Code detection method, apparatus, device, medium, and product

An electronic device, characterized in that the electronic device comprises a processor and a memory;

• and
• the processor is configured to execute instructions stored in the memory, to enable the electronic device to perform a code detection method,
• wherein the code detection method comprises:
• obtaining first code;
• performing tokenization on the first code to obtain a plurality of tokens;
• and
• inputting the plurality of tokens into a Mixture-of-Experts model, and receiving a code detection result output by the Mixture-of-Experts model,
• wherein the Mixture-of-Experts model comprises a first expert model configured to extract a feature related to a first-type attack, a second expert model configured to extract a feature related to obfuscated code, and a third expert model configured to extract a feature related to language model-generated code, the code detection result is determined based on at least one consisting of:
• the feature related to the first-type attack, the feature related to the obfuscated code, and the feature related to the language model-generated code, and the code detection result is used to represent whether the first code belongs to obfuscated code that is generated by a language model and used to perform the first-type attack.

A non-transitory computer-readable storage medium, characterized by comprising instructions, wherein the instructions instruct an electronic device to perform a code detection method,

• wherein the code detection method comprises:
• obtaining first code;
• performing tokenization on the first code to obtain a plurality of tokens;
• and
• inputting the plurality of tokens into a Mixture-of-Experts model, and receiving a code detection result output by the Mixture-of-Experts model,
• wherein the Mixture-of-Experts model comprises a first expert model configured to extract a feature related to a first-type attack, a second expert model configured to extract a feature related to obfuscated code, and a third expert model configured to extract a feature related to language model-generated code, the code detection result is determined based on at least one consisting of:
• the feature related to the first-type attack, the feature related to the obfuscated code, and the feature related to the language model-generated code, and the code detection result is used to represent whether the first code belongs to obfuscated code that is generated by a language model and used to perform the first-type attack.