Security Governance, Risk & Privacy Topics
Governance, compliance frameworks, regulatory requirements, compliance implementation, and compliance-driven risk management. Covers compliance frameworks (SOX, GDPR, HIPAA, FCPA, etc.), regulatory interpretation, compliance control design, audit and control effectiveness evaluation, and compliance process management. For operational security implementation and technical threat mitigation, see Security Engineering & Operations.
Audit Readiness, Evidence and Inspection Management
Being audited or inspected: preparing for internal and external audits and regulatory inspections, assembling and presenting the evidence auditors request (artifact packs, configuration snapshots, access records, change-approval and segregation-of-duties records, lineage and reproducibility records, design-decision and requirement traceability, and documentation packages a reviewer can follow), scoping evidence collection under deadline pressure, sampling and sample populations an auditor can trust, showing a control operated across a whole audit period rather than on one day, maintaining continuous audit readiness and audit-trail integrity, coordinating fieldwork, responding to auditor and regulator requests, including audits of deployed models (training data provenance, fairness testing records, third-party components you cannot inspect), disclosing evidence gaps and retention limits honestly, and handling adverse findings, disputed severity ratings and compensating controls professionally. Audit logging is covered as an evidence-strategy question (what must be provable, tamper-evident and retained, including where retention conflicts with privacy), not as log-pipeline engineering. Control design and testing of effectiveness, compliance frameworks and certification standards, compliance automation tooling, and detection-focused log engineering are covered elsewhere.
Compliance Frameworks and Certification Standards
The major security compliance frameworks and certification standards and how to achieve and maintain them: SOC 2 (Type I and II, Trust Services Criteria), ISO/IEC 27001 and 27701, NIST CSF and SP 800-53, CIS Controls, PCI DSS (scoping, the cardholder data environment, segmentation and card-on-file architecture, staying compliant as software ships), and FedRAMP (baselines, authorization boundary and authorization paths). Covers what each framework governs, mandatory regulation versus voluntary standard (including regulated product standards versus a voluntary certification), prescriptive versus principles-based approaches, how control families map to organizational practices, choosing and sequencing frameworks and making the cost case, which framework mandates versus merely expects a practice such as penetration testing, reading vendor attestations, scoping and gap analysis including which gaps block certification, certification roadmaps, sustaining compliance after the first report, and harmonizing overlapping requirements across standards and laws into one traceable control set. Excludes designing and testing individual controls, building audit evidence packages, compliance tooling, and the detailed text of privacy laws, which are covered elsewhere.
Security and Privacy Culture, Training and Awareness
Building organization-wide security and privacy awareness and a culture where protective behavior is the norm. Covers awareness and role-based training programs, phishing simulations, embedding security and privacy ownership into engineering, product, and support teams, and measuring and improving culture. Focuses on the human layer of the program rather than technical controls.
Data Breach and Privacy Incident Response
Responding to privacy incidents and breaches: detection, containment, investigation, severity and breach classification, and regulator and individual notification within statutory deadlines. Covers complaint intake and resolution, escalation, and balancing transparency against risk during an incident. Includes coordinating the cross-functional response and post-incident remediation.
GDPR Principles and Compliance
The General Data Protection Regulation in depth: the six lawful bases, data subject rights, accountability and records obligations, DPO requirements, and enforcement and fines. Covers how GDPR principles translate into concrete engineering and product controls. Includes controller and processor obligations and demonstrating compliance.
Internal Controls Design and Effectiveness Testing
How to design controls and prove they work. Covers control objectives, preventive vs detective vs corrective vs compensating controls and what makes a compensating control legitimate, building and maintaining a control matrix that maps controls to risks, owners and requirements, control ownership and segregation of duties, the COSO internal control framework, entity-level vs process-level controls, the three lines of defence, design-effectiveness vs operating-effectiveness testing, choosing test methods, test cadence and re-tests, sampling and interpreting exceptions, control self-assessment, judging whether controls are improving or decaying over time, evaluating control deficiencies and their severity, reliance on IT general controls, retiring, consolidating or automating controls without losing coverage, control changes in a cloud migration, and corrective and preventive action when a control fails. Applies to security, IT and compliance controls, including the IT general controls that support financial reporting, at the level of the control discipline itself. Excludes finance-process controls (payables, reconciliations, month-end close), the technical mechanics of any one security tool or attack technique, the content of specific certification frameworks, audit logistics and evidence handling, and compliance tooling and automation.
Security Findings Management and Remediation Tracking
Managing the lifecycle of security and compliance findings from identification through closure. Covers triaging and prioritizing findings and large backlogs by business impact, assigning ownership, designing tracker states and remediation ticket workflows with SLAs, escalation and time-bound risk-accepted exceptions, tracking remediation to completion, verifying fixes and choosing a retest approach, ingesting, deduplicating and normalizing findings across scanners and manual tests, and turning post-incident and vendor-blocked issues into tracked, prioritized remediation plans. Also covers reporting on remediation status, aging and program metrics (and how those metrics get misread), building auditor-ready evidence and mapping findings to compliance controls, scripting and querying remediation data, and writing the findings report itself: structure for developer and executive audiences, reproducible evidence, remediation guidance and safe handling of exploit proof. Discovering vulnerabilities and scoring them are out of scope.
Compliance Automation and Tooling
Using technology to make compliance continuous rather than point-in-time. Covers GRC platforms and control libraries (build versus buy, one control set mapped to many regulations, requirement-to-evidence traceability, risk roll-ups), compliance-as-code and policy-as-code checks mapped to framework controls (including testing, versioning and retiring the rules, and turning local legal and privacy obligations such as retention and masking into machine-checkable tests), continuous control monitoring and drift alerts, automated evidence collection and tamper-evident evidence pipelines for auditors, automated compliance and privacy reporting with traceable lineage (including regulatory SLA tracking such as DSAR deadlines), and wiring compliance checks into engineering pipelines without slowing teams. Focuses on what to automate first, how to map controls to machine-checkable tests, where to place checks, and the limits of automation. Does not cover designing or testing the controls themselves, the content of individual frameworks, hands-on security mechanics such as secrets, IAM, scanning or logging pipelines, or conducting the audit.
Data Minimization and Retention
Collecting and keeping only what is necessary: data minimization at collection, purpose limitation, and retention scheduling with automated deletion. Covers defining retention periods, enforcing them technically, and defensibly disposing of data. Includes balancing operational or analytics needs against minimization obligations.