ultimately, its design logic is expected to provide a reference for the sustainable development of security in the Meme coin ecosystem and promote the industry's shift from 'passive protection' to 'active adaptation and comprehensive coverage' of a new security paradigm.
