Merge pull request #106 from Philip-Zimmermann/feature/png_crc_db_lookup
CRC Database lookup for image_resize.py, fix #96
This commit is contained in:
Zeecka
@@ -24,7 +24,7 @@ def analyze_foremost(input_img: Path, output_dir: Path) -> None:
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timeout=MAX_PENDING_TIME,
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)
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# Note: foremost use stderr as standard output for results :o)
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# So we can't use it as error dectection :
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# So we can't use it as error detection :
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# stderr += data.stderr
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# Zip extracted files
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@@ -1,165 +1,118 @@
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"""Image size bruteforcer for common PNG sizes."""
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import zlib
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from pathlib import Path
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from .utils import update_data
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from typing import List
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# Full list of expected sizes
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EXPECTED_SIZES = [
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# -------------------------
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# ICONS (Square)
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# -------------------------
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(16, 16),
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(20, 20),
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(24, 24),
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(28, 28),
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(32, 32),
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(48, 48),
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(64, 64),
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(72, 72),
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(96, 96),
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(128, 128),
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(192, 192),
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(256, 256),
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(384, 384),
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(512, 512),
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(768, 768),
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(1024, 1024),
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(1536, 1536),
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(2048, 2048),
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(4096, 4096),
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# -------------------------
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# 1:1 Square (General)
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# -------------------------
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(300, 300),
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(500, 500),
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(800, 800),
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(1000, 1000),
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(1500, 1500),
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(2000, 2000),
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(2500, 2500),
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(3000, 3000),
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# -------------------------
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# 4:3 Aspect (Classic Screens)
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# -------------------------
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(320, 240),
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(640, 480),
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(800, 600),
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(960, 720),
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(1024, 768),
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(1280, 960),
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(1600, 1200),
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(2048, 1536),
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(2560, 1920),
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(3200, 2400),
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(4096, 3072),
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# -------------------------
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# 3:2 Aspect (Photography)
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# -------------------------
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(600, 400),
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(900, 600),
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(1200, 800),
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(1500, 1000),
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(1800, 1200),
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(2400, 1600),
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(3000, 2000),
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(3600, 2400),
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(4500, 3000),
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(6000, 4000),
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# -------------------------
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# 16:9 Aspect (Video / Web)
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# -------------------------
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(426, 240),
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(640, 360),
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(854, 480),
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(960, 540),
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(1280, 720),
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(1366, 768),
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(1600, 900),
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(1920, 1080),
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(2560, 1440),
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(3200, 1800),
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(3440, 1935),
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(3840, 2160),
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(5120, 2880),
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(7680, 4320),
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(10240, 5760),
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# -------------------------
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# 16:10 Aspect (Laptops)
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# -------------------------
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(1280, 800),
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(1440, 900),
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(1680, 1050),
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(1920, 1200),
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(2560, 1600),
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(2880, 1800),
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(3840, 2400),
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(5120, 3200),
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# -------------------------
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# Mobile Portrait (9:16)
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# -------------------------
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(720, 1280),
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(1080, 1920),
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(1440, 2560),
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(2160, 3840),
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(1440, 2960),
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(1080, 2400),
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(1170, 2532),
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(1284, 2778),
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(1290, 2796),
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# -------------------------
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# Social Media Sizes
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# -------------------------
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# Instagram
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(1080, 1080),
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(1080, 1350),
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(1080, 1920),
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# Facebook
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(1200, 628),
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(1200, 1200),
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# Twitter/X
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(1200, 675),
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(1500, 500),
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# YouTube Thumbnails
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(1280, 720),
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(1920, 1080),
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# -------------------------
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# Banners / Headers
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# -------------------------
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(1600, 500),
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(1920, 500),
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(2560, 700),
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(3000, 1000),
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(3840, 1200),
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# -------------------------
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# Print-like Digital Sizes
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# -------------------------
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(2550, 3300), # Letter @ 300 DPI
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(2480, 3508), # A4 @ 300 DPI
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(3508, 4961), # A3 @ 300 DPI
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(4961, 7016), # A2 @ 300 DPI
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(7016, 9933), # A1 @ 300 DPI
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]
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from ..app import app
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from ..models import IHDR
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from .utils import PNG, update_data
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def calc_checksum(
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header_chunk: bytearray, width_bytes: bytearray, height_bytes: bytearray
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) -> bytearray:
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def write_recovered_png(
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png_bytes: bytearray,
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width: int,
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height: int,
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output_path: Path,
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) -> None:
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"""
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Calculates the CRC32 of the IHDR chunk with new dimensions.
