4. Security & Compliance

Manages Nix access tokens and secrets securely using sops-nix, automating configuration and providing safe editing wrappers.

Provides security best practices for Python development, including input validation, injection prevention, and threat modeling.

Securely retrieves secrets from 1Password vaults via CLI, ensuring no secret exposure in output or logs.

Generates SEO metadata and affiliate compliance assets including required disclosures, sitemaps, and robots.txt files for regulatory adherence.

Comprehensive standards for secure authentication implementation using Google OAuth 2.0 and NextAuth.js.

Programmatically handles Microsoft Office files with Azure Information Protection (AIP) sensitivity labels, including reading, writing, and detection of protected files across platforms.

Provides guidance on regulatory compliance and ethical frameworks for responsible AI development and deployment.

Enforces mandatory SEO and security checklists prior to confirming changes in sensitive files.

Provides comprehensive logging and audit trails for AI systems to ensure regulatory compliance and facilitate debugging.

Comprehensive guide for implementing hierarchical Role-Based Access Control (RBAC) with custom permissions in enterprise applications.

Enforces policies to detect, classify, and protect Personally Identifiable Information (PII) data within a data platform, ensuring regulatory compliance.

Manages secure storage, rotation, and access control for secrets, credentials, and sensitive configuration to prevent unauthorized access.

Compares actual code to specifications, identifies deviations, assesses impact, and generates compliance reports for tasks, phases, or entire specs.

Enforces security best practices for Convex functions, covering error handling, validation, authentication, access control, and rate limiting.

Provides a guide for implementing SCIM 2.0 to automate user provisioning and deprovisioning, ensuring secure identity management and compliance in enterprise applications.

Comprehensive guide for implementing audit trails, logging, and observability in AI agent systems to meet compliance standards and support debugging.

Provides a comprehensive web application audit methodology covering security (OWASP Top 10), accessibility (RGAA 4.1), performance, and eco-design with reference documentation.

Assesses and mitigates risks in AI systems, addressing bias, safety, privacy, security, and ethical compliance requirements.

Comprehensive guide for securing LLM applications through prompt injection prevention, jailbreak detection, guardrails, and red teaming methodologies.

Provides essential security controls including authentication, secrets management, and audit logging to establish baseline service security requirements.

Provides a guide for implementing secure permission systems in AI agent tools, covering RBAC, approval workflows, and security policies.

Provides a comprehensive guide for conducting access audits, periodic reviews, anomaly detection, and segregation of duties to ensure security and compliance.

Automates data retention, archival, and deletion policies to ensure compliance with regulatory requirements.

Ensures data privacy compliance and security for personal information throughout the machine learning lifecycle, from training to inference.