← 研踪 PaperTrailarXiv:2611.04411 · v1
TxBench: A Benchmark of Attack Transactions and Evidence-Backed Negatives on Seven EVM Chains
首次提交 2026-11-03 14:49
版本更新 2026-11-03 14:49
雷达观测 2026-11-04 23:40
摘要
Researchers evaluate detectors of malicious smart-contract transactions on datasets that each paper assembles anew. Their positives come from incident trackers, whose citations mix attacks with setup steps and transactions that never ran, or from a detector's own output, which makes the evaluation circular; their negatives are ordinary transactions. A shared benchmark needs positives whose own execution shows the attack and negatives that use the attacks' mechanisms, with no detector deciding either label. We present TxBench, a benchmark of attack transactions and evidence-backed negatives on seven EVM chains, with the five-step pipeline that builds it. The pipeline collects every transaction that BlockSec's incident library or the EVM Hack Registry cites, maps its weakness to OWASP's SCWE taxonomy, and rebuilds its execution from free data sources. A cited transaction qualifies as a valid TxBench attack only if it extracts value from others during execution, is consistent with all verified source claims, and is independently linked to the reported incident by corroborating evidence. Negative examples are sampled from each chain's traffic near the attacks and retained only when positive evidence confirms their legitimacy. Of 1,850 cited transactions, TxBench accepts 1,012 attacks from 602 incidents, worth USD 868.1 million: 846 contract exploits and 166 key compromises. A blind review under rules fixed in advance confirms 98 of 100 sampled attacks (97.7% weighted) and all 100 sampled negatives. As baselines, four zero-shot LLMs reading anonymized traces are precise but find at most 0.43 of the attacks and no key compromise, leaving ample room for better detectors.
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v1 · 2026-11-03 14:49 · 最新观测版本
TxBench: A Benchmark of Attack Transactions and Evidence-Backed Negatives on Seven EVM Chains
Researchers evaluate detectors of malicious smart-contract transactions on datasets that each paper assembles anew. Their positives come from incident trackers, whose citations mix attacks with setup steps and transactions that never ran, or from a detector's own output, which makes the evaluation circular; their negatives are ordinary transactions. A shared benchmark needs positives whose own execution shows the attack and negatives that use the attacks' mechanisms, with no detector deciding either label. We present TxBench, a benchmark of attack transactions and evidence-backed negatives on seven EVM chains, with the five-step pipeline that builds it. The pipeline collects every transaction that BlockSec's incident library or the EVM Hack Registry cites, maps its weakness to OWASP's SCWE taxonomy, and rebuilds its execution from free data sources. A cited transaction qualifies as a valid TxBench attack only if it extracts value from others during execution, is consistent with all verified source claims, and is independently linked to the reported incident by corroborating evidence. Negative examples are sampled from each chain's traffic near the attacks and retained only when positive evidence confirms their legitimacy. Of 1,850 cited transactions, TxBench accepts 1,012 attacks from 602 incidents, worth USD 868.1 million: 846 contract exploits and 166 key compromises. A blind review under rules fixed in advance confirms 98 of 100 sampled attacks (97.7% weighted) and all 100 sampled negatives. As baselines, four zero-shot LLMs reading anonymized traces are precise but find at most 0.43 of the attacks and no key compromise, leaving ample room for better detectors.
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