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header_chunk: The full IHDR chunk (Type + Data).
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Rebuilds a PNG by patching IHDR width/height and writes it to disk.
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"""
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# Reconstruct IHDR: [Type(4)] + [New Width(4)] + [New Height(4)] + [Rest of Data(5)]
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new_header = header_chunk[:4] + width_bytes + height_bytes + header_chunk[12:]
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height_bytes = height.to_bytes(4, byteorder="big")
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width_bytes = width.to_bytes(4, byteorder="big")
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# Calculate CRC and return as 4 bytes (Big Endian)
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return bytearray((zlib.crc32(new_header) & 0xFFFFFFFF).to_bytes(4, byteorder="big"))
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full_png_data = (
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png_bytes[:16] # Splicing: [Start...IHDR+4] + [W] + [H] + [IHDR+12...End]
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+ width_bytes
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+ height_bytes
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+ png_bytes[24:]
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)
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with output_path.open("wb") as out_f:
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out_f.write(full_png_data)
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def lookup_crc(png: PNG) -> List[PNG]:
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"""
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Look up PNG images in the database by their CRC value.
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Args:
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png (PNG): A PNG object containing the CRC value to search for.
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Returns:
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List[PNG]: A list of PNG objects with matching CRC values, reconstructed from their packed
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representations.
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"""
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with app.app_context():
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imgs = IHDR.query.filter_by(crc=png.crc).all()
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results = []
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for img in imgs:
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packed = img.packed
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results.append(PNG.from_packed(packed, crc=png.crc))
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return results
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def search_height_crc(png: PNG) -> List[PNG]:
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"""
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Search for PNG images with matching CRC by iterating through possible heights.
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This function attempts to find alternative PNG configurations that produce the same
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CRC checksum as the input PNG by systematically varying the height parameter while
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keeping all other properties constant.
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Args:
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png (PNG): The reference PNG object whose CRC checksum will be matched.
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Returns:
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List[PNG]: A list of PNG objects with matching CRC values. Returns an empty list
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if no matches are found.
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Note:
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The function iterates through heights from 100 to 3500 (inclusive).
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This may be computationally expensive for large ranges.
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"""
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results = []
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for height in range(100, 3501):
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candidate = PNG(
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width=png.width,
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height=height,
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bit_depth=png.bit_depth,
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color_type=png.color_type,
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interlace=png.interlace,
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)
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if candidate.crc == png.crc:
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results.append(candidate)
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return results
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def analyze_image_resize(input_img: Path, output_dir: Path) -> None:
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"""
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Analyze an image submission using python-based resize bruteforce.
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Attempts to recover PNGs with modified resolutions but valid CRCs.
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Analyze a PNG image and recover resized versions based on CRC matching.
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This function attempts to find matching image dimensions for a given PNG file
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by looking up its CRC (Cyclic Redundancy Check) in a database. If matches are
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found, it recovers and saves PNG images with the matched dimensions.
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Args:
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input_img (Path): Path to the input PNG image file to analyze.
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output_dir (Path): Path to the directory where recovered PNG images will be saved.
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Returns:
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None
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Raises:
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Handles exceptions gracefully by updating output data with error status.
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Side Effects:
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- Creates output directory if it doesn't exist.
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- Saves recovered PNG images to the output directory.
