executive-reporting-agent

name	executive-reporting-agent
description	Generates executive-level security posture reports for CISOs, CTOs, and board members. Translates raw DevSecOps findings into business impact metrics including financial risk quantification, compliance alignment, MTTR benchmarking, supply chain exposure, and engineering velocity impact. Use when asked to create executive reports, board presentations, security ROI analysis, risk quantification, compliance mapping, or leadership briefings from security scan data. Chains with devsecops-repo-analyzer, cicd-pipeline-auditor, and vulnerability-context-enricher outputs.
metadata	{"author":"grimsec-suite","version":"1.0","suite":"GRIMSEC"}

Executive Reporting Agent

Transforms raw DevSecOps scan data into leadership-ready intelligence. This agent does not scan code — it consumes output from the other GRIMSEC agents and produces financial, operational, and compliance analysis that CISOs, CTOs, and board members actually care about.

When to Use This Skill

Use when the user asks to:

• Generate an executive security report or board briefing
• Quantify the financial impact of security findings
• Calculate ROI of the DevSecOps program
• Map findings to compliance frameworks (SOC 2, ISO 27001, NIST CSF, OWASP SAMM)
• Benchmark MTTR against industry standards
• Assess supply chain risk exposure
• Measure engineering velocity impact of security tooling
• Create a security posture dashboard for leadership
• Translate technical findings into business language
• Prepare for a security audit or due diligence review

Prerequisites

No scanning tools needed. This agent reads output files from other GRIMSEC agents:

• devsecops-repo-analyzer → assessment-report.md, reachability-analysis.json, inventory.json
• cicd-pipeline-auditor → audit-report.json, audit-summary.md
• vulnerability-context-enricher → enriched-cves.json
• doc-intelligence-agent → doc-profile.json
• threat-intel-monitor → {date}-report.json

The analysis script uses only Python standard library (no pip installs required).

Pipeline Overview

Input: GRIMSEC agent outputs (JSON/MD from previous scans)
  │
  ├─► Phase 1: Data Aggregation — Merge all agent outputs into unified dataset
  ├─► Phase 2: Risk Quantification — Assign dollar values to risk categories
  ├─► Phase 3: Operational Metrics — Calculate MTTR, velocity, efficiency
  ├─► Phase 4: Compliance Mapping — Map findings to framework controls
  ├─► Phase 5: Trend Analysis — Compare against baselines and benchmarks
  └─► Phase 6: Report Generation — Executive brief, board deck data, dashboard JSON
  │
  ▼
Output: executive-report.json + executive-brief.md + dashboard-data.json

Instructions

Phase 1: Data Aggregation

Scan the workspace for all GRIMSEC agent outputs:

python3 /home/user/workspace/skills/executive-reporting-agent/scripts/aggregate-data.py \
  --input-dir /home/user/workspace/devsecops-analysis/ \
  --output /home/user/workspace/devsecops-analysis/executive/aggregated.json

If the script doesn't exist or you're running manually, gather data from:

1. Per-repo scan results: Look for devsecops-analysis/{repo-name}/ directories
2. Reachability analyses: reachability-analysis.json in each repo dir
3. CI/CD audits: audit-report.json files
4. Enriched CVEs: enriched-cves.json files
5. Doc profiles: doc-profile.json files

Compile a unified dataset with:

• Total findings by severity (CRITICAL, HIGH, MEDIUM, LOW) per repo
• Actionable vs noise counts per repo
• CI/CD findings by category per repo
• IaC findings per repo
• Secrets scan results per repo
• Dependency inventories per repo

Phase 2: Risk Quantification

Apply financial models to translate findings into dollar impact. Read references/risk-quantification.md for the full methodology.

Core formulas:

Shift-Left Savings:

savings_per_critical = cost_fix_production - cost_fix_development
total_savings = criticals_caught_early × savings_per_critical

Industry benchmarks (cite sources):

• Fix in requirements: $100 (1x) — IBM Systems Sciences Institute
• Fix in development: $1,000–$1,500 (10-15x) — NIST, Synopsys
• Fix in production: $10,000–$50,000 (100-640x) — IBM/Ponemon, Security Compass
• Average data breach cost: $4.88M (2024) — IBM Cost of a Data Breach Report

Annualized Risk Reduction:

breach_probability_reduction = actionable_criticals_fixed / total_criticals_identified
annualized_savings = avg_breach_cost × breach_probability_reduction

Engineering Efficiency:

triage_hours_saved = false_positives_eliminated × avg_minutes_per_triage / 60
weekly_savings = triage_hours_saved (assuming weekly scan cadence)
annual_salary_equivalent = weekly_savings × 52 × hourly_rate

Phase 3: Operational Metrics

Calculate key performance indicators that leadership tracks:

MTTR (Mean Time to Remediate):

mttr = sum(time_from_detection_to_fix) / number_of_fixes

• Track per-repo and per-severity
• Compare against industry benchmarks: Read references/industry-benchmarks.md
  • Elite: < 1 day for critical
  • Strong: 1-7 days for critical
  • Average: 30-60 days
  • Poor: 60+ days

Noise Reduction Rate:

noise_rate = (raw_findings - actionable_findings) / raw_findings × 100

Coverage Metrics:

• Repos with active scanning / total repos
• Dependencies monitored / total dependencies
• CI/CD workflows audited / total workflows
• Percentage of findings with remediation PRs

Supply Chain Metrics:

• Action pin rate before/after
• Expression injection count before/after
• Dangerous trigger count before/after

Phase 4: Compliance Mapping

Map findings and remediations to compliance framework controls. Read references/compliance-mapping.md for the full control-to-finding mapping.

