Event Overview

Recently, the Trust Wallet browser extension v2.68 exposed a security incident, with the official statement indicating a timeline pointing to December 29, 2025, and confirming that 2,596 wallet addresses have been affected. In response to this incident, the platform has received and processed approximately 5,000 compensation applications, a number that far exceeds the affected addresses themselves, directly revealing the core contradiction of this incident: how to prevent duplicate applications, false claims, and even organized malicious claims while ensuring that genuinely harmed users receive compensation. The project team has publicly emphasized that in terms of compensation strategy, "accuracy takes precedence over speed" to ensure that funds can flow back to the truly harmed wallets, rather than being exploited by information asymmetry and process loopholes. It is reported that Trust Wallet expects to announce further developments within the next day, including more detailed compensation processes and reviews, and market participants need to continuously track official announcements to obtain more complete and authoritative event information and risk warnings.

Damage Profile

From the currently disclosed data, the 2,596 affected wallet addresses correspond to approximately 5,000 compensation applications, showing a nearly 1:2 one-to-many relationship, which means a single address may have multiple duplicate submissions, leaving room for non-affected users to attempt to "claim compensation." The number of applications significantly exceeds the number of confirmed affected addresses, objectively increasing Trust Wallet's risk control pressure: on one hand, it needs to quickly clean and filter a large amount of application data, and on the other hand, it must screen for potential clusters of related addresses and abnormal application patterns. Theoretically, the project team can utilize publicly available on-chain data to structurally characterize the genuinely harmed group, for example:
• Analyzing the transaction trajectories and fund flows of related addresses before and after the attack to identify whether they indeed overlap significantly with the use of the v2.68 extension;
• Comparing historical interaction objects, commonly used chains, and interaction frequencies to determine whether they are long-term genuine users rather than temporarily created "claim accounts";
• Combining the behavioral characteristics of addresses on other protocols to filter out suspicious accounts with batch registrations and homogeneous behaviors. This method, based on on-chain behavior and historical interaction profiles, will directly impact the boundaries and accuracy of the compensation list.

Compensation Verification

In terms of compensation strategy, Trust Wallet has clearly stated that "accuracy takes precedence over speed," meaning that even in the face of public opinion and user strong expectations for "quickly getting their money back," the platform still chooses to extend the review and disbursement pace to reduce the error rate and the possibility of malicious exploitation. Based on currently available information, a multi-dimensional cross-validation approach may be inferred: first, conducting fine-grained searches of on-chain transaction records, comparing the loss time reported by users with the time window of the v2.68 extension's release and risk exposure, excluding addresses not within the risk range; second, verifying whether users have indeed used the corresponding version of the extension in the relevant environment, using client version information, browser fingerprints, and other metadata for basic screening; third, performing consistency checks between the wallet addresses, reported loss situations in the application information, and real on-chain data to identify "fabricated losses" in false claims. On this basis, threshold strategies and list management can be further layered, such as setting higher review thresholds for high-risk pattern addresses, blacklisting obviously abnormal applications, establishing whitelist channels for highly matched genuinely harmed groups, and supplementing with manual reviews to confirm cases that are ambiguous at the boundary, sensitive in amount, or complex in on-chain behavior, thereby improving overall compensation accuracy through a combination of "automated rules + list systems + manual sampling."

AI Poisoning Links

In the peripheral discussions surrounding this incident, Slow Mist founder Yu Xian recently reminded users to be wary of AI prompt poisoning attacks, a security issue that has potential links to the wallet extension incident in terms of risk paradigms. Public statements indicate that once certain AI tools' "danger modes" are activated, these tools can fully automate control of users' computers without any additional confirmation, meaning that as long as the upstream prompt is poisoned, the AI tool itself may be transformed into a remote script executor for attackers. In the wallet usage scenario, if users manage assets with a browser extension in the same environment while granting high permissions to AI tools with system control capabilities, then the chain from malicious prompts to indirect control of the browser extension is established: the frontend may start with "seemingly harmless questions," gradually inducing the model to download and execute scripts, modify system configurations, until it calls the browser in the background, simulates clicks, injects content, or steals session information. Although there is currently no public evidence indicating that the v2.68 incident necessarily followed this path, user-side security configurations have become a key variable, including limiting AI tools' system-level permissions, isolating high-value wallet operation environments, and cautiously loading and authorizing browser plugins; otherwise, once AI tools are "prompt poisoned," their automation capabilities will amplify the risk exposure of wallet extensions.

