UMassCTF 2026 - Ninja-Nerds

where are your little ninja-nerds?

Initial Analysis

The supplied artifact is challenge.png. The recorded extraction is b1,b,lsb,xy: blue-channel least significant bits, row-major traversal. The original PNG is not retained, so its dimensions and preliminary file-inspection claims are not independently verified.

Solution

To extract the hidden data, we can either use automated tools or a custom script to parse the LSBs from each color plane.

1. Automated Approach

Using zsteg, we can quickly scan for common LSB patterns:

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zsteg -E "b1,b,lsb,xy" challenge.png | strings | grep "UMASS{"

2. Manual Extraction Script

Alternatively, using the Pillow library in Python allows for precise extraction from specific color channels.

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#!/usr/bin/env python3
import re
import sys
from PIL import Image

def extract_lsb(image_path):
# 统一 RGB;按 xy 行优先扫描,每字节的第一个 LSB 作为最高位
with Image.open(image_path) as source:
img = source.convert("RGB")
width, height = img.size
pixels = img.load()
found = False
for plane in range(3):
output = bytearray()
current_byte = 0
bit_count = 0
for y in range(height):
for x in range(width):
current_byte = (current_byte << 1) | (pixels[x, y][plane] & 1)
bit_count += 1
if bit_count == 8:
output.append(current_byte)
current_byte = 0
bit_count = 0
for match in re.finditer(rb"UMASS\{[\x20-\x7e]*\}", bytes(output)):
print(f"Plane {plane}: {match.group().decode('ascii')}")
found = True
if not found:
raise ValueError("No complete UMASS flag in the tested three bit planes")

if __name__ == "__main__":
if len(sys.argv) != 2:
raise SystemExit("Usage: python extract.py IMAGE")
extract_lsb(sys.argv[1])

Run python extract.py challenge.png. The blue-channel placement is the recorded hypothesis. A synthetic RGB fixture verifies row order, MSB-first byte packing and complete-string output, but challenge.png is unavailable, so the challenge extraction and agreement with zsteg have not been reproduced.

Flag

UMASS{perfectly-hidden-ready-to-strike}