AI-native security for business logic, intent, and semantic risk
面向业务逻辑、意图理解与语义风险的 AI 原生安全基础设施
Tanwe AI builds AI-native security infrastructure for modern applications. We focus on the layer where traditional scanners are weakest: business logic, authorization semantics, workflow integrity, and intent-level behavior.
Our work combines security research, program analysis, and large language model agents to help teams identify vulnerabilities that depend on context rather than simple signatures.
Make intent-level security measurable, testable, and operational for every engineering team.
- Business Logic Security — authorization bypass, workflow abuse, state-machine flaws, and logic inconsistencies
- Semantic Security Analysis — AI-assisted understanding of application behavior and business intent
- Agentic Security Testing — structured security workflows for code review, self-assessment, and authorized testing
- Developer-First Remediation — practical findings, reproducible evidence, and clear mitigation guidance
- Email: business@tanweai.com
- Website: https://tanweai.com
Tanwe AI 专注于构建 AI 原生的安全基础设施，重点关注传统扫描器最不擅长的领域：业务逻辑、权限语义、流程完整性与意图层行为。
我们的工作结合安全研究、程序分析与大语言模型 Agent，帮助团队发现那些依赖上下文理解、而不是简单规则匹配才能识别的安全问题。
让意图层安全变得可度量、可测试、可落地。
- 业务逻辑安全 — 权限绕过、流程滥用、状态机缺陷与逻辑不一致
- 语义安全分析 — 基于 AI 的应用行为理解与业务意图分析
- Agentic 安全测试 — 面向代码审计、自我检查与授权测试的结构化安全工作流
- 开发者友好修复 — 可复现证据、清晰风险说明与可执行修复建议
- Email: business@tanweai.com
- Website: https://tanweai.com
Unless otherwise noted, code in this profile repository is released under the MIT License.
除非另有说明，本 profile 仓库中的代码采用 MIT 许可证。