Smart contract security concerns the measures taken to prevent flaws and vulnerabilities in self-executing contracts deployed on a blockchain. It involves rigorous code auditing, formal verification, and adherence to best practices to safeguard against exploits that could lead to loss of funds or manipulation of contract logic. Secure smart contracts are fundamental to the trust and functionality of decentralized applications.
Context
Smart contract security is a perpetual concern in the cryptocurrency news cycle, with frequent reports of exploits resulting in substantial financial losses. Discussions often revolve around common vulnerabilities such as reentrancy attacks, integer overflows, and access control issues. The ongoing development of advanced security tools and auditing methodologies is critical for bolstering confidence in the smart contract ecosystem.
A novel system leverages large language models and retrieval-augmented generation to automate smart contract property creation, enhancing security and accessibility.
Researchers introduce a formal theory of Maximal Extractable Value, providing a rigorous framework to understand and counter economic attacks in decentralized systems.
This research introduces PropertyGPT, an AI-powered system that automates comprehensive property generation, overcoming a critical bottleneck in smart contract formal verification.
This research establishes a foundational, abstract model for Maximal Extractable Value, enabling rigorous security proofs and advancing blockchain integrity.
Evolving smart contract vulnerabilities, from access control to oracle manipulation, expose digital assets to systemic exploitation, demanding adaptive security postures.
The persistent vulnerability of DeFi protocols to flash loan attacks, smart contract exploits, and off-chain compromises presents an escalating threat to user capital and systemic stability.
The OWASP Smart Contract Top 10 for 2025 highlights persistent architectural flaws, posing systemic risk to decentralized finance protocols and user assets.
PropertyGPT leverages large language models and retrieval-augmented generation to automatically create formal specifications, significantly improving smart contract security.
This research introduces a systematization of AI agents for blockchain, proposing a four-layer architecture that enables intelligent automation and addresses critical security and privacy challenges.
This research introduces a framework for smart contracts that ensures both on-chain and off-chain data privacy, enabling secure and anonymous decentralized applications.
A misconfigured cross-chain bridge allowed an attacker to mint unauthorized tokens, triggering a significant market cap collapse and undermining trust in interoperability protocols.
This research validates large language models as potent verification oracles, simplifying complex smart contract auditing and bridging AI with formal methods.
A delegate call vulnerability in the UXLINK multisig wallet granted an attacker administrative control, enabling unauthorized token minting and significant asset draining.
This research synthesizes cryptographic principles with practical scheme designs to fortify blockchain systems against prevalent attacks, enhancing resilience across all architectural layers.
This research introduces three universal properties—Validity, Liquidity, and Fidelity—to formally verify smart contract integrity, preventing critical exploits across diverse applications.
Kontrol revolutionizes EVM smart contract security by integrating formal verification with existing tests, enabling scalable, mathematically certain code correctness.
A new formal verification tool, Certora Sunbeam Prover, ensures the correctness of Stellar smart contracts, enabling robust and secure decentralized finance applications.
This analysis reveals how smart contract language design fundamentally impacts formal verification efficacy, paving the way for more secure blockchain architectures.
UP Protocol redefines decentralized finance with a deflationary token model and AI-driven risk management, establishing a sustainable, community-governed ecosystem.
This research introduces a Post-Quantum Secure Blockchain, leveraging novel cryptographic primitives to safeguard decentralized systems from quantum computing attacks.
A new framework leverages large language models to automate the creation of robust verification properties, significantly improving smart contract security analysis.
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