# Trust Related Articles

HTX News Center provides the latest articles and in-depth analysis on "Trust", covering market trends, project updates, tech developments, and regulatory policies in the crypto industry.

WLFI's Deletion Sparks Crash Speculation: Trust Crisis in a Bear Market

Amid a bearish market sentiment, the deletion of a tweet by Eric Trump, co-founder of World Liberty Financial (WLFI), triggered widespread speculation and panic. On February 23, Eric Trump retweeted and then deleted a post about Binance listing more USD1 trading pairs. This action led to a temporary depegging of USD1 to 0.9802 against USDT and a nearly 10% drop in WLFI’s price, though both later recovered. The incident fueled FUD (fear, uncertainty, and doubt) on social media, with rumors suggesting Eric had purged all crypto-related tweets or that internal issues plagued the Trump family. WLFI quickly responded, claiming it was a coordinated attack where hackers breached multiple co-founders’ accounts, spread panic, and attempted to profit by shorting WLFI. They later clarified that only X accounts were compromised, not WLFI or USD1 contracts. However, skepticism arose. Observers noted that only one retweet was removed—not a mass deletion—and no significant shorting activity was detected. Some linked the event to an upcoming major investigation announcement by on-chain detective ZachXBT, though market data did not strongly tie it to WLFI. Critics also questioned WLFI’s narrative, suggesting the “hack” claim might be a cover-up or misdirection. The event highlights the crypto community’s heightened sensitivity and distrust during bear markets, where minor actions can spark exaggerated reactions and conspiracy theories.

比推02/24 15:15

WLFI's Deletion Sparks Crash Speculation: Trust Crisis in a Bear Market

比推02/24 15:15

Behind the 2000 BTC Incident: The Fundamental Problem of CEX Ledgers

On February 6, Bithumb, a South Korean cryptocurrency exchange, mistakenly distributed 2,000 BTC each to 249 users due to a unit error during a promotional event—intending to give away 2,000 KRW (≈$1.4) per user. The total erroneous distribution amounted to 62,000 BTC, worth approximately $41.5–44 billion. Although these assets existed only in Bithumb’s internal ledger and not on-chain, they were tradable on the platform, causing BTC/KRW prices to drop nearly 17% within minutes and triggering over $400 million in derivatives liquidations. Bithumb responded within 35 minutes, freezing affected accounts and recovering over 99% of the misallocated BTC. The remaining 1,788 BTC were covered by the exchange’s own funds. The incident exposed a fundamental flaw in centralized exchanges (CEXs): their reliance on internal accounting systems that allow rapid balance adjustments without corresponding on-chain assets. This creates systemic risk, as user balances are essentially IOU entries rather than real assets. The article draws parallels with historical failures like Mt.Gox and FTX, where discrepancies between internal ledgers and actual reserves led to catastrophic collapses. While Bithumb’s quick response limited damage, the event underscores the structural vulnerabilities of CEXs, prompting South Korean regulators to consider stricter oversight. The piece concludes that such incidents highlight the inherent trust asymmetry in CEX operations, where users rely on exchanges to honor ledger entries as real assets—a risk that remains ever-present.

比推02/10 13:52

Behind the 2000 BTC Incident: The Fundamental Problem of CEX Ledgers

比推02/10 13:52

Behind the 2000 BTC Incident: The Fundamental Problem of CEX Ledgers

A critical incident at South Korean exchange Bithumb on February 6 revealed a fundamental vulnerability in centralized exchange (CEX) accounting systems. During a small promotional event intended to distribute around $1.4 per user, a configuration error caused the system to credit 695 users with 2,000 BTC each—totaling 1.24 million BTC, worth approximately $41.5–44 billion—instead of the intended 2,000 KRW. Although these assets were not on-chain, they were tradable on the platform, causing Bithumb’s BTC/KRW pair to drop nearly 17% and triggering brief global market turbulence. Bithumb responded within 35 minutes, freezing accounts and recovering over 99% of the erroneously credited funds. The remaining 1,788 BTC sold by users were covered by the exchange’s own capital. The event underscores a systemic risk in CEXes: user balances are often merely entries in an internal database, decoupled from actual on-chain reserves. This “accounting illusion” allows exchanges to modify balances without corresponding blockchain movement, creating a trust asymmetry where users rely on the platform’s promise rather than direct asset ownership. Historical precedents like Mt. Gox and FTX further highlight how such internal ledger systems can mask insolvency, enable fraud, or—as in Bithumb’s case—allow catastrophic errors. While Bithumb contained this incident due to its limited scale and rapid response, the episode has drawn regulatory scrutiny in South Korea, emphasizing the need for stronger oversight and structural safeguards in crypto trading platforms.