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- Updates data in the output directory with analysis results via update_data().
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Notes:
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- If the PNG has invalid structure or IHDR chunk is not first, an error is logged.
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- The function performs a two-step lookup: first by CRC, then by height/CRC if no matches
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found.
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- Recovered images are named as "recovered_{width}x{height}.png".
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- Analysis results (logs, status, and image URLs) are persisted via update_data().
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"""
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# 1. Setup Paths
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@@ -168,81 +121,61 @@ def analyze_image_resize(input_img: Path, output_dir: Path) -> None:
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# 3. Initialize Logs
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logs = []
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recovered_image = None
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try:
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with input_img.open("rb") as image:
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f = image.read()
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img_bytes = bytearray(image.read())
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png = PNG.from_bytearray(img_bytes)
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b = bytearray(f)
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# Find IHDR start
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ihdr = b.find(b"\x49\x48\x44\x52")
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if ihdr == -1:
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logs.append("Failure: PNG header (IHDR) not found.")
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if png is None:
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logs.append(
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"Failure: IHDR chunk is not the first chunk, or PNG has invalid structure."
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)
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update_data(
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output_dir,
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{"image_resize": {"status": "error", "error": "PNG header not found."}},
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{
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"image_resize": {
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"status": "error",
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"error": "IHDR chunk is not the first chunk, or PNG has invalid structure.",
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}
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},
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)
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return
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# Calculate Chunk Length (The 4 bytes BEFORE IHDR tag)
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chunk_length = int.from_bytes((b[ihdr - 4 : ihdr]), byteorder="big") + 4
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logs.append(f"Target CRC found: 0x{png.crc:08x}")
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# Extract Target CRC (The 4 bytes AFTER the chunk data)
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target_crc = b[ihdr + chunk_length : ihdr + chunk_length + 4]
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saved_img_urls = []
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# Isolate the header chunk (Type + Data)
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header_chunk = b[ihdr : ihdr + chunk_length]
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db_matches = lookup_crc(png)
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if not db_matches:
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db_matches = search_height_crc(png)
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if not db_matches:
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logs.append("Failure: No matching dimensions found.")
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else:
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# Create parent directories if they don't exist
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output_dir.mkdir(parents=True, exist_ok=True)
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logs.append(f"Target CRC found: 0x{target_crc.hex()}")
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match_found = False
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# Brute-force Loop
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for size in EXPECTED_SIZES:
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width, height = size
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# Convert dimensions to 4-byte Big Endian arrays
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width_bytes = bytearray(width.to_bytes(4, byteorder="big"))
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height_bytes = bytearray(height.to_bytes(4, byteorder="big"))
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# Check if this size matches the file's CRC
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if target_crc == calc_checksum(header_chunk, width_bytes, height_bytes):
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match_found = True
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logs.append(f"Success: Match found! Dimensions: {width}x{height}")
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# Create Output Filename
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img_name = f"recovered_{width}x{height}.png"
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# Create parent directories if they don't exist
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output_dir.mkdir(parents=True, exist_ok=True)
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# Iterate through ALL candidates found
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for im_match in db_matches:
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img_name = f"recovered_{im_match.width}x{im_match.height}.png"
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output_path = output_dir / img_name
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# Splicing: [Start...IHDR+4] + [W] + [H] + [IHDR+12...End]
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full_png_data = (
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b[: ihdr + 4] + width_bytes + height_bytes + b[ihdr + 12 :]
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write_recovered_png(
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img_bytes, im_match.width, im_match.height, output_path
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)
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# Write the recovered file to disk
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with output_path.open("wb") as out_f:
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out_f.write(full_png_data)
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recovered_image = Path(output_dir.name) / img_name
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break # Stop looking after finding the match
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if not match_found:
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logs.append("Failure: No matching dimensions found.")
