2023 Cyber Apocalypse: The Chasm Crossing Conundrum

Challenge Information

Summary

This challenge presents a classic bridge-crossing puzzle where multiple people need to cross a bridge with a flashlight. The flashlight has limited charge, and only two people can cross at a time. The solution requires finding the optimal sequence of crossings to minimize total time.

Analysis

The Problem:

• N people need to cross a bridge
• Only 2 people can cross at a time (with flashlight)
• Someone must bring the flashlight back
• Each person has a crossing time
• Total time is limited by flashlight charge

Strategy: The optimal algorithm for this problem:

1. Two fastest people cross
2. Fastest returns with flashlight
3. Two slowest people cross
4. Second fastest returns
5. Repeat until everyone crosses

This approach minimizes the time spent by slow people on the bridge.

Solution

def cross_bridge(person_times, flashlight_time):
    sorted_times = sorted(enumerate(person_times, start=1), key=lambda x: x[1])
    steps = []
    total_time = 0

    while len(sorted_times) > 2:
        # Two fastest cross
        p1, t1 = sorted_times[0]
        p2, t2 = sorted_times[1]
        steps.append([p1, p2])
        total_time += t2  # Time is determined by slower of the two

        # Fastest returns
        steps.append([p1])
        total_time += t1

        # Two slowest cross
        p3, t3 = sorted_times.pop()
        p4, t4 = sorted_times.pop()
        steps.append([p3, p4])
        total_time += t3  # Time is determined by slower of the two

        # Second fastest returns
        if len(sorted_times) > 1:
            steps.append([p2])
            total_time += t2

    # Last two people cross
    if len(sorted_times) == 2:
        p1, t1 = sorted_times[0]
        p2, t2 = sorted_times[1]
        steps.append([p1, p2])
        total_time += t2

    if total_time > flashlight_time:
        return []  # No solution

    return steps, total_time

Server interaction:

1. Connect to server and receive problem parameters
2. Parse crossing times for each person
3. Parse flashlight charge limit
4. Execute algorithm to find crossing sequence
5. Format and submit solution
6. Receive flag upon success

Key Takeaways

• Algorithmic optimization is crucial for many CTF challenges
• Classic puzzle problems require understanding of algorithm design
• Greedy algorithms don’t always provide optimal solutions
• Timing constraints require careful analysis
• Dynamic problem solving skills are essential
• Many CTF challenges test algorithmic thinking alongside hacking