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Dynamic Programming / 1Dmedium45 minSecurity Engineer

Threat Ranking Budget Optimizer

Security Engineer signal: dynamic programming + knapsack in a threat intel graph context. This is a ProdMatch-owned security engineer drill, framed as a March 2026 Udaan Security Platform simulation, not a copied platform question.

Company context

Udaan · Security Platform

Freshness

March 2026

Product surface

threat intel graph

ProdMatch interview simulation based on product-team patterns; not a claim of a real company question.

Question

Your Security Platform roadmap has candidate improvements for threat intel graph. Each improvement has cost, lift and risk. Maximize lift under budget while keeping total risk below a threshold.

Input

  • Items [cost, lift, risk], budget and maxRisk.

Output

  • Maximum lift achievable.

Constraints

  • 1 <= items.length <= 500
  • Budget <= 10000
  • maxRisk <= 10000

Concepts

  • attack graphs
  • policy tries
  • anomaly detection
  • dynamic programming
  • knapsack
  • ranking trade-off

items [[2,5,1],[4,9,4]], budget=4, risk=4 -> 9

Approach

Try framing your own approach first. The 30 seconds you think before peeking is where learning happens.

Clean Solution

Reveal the approach first.

How well did you understand?

Your rating tunes when this problem shows up again.

Common Mistakes

  • Unclear state definition usually causes off-by-one bugs.
  • Do not overwrite a state before all consumers have used it.

Next Similar Problems

Attack Ranking Budget OptimizermediumPolicy Ranking Budget OptimizerhardAnomaly Ranking Budget Optimizerhard