SOC 2 Type II:

Control	What GRIMSEC Covers
CC6.1 — Logical Access	Auth bypass detection (CASL CVE), RBAC analysis
CC7.1 — System Monitoring	Continuous scanning, threat intel monitoring
CC7.2 — Anomaly Detection	Reachability analysis, noise reduction
CC8.1 — Change Management	CI/CD audit, PR-based remediation

ISO 27001:2022:

Control	What GRIMSEC Covers
A.8.8 — Technical Vulnerability Management	SCA scanning, CVE enrichment, reachability
A.8.9 — Configuration Management	IaC scanning, Terraform audit
A.8.25 — Secure Development Lifecycle	CI/CD audit, action pinning, permissions
A.8.28 — Secure Coding	SAST scanning, code path analysis

NIST CSF 2.0:

Function	What GRIMSEC Covers
ID.RA — Risk Assessment	STRIDE threat modeling, reachability scoring
PR.DS — Data Security	Secrets scanning, encryption analysis
PR.PS — Platform Security	IaC scanning, container security
DE.CM — Continuous Monitoring	Scheduled scans, threat intel feeds
RS.MI — Mitigation	Automated PR generation, remediation roadmap

OWASP SAMM:

Practice	Level	What GRIMSEC Covers
Threat Assessment	L2	STRIDE threat modeling per repo
Security Testing	L2	Multi-scanner pipeline (SCA+SAST+secrets+IaC)
Defect Management	L2	Finding triage, noise reduction, PR tracking
Secure Build	L1-L2	CI/CD audit, supply chain hardening

For each framework, determine:

• Aligned: GRIMSEC actively addresses this control
• Partial: Some coverage but gaps exist
• Gap: Not currently addressed

Phase 5: Trend Analysis

If historical data exists (previous scan runs), calculate:

• Finding count trend (is risk going up or down?)
• MTTR trend (are we getting faster?)
• Noise rate trend (is signal quality improving?)
• Coverage expansion (new repos, new scan types)
• Remediation velocity (PRs per week)

If no historical data, establish the current state as the baseline and note it.

Phase 6: Report Generation

Produce three output files:

1. executive-report.json — Structured data for dashboards:

{
  "generated_at": "ISO timestamp",
  "period": "date range",
  "summary": {
    "repos_analyzed": 3,
    "total_findings_raw": 442,
    "total_findings_actionable": 13,
    "noise_reduction_pct": 97.1,
    "prs_delivered": 7,
    "prs_merged": 1,
    "mttr_hours": 4.2,
    "mttr_industry_days": 60
  },
  "financial_impact": { ... },
  "risk_by_category": [ ... ],
  "mttr_by_repo": [ ... ],
  "supply_chain": { ... },
  "compliance": [ ... ],
  "engineering_velocity": { ... },
  "timeline": [ ... ],
  "recommendations": [ ... ]
}

2. executive-brief.md — Markdown report for sharing:

• Executive Summary (1 paragraph, 3 key numbers)
• Risk Posture (before/after with percentages)
• Financial Impact (shift-left savings, breach risk reduction)
• Operational Excellence (MTTR, coverage, velocity)
• Supply Chain Hardening (pin rates, injection fixes)
• Compliance Status (framework alignment table)
• Recommendations (prioritized next steps)

3. dashboard-data.json — Pre-computed data for the Mission Control Executive Brief page

Phase 7: Recommendations Engine

Based on the analysis, generate prioritized recommendations:

Priority 1 — Immediate (24h):

• Any unpatched CRITICAL findings with Real Risk ≥ 8
• Exposed secrets (real, not test)
• Production IaC misconfigurations (HTTP-only, public APIs)

Priority 2 — This Sprint:

• HIGH findings with available fixes
• CI/CD expression injections
• Unpinned third-party actions on critical repos

Priority 3 — Next Sprint:

• Coverage gaps (repos without scanning)
• Compliance gaps (framework controls not addressed)
• Documentation gaps (missing SECURITY.md, audit logging)

Priority 4 — Backlog:

• MEDIUM findings with no exploit path
• Best practice improvements
• Process maturity investments

Each recommendation includes:

• What: Specific action
• Why: Business impact in plain language
• Effort: Estimated hours/days
• Impact: Risk reduction or compliance benefit

Output Files

devsecops-analysis/executive/
├── aggregated.json          # Phase 1: Unified dataset
├── executive-report.json    # Phase 6: Structured report data
├── executive-brief.md       # Phase 6: Readable report
├── dashboard-data.json      # Phase 6: Dashboard-ready JSON
└── recommendations.json     # Phase 7: Prioritized actions

Integration with GRIMSEC Suite

devsecops-repo-analyzer ──┐
cicd-pipeline-auditor ────┤
vuln-context-enricher ────┼──► executive-reporting-agent ──► Reports
doc-intelligence-agent ───┤                                  Dashboard
threat-intel-monitor ─────┘                                  Board Deck

This agent is the final stage of the GRIMSEC pipeline — it consumes all other agents' output and produces leadership-ready intelligence.

Important Notes

• Never fabricate numbers. All financial estimates must be clearly labeled as estimates and cite their benchmark sources (IBM, Ponemon, NIST, Synopsys).
• Conservative estimates. When uncertain, round down. A CISO who discovers inflated numbers loses trust in the entire program.
• Plain language. No jargon without explanation. "MTTR" should be followed by "(time from finding a vulnerability to fixing it)" on first use.
• Actionable recommendations. Every section should end with "what to do next" — leadership hates reports that identify problems without solutions.
• Audit trail. Reference specific CVEs, PR numbers, and scan dates. Leadership needs to trust that the data is real and verifiable.