BinaryAI Python SDK

PUBLISH readthedocs Downloads Gitter

BinaryAI是腾讯安全科恩实验室基于在静态分析和AI安全领域的经验研发的二进制安全智能分析平台。本SDK旨在帮助用户上传文件并获取分析结果，也可以作为调用BinaryAI API的一个参考

要使用SDK，你需要相应的凭据。查看BinaryAI的文档 获取指引。

依赖版本

Python >= 3.9

下载和安装

python3 -m pip install binaryai

快速入门

请查看SDK文档。

内部细节

API地址

对公众的默认API地址是https://api.binaryai.cn/v1/endpoint。

API凭据

API凭据用于签名请求。你可以使用SDK进行签名，但也可以自行编写签名方法。我们使用和腾讯云一致的 TC3-HMAC-SHA256 方案，你可以阅读 腾讯云文档 获取技术细节。BinaryAI需要的签名信息是：

Region  = "ap-shanghai"
service = "binaryai"
Action  = "BinaryAI"
Version = "2023-04-15"

更多资料

Read the Changelog of our product, and hope you can also have fun reading papers related to our job:

  1. Yu, Zeping, et al. “Codecmr: Cross-modal retrieval for function-level binary source code matching.” Advances in Neural Information Processing Systems 33 (2020): 3872-3883.

  2. Yu, Zeping, et al. “Order matters: Semantic-aware neural networks for binary code similarity detection.” Proceedings of the AAAI conference on artificial intelligence. Vol. 34. No. 01. 2020.

  3. Li, Zongjie, et al. “Unleashing the power of compiler intermediate representation to enhance neural program embeddings.” Proceedings of the 44th International Conference on Software Engineering. 2022.

  4. Wong, Wai Kin, et al. “Deceiving Deep Neural Networks-Based Binary Code Matching with Adversarial Programs.” 2022 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE, 2022.

  5. Wang, Huaijin, et al. “Enhancing DNN-Based Binary Code Function Search With Low-Cost Equivalence Checking.” IEEE Transactions on Software Engineering 49.1 (2022): 226-250.

  6. Jia, Ang, et al. “1-to-1 or 1-to-n? Investigating the Effect of Function Inlining on Binary Similarity Analysis.” ACM Transactions on Software Engineering and Methodology 32.4 (2023): 1-26.

  7. Wang, Huaijin, et al. “sem2vec: Semantics-aware Assembly Tracelet Embedding.” ACM Transactions on Software Engineering and Methodology 32.4 (2023): 1-34.

  8. Jiang, Ling, et al. “Third-Party Library Dependency for Large-Scale SCA in the C/C++ Ecosystem: How Far Are We?.” Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis. 2023.