sherlock-project/sherlock
Jan 2025 – Jan 2025
1 Month active
Languages Used
BashDockerfileJSONMarkdown
Technical Skills
API IntegrationCloud ComputingDevOpsDocumentationServerless
Adam Kliment
PROFILE
Adam Kliment
Developed and launched an Apify Actor for the sherlock-project/sherlock repository, enabling serverless username reconnaissance workflows. The work involved creating a Dockerfile for reproducible builds, implementing an actor script to process input data and push results, and updating both the main and dedicated READMEs with comprehensive documentation on usage and the actor’s input/output contract. Leveraging skills in API integration, cloud computing, and serverless architecture, the solution allows operators to deploy scalable reconnaissance tasks with clear operational guidance. All changes were consolidated into a single, traceable feature commit, emphasizing maintainability and clarity while utilizing Bash, Dockerfile, and JSON for implementation.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
220
Activity Months1
Your Network
43 peopleShared Repositories
43
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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