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logs.append(f"Image saved: {img_name}")
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# Append the formatted URL to our list
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saved_img_urls.append("/image/" + str(Path(output_dir.name) / img_name))
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# 4. Final Data Update
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output_data = {
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"image_resize": { # Key name must match your module name in AperiSolve
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"image_resize": {
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"status": "ok",
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"output": logs,
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"png_images": saved_img_urls,
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}
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}
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if recovered_image:
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output_data["image_resize"]["image"] = "/image/" + str(recovered_image)
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update_data(output_dir, output_data)
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except Exception as e:
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@@ -11,7 +11,7 @@ from .utils import MAX_PENDING_TIME, update_data
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def analyze_outguess(
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input_img: Path, output_dir: Path, password: Optional[str] = None
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) -> None:
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"""Analyze an image submission using stehide."""
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"""Analyze an image submission using outguess."""
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image_name = input_img.name
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try:
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@@ -7,7 +7,7 @@ from .utils import MAX_PENDING_TIME, update_data
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def analyze_pngcheck(input_img: Path, output_dir: Path) -> None:
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"""Analyze an image submission using strings."""
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"""Analyze an image submission using pngcheck."""
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try:
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data = subprocess.run(
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@@ -24,15 +24,15 @@ def analyze_pngcheck(input_img: Path, output_dir: Path) -> None:
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# )
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# return
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data_strings = data.stdout.split("\n") if data else []
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data_strings = [s for s in data_strings if s]
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data_pngcheck = data.stdout.split("\n") if data else []
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data_pngcheck = [s for s in data_pngcheck if s]
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update_data(
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output_dir,
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{
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"pngcheck": {
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"status": "ok",
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"output": data_strings,
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"output": data_pngcheck,
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}
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},
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)
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@@ -12,7 +12,7 @@ from .utils import MAX_PENDING_TIME, update_data
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def analyze_steghide(
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input_img: Path, output_dir: Path, password: Optional[str] = None
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) -> None:
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"""Analyze an image submission using stehide."""
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"""Analyze an image submission using steghide."""
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image_name = input_img.name
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try:
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@@ -2,10 +2,14 @@
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import fcntl
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import json
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import math
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import os
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import struct
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import threading
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import zlib
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from functools import cached_property
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from pathlib import Path
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from typing import Any
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from typing import Any, Self
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_thread_lock = threading.Lock()
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@@ -46,3 +50,255 @@ def update_data(
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os.replace(tmp_file, json_file) # ensures file write is atomic
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finally:
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fcntl.flock(lock, fcntl.LOCK_UN)
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def get_resolutions():
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"""
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Generate a sorted list of common display and image resolutions.
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Creates a comprehensive set of resolution tuples by combining various base widths
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with standard aspect ratios used in screens, digital displays, photography, and
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paper standards. Includes both portrait and landscape orientations.
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Base widths range from 16px to 10000px, covering:
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- Low resolution: 16-256px (16px increments)
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- Standard: 320-1024px (32px increments)
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- HD/Full HD: 1280-2560px (64px increments)
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- 4K: 3000-4096px (128px increments)
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- 5K-8K: 5120-8192px (256px increments)
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- Upper bound: 10000px
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Aspect ratios include common formats:
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- Digital screens: 1:1, 4:3, 3:2, 16:10, 16:9, 21:9
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- Photography/print: 5:4, 7:5, 2:3
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- Paper standards: ISO A-series, US Letter, Legal, Tabloid
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Returns:
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list[tuple[int, int]]: Sorted list of (width, height) resolution tuples
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with heights constrained between 1 and 10000 pixels.