Odaily星球日报02/10 10:46

Behind the 2000 BTC Incident: The Fundamental Problem of CEX Ledgers

Odaily星球日报02/10 10:46

Behind the 2000 BTC Incident: The Fundamental Problem of CEX Ledgers

On February 6, Korean crypto exchange Bithumb mistakenly distributed 2,000 BTC (worth approximately $1.6 million at the time) to each of 249 users due to a unit configuration error in a promotional event, instead of the intended 2,000 KRW (about $1.4). The total erroneous distribution amounted to 62,000 BTC, with a notional value of $41.5–44 billion, far exceeding Bithumb’s actual Bitcoin holdings of 42,600 BTC. Although Bithumb recovered over 99% of the misallocated funds within 35 minutes by freezing accounts and covering the remainder with company assets, the incident exposed a fundamental flaw in centralized exchanges (CEXs): their reliance on internal ledgers that are decoupled from on-chain assets. Unlike decentralized exchanges, where transactions occur on-chain, CEXs use internal databases to record user balances, allowing instant—but potentially unbacked—asset entries. This creates systemic risk, as seen in historical failures like Mt. Gox (where internal ledger mismasks hid massive theft) and FTX (where customer funds were secretly diverted). The event underscores the trust asymmetry in CEXs: users see balances as real assets, but they are merely IOU promises. The Korean Financial Supervisory Service has since launched inspections, signaling heightened regulatory scrutiny. Bithumb’s near-disaster serves as a critical reminder of the inherent vulnerabilities in CEXs’ accounting models.

marsbit02/10 10:43

Behind the 2000 BTC Incident: The Fundamental Problem of CEX Ledgers

marsbit02/10 10:43

AI Trust Crisis Escalates, Blockchain Becomes an Indispensable 'Anti-Counterfeiting Layer'

AI systems are disrupting the internet, which was designed for human-scale interactions, by making it difficult to distinguish between human and machine-generated content, identities, and transactions. The core issue is the lack of a native method to differentiate humans from AI while preserving privacy and usability. Blockchain technology offers critical solutions through five key mechanisms: 1. AI can cheaply mimic human behavior at scale, but decentralized proof-of-personhood systems (e.g., World ID) increase the marginal cost of impersonation by enforcing uniqueness and scarcity. 2. Decentralized identity systems shift control from centralized platforms to users, reducing single points of failure and enhancing security and censorship resistance. 3. AI agents require portable, universal "passports" to operate across platforms without being locked into specific ecosystems, enabled by blockchain-based identity layers. 4. Existing payment systems are inadequate for AI agent-scale transactions; blockchain enables micro-payments, smart contracts, and programmable revenue sharing suitable for machine-to-machine commerce. 5. Privacy and security are intertwined: zero-knowledge proofs allow verification of attributes without exposing personal data, denying AI the raw materials needed for imitation. In summary, blockchain restores trust, raises impersonation costs, protects human-scale interactions, decentralizes identity, enforces privacy by default, and provides native economic infrastructure for AI agents—making it an essential layer for an AI-native internet.

比推02/05 15:30

AI Trust Crisis Escalates, Blockchain Becomes an Indispensable 'Anti-Counterfeiting Layer'

比推02/05 15:30

In 2026, Has the AI Agent Economy Truly Started to Operate?

The AI Agent economy reached a critical inflection point in January 2026, with three foundational layers—payments, trust, and social collaboration—becoming production-ready. The x402 protocol processed over 20 million transactions, ERC-8004 launched on Ethereum mainnet, and over 1.2 million autonomous agents registered on Moltbook. Infrastructure is now mature, but the product layer is still underdeveloped. While protocols are validated, key gaps remain in discovery mechanisms, capability verification, and middleware connecting trust and payment systems. x402 has stabilized with 89.2% of services priced between $0.01–$0.10, making microtransactions viable. ERC-8004 enables composable on-chain identity, reputation, and verification for agents. Despite a 68% drop in transaction count and 77% in volume, this reflects a shift from artificial volume to organic usage, with the buyer-to-seller ratio improving significantly. The biggest opportunities lie in demand-side solutions: a unified discovery layer (an "App Store for agents"), capability benchmarking beyond payment trust, and trust-gated payment middleware integrating ERC-8004 with x402. Primary paid use cases include trading signals, compute power, and granular data access. The ecosystem is consolidating around Base and Solana. While infrastructure development is concluding, builders must now focus on application-layer products, with a critical 2–3 month window to capitalize on the transition from protocol-ready to product-ready. Key risks include data noise, security vulnerabilities, and unresolved regulatory frameworks.

Odaily星球日报02/04 07:00

In 2026, Has the AI Agent Economy Truly Started to Operate?

Odaily星球日报02/04 07:00

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