Automate security assessments of REST and GraphQL API endpoints.
npx skills add https://github.com/noname300989/Security-Claw --skill api-tester-noname300989
Please help me install this Agent Skill. Skill: api-tester Source: https://github.com/noname300989/Security-Claw/tree/main/skills/api-tester Command: npx skills add https://github.com/noname300989/Security-Claw --skill api-tester-noname300989
This Skill addresses the critical need for robust security testing of both RESTful and GraphQL APIs, identifying vulnerabilities that could lead to data breaches, unauthorized access, and denial-of-service attacks.
Use the api-tester skill to perform a full security assessment on the GraphQL endpoint at https://api.example.com/graphql.
High-intent search queries and answers about installing and using this skill.
To test GraphQL APIs for security vulnerabilities, automated tools perform introspection-based discovery and execute targeted attacks like batch query exploitation and field suggestion analysis to uncover schema weaknesses and data exposure risks.
Yes, you can import OpenAPI or Swagger specifications to automatically discover REST API endpoints, enabling targeted penetration testing for authorization flaws like BOLA and authentication bypass vulnerabilities.
The OWASP API Security Top 10 (2023) defines critical API security risks, and automated vulnerability assessments map discovered flaws like BFLA and injection attacks directly to these categories for prioritized remediation.
Yes, comprehensive API security testing supports both REST and GraphQL architectures, applying tailored methodologies like OpenAPI spec parsing for REST and introspection-based discovery for GraphQL to identify distinct attack vectors.
To check for BOLA and business logic flaws, automated security assessments test authorization boundaries and execute logical abuse scenarios on API endpoints to detect unauthorized data access and privilege escalation vulnerabilities.
Automated API penetration testing efficiently identifies common vulnerabilities like injection and authorization flaws, but detecting complex business logic flaws often requires AI-guided analysis and manual validation to confirm true positive findings.
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