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"""
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base_widths = (
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list(range(16, 257, 16)) # 16 → 256
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+ list(range(320, 1025, 32)) # 320 → 1024
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||||
+ list(range(1280, 2561, 64)) # 1280 → 2560
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+ list(range(3000, 4097, 128)) # 3K–4K
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+ list(range(5120, 8193, 256)) # 5K–8K
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+ [10000] # upper bound
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||||
)
|
||||
aspect_ratios = [
|
||||
# Screens / digital
|
||||
(1, 1), # square
|
||||
(4, 3),
|
||||
(3, 2),
|
||||
(16, 10),
|
||||
(16, 9),
|
||||
(21, 9),
|
||||
# Photography / print
|
||||
(5, 4), # 8x10
|
||||
(7, 5), # 5x7
|
||||
(3, 2), # 4x6 (already included, kept for clarity)
|
||||
(2, 3), # poster
|
||||
# Paper standards
|
||||
(1414, 1000), # ISO A-series (A4, A3, A2, ...)
|
||||
(11, 85), # US Letter
|
||||
(14, 85), # Legal
|
||||
(17, 11), # Tabloid
|
||||
]
|
||||
resolutions = set()
|
||||
for w in base_widths:
|
||||
for ar_w, ar_h in aspect_ratios:
|
||||
h = math.floor(round(w * ar_h / ar_w))
|
||||
if 1 <= h <= 10000:
|
||||
resolutions.add((w, h))
|
||||
resolutions.add((h, w)) # portrait / landscape
|
||||
return sorted(resolutions)
|
||||
|
||||
|
||||
def get_valid_depth_color_pairs():
|
||||
"""
|
||||
Generate valid combinations of color and bit depth values.
|
||||
|
||||
Yields tuples of (depth, color) representing valid color mode and bit depth
|
||||
combinations. Supports grayscale (0), RGB (2, 3, 4, 6) color modes with
|
||||
appropriate bit depths (1, 2, 4, 8, 16 bits).
|
||||
|
||||
Yields:
|
||||
tuple: A tuple of (depth, color) where depth is an integer representing
|
||||
bit depth and color is an integer representing the color mode.
|
||||
"""
|
||||
valid_color_depth = {
|
||||
0: [1, 2, 4, 8, 16],
|
||||
2: [8, 16],
|
||||
3: [1, 2, 4, 8],
|
||||
4: [8, 16],
|
||||
6: [8, 16],
|
||||
}
|
||||
for color, depths in valid_color_depth.items():
|
||||
for depth in depths:
|
||||
yield depth, color
|
||||
|
||||
|
||||
class PNG:
|
||||
"""
|
||||
A class representing a PNG image header (IHDR chunk).
|
||||
This class encapsulates the metadata from a PNG file's IHDR (Image Header) chunk,
|
||||
including image dimensions, bit depth, color type, interlacing method, and CRC checksum.
|
||||
It provides methods for parsing PNG files, packing/unpacking header data, and generating
|
||||
PNG crc if omitted.
|
||||
"""
|
||||
|
||||
width: int
|
||||
height: int
|
||||
bit_depth: int
|
||||
color_type: int
|
||||
crc: int
|
||||
interlace: int = 0
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
width: int,
|
||||
height: int,
|
||||
bit_depth: int,
|
||||
color_type: int,
|
||||
crc: int | None = None,
|
||||
interlace: int = 0,
|
||||
):
|
||||
"""Initialize a PNG IHDR (Image Header) chunk.
|
||||
|
||||
Args:
|
||||
width (int): The width of the image in pixels.
|
||||
height (int): The height of the image in pixels.
|
||||
bit_depth (int): The number of bits per sample or per palette index (1, 2, 4, 8, or 16).
|
||||
color_type (int): The color type of the image (0=Grayscale, 2=RGB, 3=Indexed,
|
||||
4=Grayscale+Alpha, 6=RGBA).
|
||||
crc (int | None, optional): CRC (Cyclic Redundancy Check) checksum for the chunk.
|
||||
If None, it will be calculated automatically. Defaults
|
||||
to None.
|
||||
interlace (int, optional): The interlace method (0=no interlace, 1=Adam7 interlace).
|
||||
Defaults to 0.
