Expired50% confidenceFactExact time
Large models are capable of deobfuscating obfuscated code and directly outputting usable Python implementation code while also extracting SM2 and SM4 key pairs.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/20/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 10/18/2026(expired)
Sources
Related Claims
UnverifiedThe author used DeepSeek to restore the located obfuscated code and generate complete Python code containing hashlib, json, and SM2/SM4 processing; the generated code was verified to work and produced the correct encryption results.71% similarUnverifiedLarge language models with strong reasoning capabilities can understand code semantic logic and discover new types of defects that have never appeared in known vulnerability databases.68% similarUnverified大模型能识别代码模式而非仅代码字面，即便变量名被混淆，只要算法骨架与已知算法匹配便能还原语义66% similarUnverified简单代码补全用轻量模型即可，涉及跨文件重构、架构级推理时才需要旗舰能力66% similarUnverifiedopen-code-review adopts a hybrid architecture that combines a deterministic rule engine with a large language model Agent.64% similar
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