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:
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.
#!/usr/bin/env python3import reimport sysfrom 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}