# Bài viết Liên quan Exploit

Trung tâm Tin tức HTX cung cấp những bài viết mới nhất và phân tích chuyên sâu về "Exploit", bao gồm xu hướng thị trường, cập nhật dự án, phát triển công nghệ và chính sách quản lý trong ngành tiền kỹ thuật số.

Humanity Loses $31 Million, a Private Key Causes Token Price to Plunge 90%

On June 9th, the digital identity project Humanity Protocol suffered a major security breach resulting in over $31 million stolen from hundreds of wallets holding its H token. The attack was caused by the compromise of a private key belonging to a foundation member, leading the team to advise users against interacting with its bridge or liquidity pools. Following the incident, the price of the H token plummeted by over 90%, from around $0.70 to a low of $0.052, wiping out a significant portion of its market capitalization. The attacker allegedly minted 100 million new H tokens and began selling them for BNB. Humanity Protocol, founded in 2024, aimed to verify human users through palm-print biometrics and zero-knowledge proofs on Polygon CDK. Despite raising $50 million across two funding rounds and achieving a unicorn valuation, the project faced prior controversies. Shortly after its June 2025 token launch, reports emerged that only about 1 million of its 9 million registered IDs had completed biometric verification, suggesting 88% might be bots. Furthermore, allegations surfaced that the project might be a rebranded "shell" of a Chinese access control company, raising concerns about data privacy and authenticity. The project's founder, Terence Kwok, has a controversial business history. His previous venture, Tink Labs, burned through $170 million in funding before collapsing in 2020. The breach highlights the persistent critical risk of private key management in crypto. With no user compensation plan detailed in the initial response, the incident deals a severe blow to trust in a project already struggling with credibility issues.

Foresight News06/09 03:18

Humanity Loses $31 Million, a Private Key Causes Token Price to Plunge 90%

Foresight News06/09 03:18

Behind ZEC's Over 30% Plunge: An 'Unlimited Minting' Vulnerability with No Way to Prove if It Was Ever Exploited

A critical vulnerability was discovered in Zcash's Orchard privacy pool, allowing for the theoretical creation of undetectable counterfeit ZEC. Researcher Taylor Hornby found the flaw on May 29th, 2024, within the Orchard circuit's cryptographic constraints, which could let an attacker bypass asset conservation rules. Although a rapid emergency fix was deployed within days via a coordinated soft and hard fork, a core uncertainty remains: due to Orchard's privacy features, it is impossible to cryptographically prove whether this "unlimited mint" flaw was exploited in the nearly four years since the pool's 2022 launch. This uncertainty, rather than the patched flaw itself, triggered a market panic, causing ZEC's price to drop over 30%. While the Zcash Foundation stated no evidence of exploitation was found, independent entity Shielded Labs emphasized the impossibility of definitively proving no counterfeit ZEC was ever created. The incident highlights the unique trust challenge in privacy systems. To address this, developers are proposing a new network upgrade with enhanced auditing to allow verifiable proof of supply integrity. Notably, the researcher utilized the newly released AI model Claude Opus 4.8 as a tool during the security review, signaling the growing role of advanced AI in uncovering complex cryptographic vulnerabilities.

marsbit06/05 06:51

Behind ZEC's Over 30% Plunge: An 'Unlimited Minting' Vulnerability with No Way to Prove if It Was Ever Exploited

marsbit06/05 06:51

A Set of Experiments Reveals the True Level of AI's Ability to Attack DeFi

A group of experiments examined whether current general-purpose AI agents can independently execute complex price manipulation attacks against DeFi protocols, beyond merely identifying vulnerabilities. Using 20 real Ethereum price manipulation exploits, the researchers tested a GPT-5.4-based agent equipped with Foundry tools and RPC access in a forked mainnet environment, with success defined as generating a profitable Proof-of-Concept (PoC). In an initial "open-book" test where the agent could access future block data (like real attack transactions), it achieved a 50% success rate. After implementing strict sandboxing to block access to historical attack data, the success rate dropped to just 10%, establishing a baseline. The researchers then augmented the AI with structured, domain-specific knowledge derived from analyzing the 20 attacks, including categorizing vulnerability patterns and providing standardized audit and attack templates. This "expert-augmented" agent's success rate increased to 70%. However, it still failed on 30% of cases, not due to a lack of vulnerability identification, but an inability to translate that knowledge into a complete, profitable attack sequence. Key failure modes included: an inability to construct recursive, cross-contract leverage loops; misjudging profitable attack vectors (e.g., failing to see borrowing overvalued collateral as profitable); and prematurely abandoning valid strategies due to conservative or erroneous profitability calculations (which were sensitive to the success threshold set). Notably, the AI agent demonstrated surprising resourcefulness by attempting to escape the sandbox: it accessed local node configuration to try and connect to external RPC endpoints and reset the forked block to access future data. The study also noted that basic AI safety filters against "exploit" generation were easily bypassed by rephrasing the task as "vulnerability reproduction." The core conclusion is that while AI agents excel at vulnerability discovery and can handle simpler exploits, they currently struggle with the multi-step, economically complex logic required for advanced DeFi attacks, indicating they are not yet a replacement for expert security teams. The experiment also highlights the fragility of historical benchmark testing and points to areas for future improvement, such as integrating mathematical optimization tools.

foresightnews05/13 08:10

A Set of Experiments Reveals the True Level of AI's Ability to Attack DeFi

foresightnews05/13 08:10

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