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Echo: Learning-based Matching Decompilation using Trusted Back Translation
Researchers introduce Echo, a matching decompiler using trusted back-translation that roughly doubles exact-match rates and outperforms GPT-5.6 and Codex on Mirai.
Echo performs matching decompilation by using compilation as trusted feedback for iterative search: a domain-specific model generates candidate code and compilation configurations, which are recompiled, compared at assembly level, and repaired via rule-based rewriting, neural refinement, and reasoning-based refinement. On function-level benchmarks, Echo produces 2.43x more exact matches than the strongest baseline and the highest structural similarity to ground truth. On the Mirai malware binary, it matches 2.75x and 7.4x as many functions as GPT-5.6 and Codex, respectively.
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Threat Brief: CVE-2022-41040 and CVE-2022-41082: Microsoft Exchange Server (ProxyNotShell)
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