Validate delivery changes for LGPD, injection, and hardcoded secrets.
npx skills add https://github.com/joleques/northstar-ai --skill security-revisor
Please help me install this Agent Skill. Skill: security-revisor Source: https://github.com/joleques/northstar-ai/tree/main/.codex/skills/security-revisor Command: npx skills add https://github.com/joleques/northstar-ai --skill security-revisor
Prevent insecure or non-compliant code deliveries by detecting LGPD/data privacy issues, input validation gaps, injection risks, and hardcoded secrets before release. The skill enforces a gate that blocks delivery when critical or high-severity findings are present and produces a clear remediation path for the development team.
Run the security-revisor on the change by providing the demand type (bug or implementation), list of modified files, executed tests and results, and any new environment variables.
High-intent search queries and answers about installing and using this skill.
To check for hardcoded secrets and LGPD compliance issues before delivery, run a pre-release security review on modified files, test results, and environment variables. This validates input, detects sensitive data exposure, and generates a structured PASS/FAIL status with mandatory remediation actions.
A pre-delivery security review is a checklist-driven gate that validates input handling and detects injection vulnerabilities in code changes. It produces evidence-backed findings with severity classifications and blocks delivery when critical or high-severity security risks are present.
You block a code release when high-severity vulnerabilities are found by applying structured gating during your pre-delivery review. The process returns a FAIL status, halting delivery until the development team executes the required corrective actions for the identified risks.
To review data protection and security risks, you need to provide the change type, a list of modified files, executed tests and results, and any new environment variables. This minimal context allows the review to pinpoint LGPD gaps and hardcoded credentials accurately.
Yes, automated security review works for both bug fixes and new feature implementations. You apply it as a final pre-release check by providing the demand type alongside modified files and test results to ensure no unsafe query construction or sensitive data leakage is introduced.
cursorReview Git diffs, run targeted tests, and open PRs.
tbeackOrchestrate security review findings into diffs, regression tests, and PRs.
nanorepublicaStandardize unit-test coding practices across Claude Code projects.
stephanjConducts security audits and vulnerability assessments on codebases and infrastructure.
