Can this help with language-specific vulnerabilities?

Absolutely. It provides specific guidance for JavaScript/TypeScript, Python, and SQL to prevent exploits like prototype pollution, pickle RCE, and injection.

How does it help with AI Agent security?

It includes a dedicated framework for mitigating risks unique to AI, such as goal hijacking, tool misuse, and prompt injection in agentic systems.

Is it suitable for high-security applications?

Yes, it incorporates ASVS 5.0 levels 1 through 3, making it suitable for standard applications as well as critical systems requiring hardware-level security.

Does this skill cover the latest OWASP standards?

Yes, it includes guidelines for the OWASP Top 10:2025 and preliminary Agentic AI Security (OWASP 2026) standards.

OWASP Security Best Practices

Name: OWASP Security Best Practices
Author: nikhillinit

bynikhillinit

0•

Security & Testing

Integrates industry-standard OWASP security guidelines and defensive coding patterns directly into your development and review workflow.

This skill empowers Claude to act as a security-conscious engineer by applying the latest OWASP Top 10:2025 standards and ASVS requirements during code generation and review. It provides specialized checklists for input validation, authentication, and access control, alongside secure implementation patterns for common vulnerabilities like SQL injection and command execution. Beyond traditional web security, it includes cutting-edge guidance for Agentic AI security (OWASP 2026), ensuring that LLM-based applications are resilient against prompt injection and tool misuse. Whether you are building a simple API or a critical system handling sensitive data, this skill ensures your code follows a 'deny-by-default' philosophy and remains hardened against modern attack vectors.

Key Features

01Secure coding patterns for Python, JavaScript, TypeScript, and SQL

020 GitHub stars

03Automated security code reviews based on OWASP Top 10:2025 standards

04Multi-level ASVS 5.0 requirement mapping for sensitive applications

05Comprehensive Agentic AI security mitigations for LLM-driven systems

06Language-specific vulnerability detection for proto-pollution and RCE

Use Cases

01Implementing robust authentication and password hashing using Argon2/bcrypt

02Performing a deep security audit on a new feature before deployment

03Hardening AI agents against prompt injection and unauthorized tool usage

Key Features

01Secure coding patterns for Python, JavaScript, TypeScript, and SQL

020 GitHub stars

03Automated security code reviews based on OWASP Top 10:2025 standards

04Multi-level ASVS 5.0 requirement mapping for sensitive applications

05Comprehensive Agentic AI security mitigations for LLM-driven systems

06Language-specific vulnerability detection for proto-pollution and RCE

Use Cases

01Implementing robust authentication and password hashing using Argon2/bcrypt

02Performing a deep security audit on a new feature before deployment

03Hardening AI agents against prompt injection and unauthorized tool usage