opsec

A digital exposure audit inventories your personal identifiers, evaluates exposure risk, and guides remediation to reduce identity leakage. This framework structures the process into phases covering inventory, scoring, chain mapping, and remediation planning across quarterly audits.

An identity chain map links your digital identifiers to trace how public data connects your profiles and accounts. Mapping these chains exposes vulnerability paths, enabling targeted privacy remediation to break linkages and minimize personal data leakage.

Risk scoring evaluates the exposure of your cataloged identifiers by assessing their visibility and linkage across public data. This framework applies structured gate checks to score risk, producing actionable remediation documents to secure your digital footprint.

Yes, this framework includes Python scripts for state management and gate checks. The scripts enforce production-grade workflow constraints, maintaining an interactive state model across your OPSEC self-assessment phases to ensure structured remediation progression.

Yes, PyYAML is required. The framework depends on PyYAML to handle configuration and manage OPSEC self-assessment artifacts, including inventory documents, exposure scoring, chain maps, remediation plans, and quarterly audit records.

Perform quarterly OPSEC audits when your digital footprint changes frequently, such as publishing public repos or creating new profiles. Periodic audits track identifier drift over time, ensuring exposure scoring and remediation plans remain accurate against new public data.