Firewall Rule Complexity Analyzer
ANA›Life Services Authority›National Calculator Authority›Firewall Rule Complexity Analyzer
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Firewall Rule Complexity Analyzer
Quantifies firewall rule-set complexity using a weighted scoring model based on rule count, average conditions per rule, overlap/redundancy percentage, negation usage, and port-range breadth. Outputs a Complexity Score (0–100) and a risk tier.
Total Number of Rules
Average Conditions per Rule (source IP, dest IP, port, protocol, etc.)
Estimated Rule Overlap / Redundancy (%)
Percentage of Rules Using Negation / Exceptions (%)
Average Port-Range Breadth per Rule (1 = single port, 65535 = any)
Analyze Complexity
Results will appear here.
function firCalc() { // --- collect inputs --- const ruleCount = parseFloat(document.getElementById('fir_rule_count').value); const avgCond = parseFloat(document.getElementById('fir_avg_conditions').value); const overlapPct = parseFloat(document.getElementById('fir_overlap_pct').value); const negationPct = parseFloat(document.getElementById('fir_negation_pct').value); const portBreadth = parseFloat(document.getElementById('fir_port_breadth').value);
const resultDiv = document.getElementById('fir_result');
// --- validation --- if (isNaN(ruleCount) || isNaN(avgCond) || isNaN(overlapPct) || isNaN(negationPct) || isNaN(portBreadth)) { resultDiv.innerHTML = '⚠ Please fill in all fields.'; return; } if (ruleCount 10000) { resultDiv.innerHTML = '⚠ Rule count must be between 1 and 10,000.'; return; } if (avgCond 20) { resultDiv.innerHTML = '⚠ Average conditions must be between 1 and 20.'; return; } if (overlapPct 100 || negationPct 100) { resultDiv.innerHTML = '⚠ Percentage values must be between 0 and 100.'; return; } if (portBreadth 65535) { resultDiv.innerHTML = '⚠ Port-range breadth must be between 1 and 65,535.'; return; }
// --------------------------------------------------------------- // FORMULA // // Five sub-scores, each normalised to [0, 1], then weighted: // // S_rules = log10(ruleCount) / log10(10000) [weight 0.30] // S_cond = (avgCond - 1) / 19 [weight 0.25] // S_overlap = overlapPct / 100 [weight 0.20] // S_negation = negationPct / 100 [weight 0.15] // S_port = log10(portBreadth) / log10(65535) [weight 0.10] // // RawScore = 0.30S_rules + 0.25S_cond + 0.20S_overlap // + 0.15S_negation + 0.10*S_port // // ComplexityScore = RawScore * 100 (clamped 0–100) // ---------------------------------------------------------------
const W_RULES = 0.30; const W_COND = 0.25; const W_OVERLAP = 0.20; const W_NEGATION = 0.15; const W_PORT = 0.10;
const S_rules = Math.log10(ruleCount) / Math.log10(10000); const S_cond = (avgCond - 1) / 19; const S_overlap = overlapPct / 100; const S_negation = negationPct / 100; const S_port = Math.log10(portBreadth) / Math.log10(65535);
const rawScore = W_RULES * S_rules + W_COND * S_cond + W_OVERLAP * S_overlap + W_NEGATION * S_negation + W_PORT * S_port;
const complexityScore = Math.min(100, Math.max(0, rawScore * 100));
// --- effective (non-redundant) rules --- const effectiveRules = Math.round(ruleCount * (1 - overlapPct / 100));
// --- risk tier --- let tier, tierColor, tierAdvice; if (complexityScore Complexity Score
${complexityScore.toFixed(1)} / 100
Risk Tier ${tier} Effective (Non-Redundant) Rules ${effectiveRules.toLocaleString()} Complexity Index (Effective Rules × Avg Conditions) ${complexityIndex.toLocaleString()} Rule Sub-Score (S_rules) ${(S_rules * 100).toFixed(1)}% Condition Sub-Score (S_cond) ${(S_cond * 100).toFixed(1)}% Overlap Sub-Score (S_overlap) ${(S_overlap * 100).toFixed(1)}% Negation Sub-Score (S_negation) ${(S_negation * 100).toFixed(1)}% Port-Breadth Sub-Score (S_port) ${(S_port * 100).toFixed(1)}%
Recommendation: ${tierAdvice}
`; }
#### Formula
Five normalised sub-scores are computed and combined with empirical weights:
- S_rules = log₁₀(ruleCount) / log₁₀(10 000) — weight 0.30
- S_cond = (avgConditions − 1) / 19 — weight 0.25
- S_overlap = overlapPct / 100 — weight 0.20
- S_negation = negationPct / 100 — weight 0.15
- S_port = log₁₀(portBreadth) / log₁₀(65 535) — weight 0.10
ComplexityScore = (0.30·S_rules + 0.25·S_cond + 0.20·S_overlap + 0.15·S_negation + 0.10·S_port) × 100
Logarithmic scaling for rule count and port breadth reflects diminishing marginal complexity growth. Weights reflect industry consensus on the relative impact of each factor on policy manageability.
Effective Rules = ruleCount × (1 − overlapPct / 100)
Complexity Index = Effective Rules × avgConditions
Risk Tiers: Low (<25) | Moderate (25–49) | High (50–74) | Critical (≥75)
#### Assumptions & References
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