sherlock-project/sherlock
Jan 2025 – Jan 2025
1 Month active
Languages Used
BashDockerfileJSONMarkdown
Technical Skills
API IntegrationCloud ComputingDevOpsDocumentationServerless
Adam Kliment
PROFILE
Adam Kliment
Adam developed a serverless username reconnaissance solution for the sherlock-project/sherlock repository by implementing an Apify Actor. He designed and built the actor script to process input data and push results, leveraging Dockerfile for containerization and Bash for scripting. Adam ensured the solution was cloud-ready and reproducible by providing comprehensive documentation, including updates to the main README and a dedicated guide detailing input/output contracts and deployment instructions. His work focused on API integration and DevOps best practices, resulting in a single, traceable feature commit that established a scalable foundation for automated reconnaissance workflows without introducing any bug fixes.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
220
Activity Months1
Your Network
41 people
Work History
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025: Implemented Apify Actor for the Sherlock project to enable serverless username reconnaissance. Added a Dockerfile for building the actor, an actor script to process inputs and push results, and comprehensive usage/documentation. Main repository README updated to describe how to use the Apify Actor and its IO contract. All changes are traceable to a single feature commit, laying groundwork for scalable, reproducible reconnaissance workflows.
1 Commits • 1 Features
Jan 1, 2025January 2025: Implemented Apify Actor for the Sherlock project to enable serverless username reconnaissance. Added a Dockerfile for building the actor, an actor script to process inputs and push results, and comprehensive usage/documentation. Main repository README updated to describe how to use the Apify Actor and its IO contract. All changes are traceable to a single feature commit, laying groundwork for scalable, reproducible reconnaissance workflows.
January 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
BashDockerfileJSONMarkdown
Technical Skills
API IntegrationCloud ComputingDevOpsDocumentationServerless
Repositories Contributed To
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