Tencent/AI-Infra-Guard
Dec 2025 – Dec 2025
1 Month active
Languages Used
Python
Technical Skills
AI IntegrationAPI integrationCyber SecurityDynamic AnalysisPythonPython scripting
sc
PROFILE
Sc
Cheng Sheng developed a major upgrade to the Tencent/AI-Infra-Guard Dynamic Analysis Framework, focusing on scalable security assessments for AI infrastructure. He designed and implemented asynchronous test-case generation and execution, expanded vulnerability detection to include credential leakage and prompt injection, and introduced rug pull detection. Using Python and asynchronous programming, Cheng stabilized the dynamic analysis workflow, improved server transport compatibility, and enhanced error handling for dynamic transports. His work addressed both feature development and bug fixes, resulting in faster security triage and broader automation. The depth of engineering demonstrated robust backend development and thoughtful integration of security testing and tool resilience.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
6Total
Bugs
1
Commits
6
Features
1
Lines of code
1,862
Activity Months1
Your Network
22 peopleSame Organization
@m.fudan.edu.cn4
Work History
December 2025
6 Commits • 1 Features
Dec 1, 2025Summary for 2025-12 (Tencent/AI-Infra-Guard): Delivered a major upgrade to the Dynamic Analysis Framework enabling scalable security assessments with new agents/tools, asynchronous test-case generation/execution, and expanded vulnerability coverage (credential leakage, prompt injection), rug pull detection, and updated server transport options. Completed and stabilized the dynamic analysis workflow, including framework debugging, and fixed server transport/type handling. Fixed MCP tooling description logic and improved server transport error handling to increase reliability under dynamic analysis. Overall impact: faster security triage, broader automation, and stronger transport resilience. Technologies demonstrated include dynamic analysis framework design, asynchronous task orchestration, multi-transport support, robust error handling, and tooling resilience (tool description and rug pull detection).
6 Commits • 1 Features
Dec 1, 2025Summary for 2025-12 (Tencent/AI-Infra-Guard): Delivered a major upgrade to the Dynamic Analysis Framework enabling scalable security assessments with new agents/tools, asynchronous test-case generation/execution, and expanded vulnerability coverage (credential leakage, prompt injection), rug pull detection, and updated server transport options. Completed and stabilized the dynamic analysis workflow, including framework debugging, and fixed server transport/type handling. Fixed MCP tooling description logic and improved server transport error handling to increase reliability under dynamic analysis. Overall impact: faster security triage, broader automation, and stronger transport resilience. Technologies demonstrated include dynamic analysis framework design, asynchronous task orchestration, multi-transport support, robust error handling, and tooling resilience (tool description and rug pull detection).
December 2025
Activity
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Quality Metrics
Correctness83.4%
Maintainability80.0%
Architecture80.0%
Performance76.6%
AI Usage56.6%
Skills & Technologies
Programming Languages
Python
Technical Skills
AI IntegrationAPI integrationCyber SecurityDynamic AnalysisPythonPython scriptingSoftware DevelopmentTool Developmentasynchronous programmingbackend developmentdynamic analysissecurity testingsoftware engineering
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