|
||||
"""
|
||||
self.width = width
|
||||
self.height = height
|
||||
self.bit_depth = bit_depth
|
||||
self.color_type = color_type
|
||||
self.crc = (
|
||||
crc
|
||||
or zlib.crc32(
|
||||
b"IHDR"
|
||||
+ width.to_bytes(4, "big")
|
||||
+ height.to_bytes(4, "big")
|
||||
+ bytes((bit_depth, color_type, 0, 0, interlace))
|
||||
)
|
||||
& 0xFFFFFFFF
|
||||
)
|
||||
self.interlace = interlace
|
||||
|
||||
@classmethod
|
||||
def from_packed(cls, packed: int, crc: int | None = None) -> Self:
|
||||
"""Create a PNG instance from a packed integer representation.
|
||||
|
||||
Parse a packed integer containing width, height, bit depth, color type and interlace
|
||||
bits and return a PNG instance. The CRC may be supplied; if omitted it will be
|
||||
computed by the constructor.
|
||||
|
||||
Args:
|
||||
packed (int): Packed integer with fields laid out as described in the `packed` property.
|
||||
crc (int | None): Optional CRC value for the IHDR chunk.
|
||||
|
||||
Returns:
|
||||
Self: PNG instance with parsed fields.
|
||||
"""
|
||||
interlace = packed & 0b1
|
||||
color = (packed >> 1) & 0b111
|
||||
depth = (packed >> 4) & 0b111
|
||||
height = (packed >> 7) & 0xFFFF
|
||||
width = (packed >> 23) & 0xFFFF
|
||||
return cls(
|
||||
width=width,
|
||||
height=height,
|
||||
bit_depth=depth,
|
||||
color_type=color,
|
||||
crc=crc,
|
||||
interlace=interlace,
|
||||
)
|
||||
|
||||
@cached_property
|
||||
def packed(self) -> int:
|
||||
"""Pack IHDR fields into a single integer.
|
||||
|
||||
Returns:
|
||||
int: Packed integer encoding the IHDR fields.
|
||||
|
||||
Layout:
|
||||
width : 16 bits
|
||||
height : 16 bits
|
||||
depth : 3 bits
|
||||
color : 3 bits
|
||||
interlace : 1 bit
|
||||
"""
|
||||
return (
|
||||
((self.width & 0xFFFF) << 23)
|
||||
| ((self.height & 0xFFFF) << 7)
|
||||
| ((self.bit_depth & 0b111) << 4)
|
||||
| ((self.color_type & 0b111) << 1)
|
||||
| (self.interlace & 0b1)
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def from_bytearray(cls, data: bytearray) -> Self:
|
||||
"""Create a PNG image instance from a bytearray containing PNG file data.
|
||||
|
||||
Parses the PNG signature and IHDR (Image Header) chunk to extract image metadata
|
||||
including dimensions, bit depth, color type, and interlacing information.
|
||||
|
||||
Args:
|
||||
data (bytearray): A bytearray containing the complete PNG file data, starting
|
||||
with the PNG signature (8 bytes: \\x89PNG\\r\\n\\x1a\\n).
|
||||
|
||||
Returns:
|
||||
Self | None: A new instance of the PNG image class with parsed IHDR metadata
|
||||
(width, height, bit_depth, color_type, crc, interlace) if the data is
|
||||
valid and contains a proper IHDR chunk. Returns None if the PNG signature
|
||||
is invalid or the IHDR chunk type is not found.
|
||||
|
||||
Raises:
|
||||
struct.error: If the data is too short or malformed for unpacking IHDR fields.
|
||||
IndexError: If the bytearray is shorter than expected for the PNG structure.
