Security Analysis of Ripple Consensus

Ignacio, Amores-Sesar,; Cachin, Christian; Jovana, Mićić,

doi:10.4230/lipics.opodis.2020.10

Cited by 2 publications

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“…To simulate a double-spend attack on the XRPL client, we have first deployed a network of ten validators configured as a full mesh network, which means every validator was connected to every other. All validators were set to participate in the consensus process and were included in the so-called unique node list (UNL) [27]. This configuration was chosen to maximize the number of nodes participating in the consensus process, making the network more robust and representative.…”

Section: ) Simulating and Analyzing Double Spend Attacks On Xrpl Usin...mentioning

confidence: 99%

Validating the Blockchain Benchmarking Framework Through Controlled Deployments of XRPL and Ethereum

Touloupou,

Christodoulou,

Themistocleous

2024

IEEE Access

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In the evolving domain of blockchain, a critical challenge lies in the performance analysis of blockchains under controlled test conditions. This paper focuses on validating the Blockchain Benchmarking Framework (BBF), developed for the evaluation of blockchain protocols in a controlled environment. The BBF's robustness and versatility are demonstrated through its application to the official Docker clients of Ripple's XRP Ledger (XRPL) and Ethereum, deployed in private, local and controlled environments. These deployments are utilized to simulate network dynamics, transaction throughput, and resilience in a variety of scenarios. Our methodology encompasses tests ranging from standard operational conditions to adverse scenarios, including node failures and simulated double-spend attacks. These controlled environments are essential for evaluating the BBF's efficacy in stress testing blockchain protocols and assessing their stability and robustness. The BBF's ability to accurately capture and analyze performance characteristics is highlighted, providing insights into the operational mechanics, scalability, and resilience of these blockchain clients. The findings emphasize the BBF's adaptability and effectiveness in managing different blockchain protocols, reaffirming its potential for broader application in pre-launch testing and analysis of blockchain performance. This study contributes to the understanding of how blockchain clients can be preliminarily assessed before mainnet deployment as well as to validate all the design decisions made by the protocol under different settings and synthetic scenarios.

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Section: ) Simulating and Analyzing Double Spend Attacks On Xrpl Usin...mentioning

confidence: 99%

Validating the Blockchain Benchmarking Framework Through Controlled Deployments of XRPL and Ethereum

Touloupou,

Christodoulou,

Themistocleous

2024

IEEE Access

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Randomized Testing of Byzantine Fault Tolerant Algorithms

Winter

Buse

Graaf

et al. 2023

Proc. ACM Program. Lang.

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Byzantine fault-tolerant algorithms promise agreement on a correct value, even if a subset of processes can deviate from the algorithm arbitrarily. While these algorithms provide strong guarantees in theory, in practice, protocol bugs and implementation mistakes may still cause them to go wrong. This paper introduces ByzzFuzz, a simple yet effective method for automatically finding errors in implementations of Byzantine fault-tolerant algorithms through randomized testing. ByzzFuzz detects fault-tolerance bugs by injecting randomly generated network and process faults into their executions. To navigate the space of possible process faults, ByzzFuzz introduces small-scope message mutations which mutate the contents of the protocol messages by applying small changes to the original message either in value (e.g., by incrementing the round number) or in time (e.g., by repeating a proposal value from a previous message). We find that small-scope mutations, combined with insights from the testing and fuzzing literature, are effective at uncovering protocol logic and implementation bugs in real-world fault-tolerant systems. We implemented ByzzFuzz and applied it to test the production implementations of two popular blockchain systems, Tendermint and Ripple, and an implementation of the seminal PBFT protocol. ByzzFuzz detected several bugs in the implementation of PBFT, a potential liveness violation in Tendermint, and materialized two theoretically described vulnerabilities in Ripple’s XRP Ledger Consensus Algorithm. Moreover, we discovered a previously unknown fault-tolerance bug in the production implementation of Ripple, which is confirmed by the developers and fixed.

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Security Analysis of Ripple Consensus

Cited by 2 publications

References 0 publications

Validating the Blockchain Benchmarking Framework Through Controlled Deployments of XRPL and Ethereum

Validating the Blockchain Benchmarking Framework Through Controlled Deployments of XRPL and Ethereum

Randomized Testing of Byzantine Fault Tolerant Algorithms

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