Macro and Sentiment

Beyond individual security incidents, the macro liquidity environment is also an important background affecting on-chain behavior. Data from a single source indicates that the People's Bank of China recently injected 482.3 billion yuan of liquidity into the market through reverse repurchase operations, a figure that represents a relatively large-scale short-term capital injection in the traditional financial system, but its impact on cryptocurrency prices and on-chain sentiment tends to be more indirect. In the current environment, on one hand, security incidents like those involving Trust Wallet have impacted user confidence, prompting some funds to adopt a wait-and-see approach, withdraw from high-traffic applications, or shift to more "cold" asset storage methods; on the other hand, the marginal easing of macro liquidity provides potential support for risk assets, with some investors possibly leveraging easing expectations to increase positions in high Beta assets or explore new opportunities. The combination of security incidents and liquidity backgrounds has made the paths of on-chain capital migration more differentiated: risk-averse users are more inclined to contract their positions, transferring assets to multi-signature wallets, hardware wallets, or centralized exchanges (CEX), while risk-tolerant users may seek entry points amid the "negative market crash + liquidity support" dislocation. Overall, the "impact of security incidents" suppresses short-term sentiment, while "liquidity support" provides underlying buffering over a longer period, and the tug-of-war between these two forces is an important observation dimension for recent market fluctuations.

Risk Control Insights

Surrounding the browser extension v2.68 incident, a series of improvement directions for wallet and browser plugin institutional construction can be distilled: at the monitoring level, more granular behavior monitoring and abnormal pattern recognition mechanisms are needed, with real-time alerts for abnormal authorization requests, batch signing behaviors, and sensitive operations after version updates; at the alert and stop-loss level, the ability to quickly delist or forcibly disable risky versions should be established, and risk alerts should be pushed through multiple channels to guide users to evacuate high-risk environments at the first opportunity. From the perspective of compensation mechanism design, project parties need to dynamically balance efficiency, fairness, and fraud prevention: efficiency requires prompt verification and disbursement, fairness requires not to overlook genuinely harmed small and long-tail users, while fraud prevention necessitates embedding sufficient anti-abuse constraints in the process, such as information consistency checks, risk control scoring, and tiered reviews. For ordinary users, this incident also highlights the importance of basic security habits: in terms of AI tool authorization, avoid granting high permissions that allow system-level control or arbitrary file access; in plugin management, regularly clean unnecessary browser extensions, prioritize using official channels and open-source projects, and disable automatic interactions with unknown websites; in asset storage architecture, adopt a method of "small daily transactions in hot wallets, large long-term holdings in cold wallets, and layered multi-address management" to reduce the impact of single points of failure on overall asset security.

Follow-up Observations

Regarding the security incident and compensation progress of the Trust Wallet browser extension v2.68, current public information remains limited, especially in key dimensions such as specific compensation amounts, loss scales, and complete technical reviews, and we still need to wait for official follow-up announcements to provide more detailed data and timelines. From a regulatory and industry perspective, this incident also overlays new risks such as AI tool abuse and prompt poisoning, and in the near future, regulatory attention to wallet infrastructure security, AI tool permission boundaries, and the compliance of browser extension ecosystems is likely to increase, raising the standards for project parties in self-examination and information disclosure. From a longer-term perspective, this incident is not only a stress test of a single project's risk control capabilities but also a concentrated exposure of the entire industry's shortcomings in security, compliance, and user education: in terms of security, more systematic version governance, reliance audits, and multi-layered protection are needed; in terms of compliance, compensation processes, incident reporting, and user protection mechanisms need to be more transparent and predictable; in terms of user education, more ordinary users need to realize that AI tools and browser extensions are not "zero-cost efficiency tools," but high-permission tools that must be managed with caution. If relevant experiences can be distilled into industry-wide standards and best practices, the scope of losses and the difficulty of handling similar incidents in the future are expected to be significantly reduced.

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