|
||||
"""
|
||||
|
||||
png_signature = b"\x89PNG\r\n\x1a\n"
|
||||
if data[:8] != png_signature:
|
||||
raise ValueError("Invalid PNG signature")
|
||||
offset = 8 # Read IHDR chunk
|
||||
length = struct.unpack(">I", data[offset : offset + 4])[0]
|
||||
offset += 4
|
||||
chunk_type = data[offset : offset + 4]
|
||||
offset += 4
|
||||
if chunk_type != b"IHDR":
|
||||
raise ValueError("IHDR chunk not found at expected position")
|
||||
|
||||
ihdr_data = data[offset : offset + length]
|
||||
offset += length
|
||||
|
||||
crc = struct.unpack(">I", data[offset : offset + 4])[0]
|
||||
|
||||
# Unpack IHDR fields
|
||||
width, height, depth, color, _, _, interlace = struct.unpack(
|
||||
">IIBBBBB", ihdr_data
|
||||
)
|
||||
|
||||
return cls(
|
||||
width=width,
|
||||
height=height,
|
||||
bit_depth=depth,
|
||||
color_type=color,
|
||||
crc=crc,
|
||||
interlace=interlace,
|
||||
)
|
||||
|
||||
def __repr__(self) -> str:
|
||||
return (
|
||||
f"PNG(width={self.width}, height={self.height}, "
|
||||
f"bit_depth={self.bit_depth}, color_type={self.color_type}, "
|
||||
f"interlace={self.interlace}, crc=0x{self.crc:08x})"
|
||||
)
|
||||
|
||||
+7
-7
@@ -1,4 +1,4 @@
|
||||
"""AperiSolve Flask application."""
|
||||
"""Aperi'Solve Flask application."""
|
||||
|
||||
import hashlib
|
||||
import json
|
||||
@@ -41,7 +41,7 @@ def too_large(_: Any) -> tuple[Response, int]:
|
||||
@app.errorhandler(404)
|
||||
def not_found(_: Any) -> str:
|
||||
"""Error Handler for 404 not found."""
|
||||
return render_template("error.html", message="Ressource not found", statuscode=404)
|
||||
return render_template("error.html", message="Resource not found", statuscode=404)
|
||||
|
||||
|
||||
@app.route("/")
|
||||
@@ -134,12 +134,12 @@ def upload_image() -> tuple[Response, int]:
|
||||
first_submission_date=datetime.now(timezone.utc),
|
||||
last_submission_date=datetime.now(timezone.utc),
|
||||
)
|
||||
db.session.add(new_img)
|
||||
db.session.commit()
|
||||
db.session.add(new_img) # pylint: disable=no-member
|
||||
db.session.commit() # pylint: disable=no-member
|
||||
|
||||
sub_img = Image.query.filter_by(hash=img_hash).first() # type: ignore
|
||||
sub_img.upload_count += 1
|
||||
db.session.commit()
|
||||
db.session.commit() # pylint: disable=no-member
|
||||
|
||||
# Create new Submission entry
|
||||
submission_path.mkdir(parents=True, exist_ok=True)
|
||||
@@ -152,9 +152,9 @@ def upload_image() -> tuple[Response, int]:
|
||||
date=time.time(),
|
||||
image_hash=sub_img.hash, # type: ignore
|
||||
)
|
||||
db.session.add(submission)
|
||||
db.session.add(submission) # pylint: disable=no-member
|
||||
|
||||
db.session.commit() # Commit to save the new Image and Submission
|
||||
db.session.commit() # pylint: disable=no-member
|
||||
# Start the analysis jobs
|
||||
queue.enqueue("aperisolve.workers.analyze_image", submission.hash, job_timeout=300)
|
||||
|
||||
|
||||
+28
-7
@@ -14,7 +14,28 @@ MAX_STORE_TIME = int(getenv("MAX_STORE_TIME", "259200")) # 3 days by default
|
||||
|
||||
|
||||
def cleanup_old_entries() -> None:
|
||||
"""Clean up old entries in the database and file system."""
|
||||
"""
|
||||
Clean up old and incomplete entries from the database and file system.
