Software testing 2023-03-08
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Aptori

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AI-Driven Application & API Security Testing
Generated by ChatGPT

Aptori is a developer-first, AI-Driven Application and API Security Testing tool. It uses Artificial Intelligence for business logic testing to make the testing process significantly more effective.

Aptori uses semantic reasoning technology to generate a semantic model of an application's API. It then autonomously generates and executes API tests, aiming to uncover any business logic flaws in the application to help prevent security vulnerabilities.

Aptori's unique offering ensures continuous risk assessment, performance testing, and ultimately releases with higher confidence. It integrates its security testing into every phase of the Software Development Life Cycle (SDLC), ensuring a secure development workflow.

The tool is capable of discovering defects in applications before they make it to production. It can reduce the labor-intense task of manually creating and maintaining testing code by using its AI engine to emulate user interactions and devise API test scenarios.

Additionally, Aptori actively monitors the security posture of an application across all stages of the SDLC. Through continuous API risk assessment, it ensures that applications and APIs always remain secure and compliant.

Aptori uses a semantic graph to analyze an application's APIs behaviour with a goal to uncover business logic defects to prevent application vulnerabilities.

All of these functionalities contribute to reducing operational costs and mitigating security risks associated with the applications and APIs.

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Aptori was manually vetted by our editorial team and was first featured on December 24th 2023.
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8 alternatives to Aptori for Software testing

Pros and Cons

Pros

Developer-first approach
Business logic testing
Semantic reasoning technology
Continuous risk assessment
Performance testing
SDLC integration
Defect discovery
Reduces manual testing labor
API test scenario creation
Security posture monitoring
Continuous API risk assessment
Semantic graph for API analysis
Operational cost reduction
Security risk mitigation
Emulates user interactions
Application's APIs behaviour analysis
Semantic model generation
Autonomous testing
Uncover business logic flaws
Continuous testing
Actionable vulnerability results
Stateful graphing of APIs
Secure, high-quality software development
Eliminates manual test creation
Eliminates human error in testing
Enhances software quality
Accelerates development cycle
Comprehensive code coverage
Pinpoints vulnerabilities accurately
Streamlines testing process
Developer-first security
Security integrated into code-writing
Cultivates culture of shared security responsibility
Capable of predicting potential vulnerabilities
Effective API sequence testing
Shift-left security testing
Automated penetration testing
Comprehensive API testing without live traffic

Cons

No threat modeling
No interactive application security testing
Misses syntactic defects
Optimized strictly for API testing
Cannot simulate human error
Lack of personalized testing
Inefficient for small scale applications
Dependency on semantic integrity
No support for mobile applications
Difficult to emulate all user interactions

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