Results for “data-quality”

Data quality audit on CRM with completeness scoring and specific fix recommendations

Audit and implement behavior-preserving cleanup across types, dead code, dependencies, errors, and comments

Enforces GDPR-compliant deployment practices for Google Cloud Run, including Frankfurt region verification, PII-safe logging, data anonymization, retention policies, and CSP configuration.

Scans a codebase for security vulnerabilities using CodeQL's interprocedural data flow and taint tracking analysis. Triggers on "run codeql", "codeql scan", "codeql analysis", "build codeql database", or "find vulnerabilities with codeql". Supports "run all" (security-and-quality suite) and "important only" (high-precision security findings) scan modes. Also handles creating data extension models and processing CodeQL SARIF output.

Application-level business logic security testing for any domain. Takes an understanding-first approach: map the intended workflows before probing them. Covers: value/quantity logic abuse (negative, zero, overflow, rounding on any numeric field), workflow and state machine bypass (skipping required steps, forcing illegal state transitions, reusing one-time tokens), trust boundary violations (BOLA horizontal/vertical, BFLA, cross-tenant access, negative ownership attacks), idempotency and replay attacks (duplicate submissions, double-spend, same-reference reuse), multi-step flow integrity (checkout, registration, approval, verification), quota and rate limit bypass, time/date manipulation, and authorization code / reference number predictability. Domain-agnostic — applies to SaaS, e-commerce, banking, gaming, social platforms, APIs, or any multi-user application with stateful workflows. Chains from /pentester; chains into /param-fuzz when boundary violations or mass assignment are confirmed.

Tracks indicators of compromise from initial discovery through validation, enrichment, deployment, monitoring, and retirement to maintain a high-quality, actionable indicator database.

Review PostgreSQL code for best practices, anti-patterns, and quality standards including JSONB, arrays, custom types, schema design, functions, and security features like Row Level Security.

Builds SOC performance metrics and KPI tracking dashboards measuring Mean Time to Detect (MTTD), Mean Time to Respond (MTTR), alert quality ratios, analyst productivity, and detection coverage using SIEM data.