Pith. sign in

REVIEW 1 cited by

FORAY: Towards Effective Attack Synthesis against Deep Logical Vulnerabilities in DeFi Protocols

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2407.06348 v3 pith:PAWUM3PT submitted 2024-07-08 cs.CR cs.PL

classification cs.CRcs.PL
keywords defiprotocolsattacksmartcontractsforaycompilationdeep
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Blockchain adoption has surged with the rise of Decentralized Finance (DeFi) applications. However, the significant value of digital assets managed by DeFi protocols makes them prime targets for attacks. Current smart contract vulnerability detection tools struggle with DeFi protocols due to deep logical bugs arising from complex financial interactions between multiple smart contracts. These tools primarily analyze individual contracts and resort to brute-force methods for DeFi protocols crossing numerous smart contracts, leading to inefficiency. We introduce Foray, a highly effective attack synthesis framework against deep logical bugs in DeFi protocols. Foray proposes a novel attack sketch generation and completion framework. Specifically, instead of treating DeFis as regular programs, we design a domain-specific language (DSL) to lift the low-level smart contracts into their high-level financial operations. Based on our DSL, we first compile a given DeFi protocol into a token flow graph, our graphical representation of DeFi protocols. Then, we design an efficient sketch generation method to synthesize attack sketches for a certain attack goal (e.g., price manipulation, arbitrage, etc.). This algorithm strategically identifies candidate sketches by finding reachable paths in TFG, which is much more efficient than random enumeration. For each candidate sketch written in our DSL, Foray designs a domain-specific symbolic compilation to compile it into SMT constraints. Our compilation simplifies the constraints by removing redundant smart contract semantics. It maintains the usability of symbolic compilation, yet scales to problems orders of magnitude larger. Finally, the candidates are completed via existing solvers and are transformed into concrete attacks via direct syntax transformation.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. AiRacleX: Automated Detection of Price Oracle Manipulations via LLM-Driven Knowledge Mining and Prompt Generation

    cs.CR 2025-02 conditional novelty 6.0 of 10

    A three-LLM pipeline (knowledge synthesis, prompt generation, auditing) is reported to detect 2.58x more price oracle manipulation bugs than GPTScan on 60 known DeFi vulnerabilities.

Pith tools