|
||||
|
||||
This function performs two main cleanup operations:
|
||||
|
||||
1. Submission cleanup:
|
||||
- Deletes submissions with "pending" or "running" status that have exceeded
|
||||
the maximum allowed processing time (MAX_PENDING_TIME).
|
||||
- Deletes completed submissions ("done" status) that have missing or buggy
|
||||
results (results.json file not found).
|
||||
|
||||
2. Image cleanup:
|
||||
- Deletes images older than MAX_STORE_TIME along with all associated
|
||||
submissions and their result folders.
|
||||
- Deletes orphaned images (with no submissions) older than MAX_PENDING_TIME
|
||||
and removes their associated result folders from the file system.
|
||||
|
||||
All database changes are committed at the end of the operation.
|
||||
|
||||
Returns:
|
||||
None
|
||||
"""
|
||||
now = time.time()
|
||||
for submission in Submission.query.all(): # type: ignore
|
||||
if (
|
||||
@@ -22,7 +43,7 @@ def cleanup_old_entries() -> None:
|
||||
and now - submission.date > MAX_PENDING_TIME # type: ignore
|
||||
):
|
||||
# Processing took too long, delete
|
||||
db.session.delete(submission) # type: ignore
|
||||
db.session.delete(submission) # pylint: disable=no-member
|
||||
elif submission.status == "done": # type: ignore
|
||||
# Search for buggy results, delete
|
||||
result_path = (
|
||||
@@ -30,7 +51,7 @@ def cleanup_old_entries() -> None:
|
||||
)
|
||||
result_file = result_path / "results.json"
|
||||
if not result_file.exists():
|
||||
db.session.delete(submission) # type: ignore
|
||||
db.session.delete(submission) # pylint: disable=no-member
|
||||
shutil.rmtree(result_path)
|
||||
|
||||
# Delete "old" images
|
||||
@@ -43,15 +64,15 @@ def cleanup_old_entries() -> None:
|
||||
img_fold = RESULT_FOLDER / img.hash
|
||||
if delay.total_seconds() > MAX_STORE_TIME:
|
||||
for s in img.submissions:
|
||||
db.session.delete(s) # type: ignore
|
||||
db.session.delete(s) # pylint: disable=no-member
|
||||
if img_fold.exists():
|
||||
shutil.rmtree(img_fold) # type: ignore
|
||||
db.session.delete(img)
|
||||
db.session.delete(img) # pylint: disable=no-member
|
||||
|
||||
# Delete Images with missing submission
|
||||
if len(img.submissions) == 0 and delay.total_seconds() > MAX_PENDING_TIME:
|
||||
if img_fold.exists():
|
||||
shutil.rmtree(img_fold) # type: ignore
|
||||
db.session.delete(img)
|
||||
db.session.delete(img) # pylint: disable=no-member
|
||||
|
||||
db.session.commit()
|
||||
db.session.commit() # pylint: disable=no-member
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
"""AperiSolve configuration variables."""
|
||||
"""Aperi'Solve configuration variables."""
|
||||
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
+93
-17
@@ -1,11 +1,13 @@
|
||||
"""This module defines the database models for the Aperisolve application."""
|
||||
"""This module defines the database models for the Aperi'Solve application."""
|
||||
|
||||
import itertools
|
||||
from datetime import datetime, timezone
|
||||
from decimal import Decimal
|
||||
|
||||
from flask import Flask
|
||||
from flask_sqlalchemy import SQLAlchemy
|
||||
from sqlalchemy import Boolean, Column, DateTime, Float, Integer, String
|
||||
from sqlalchemy import BigInteger, Boolean, Column, DateTime, Float, Integer, String
|
||||
|
||||
from aperisolve.analyzers.utils import PNG, get_resolutions, get_valid_depth_color_pairs
|
||||
|
||||
db: SQLAlchemy = SQLAlchemy()
|
||||
|
||||
@@ -13,21 +15,21 @@ db: SQLAlchemy = SQLAlchemy()
|
||||
class Image(db.Model): # type: ignore
|
||||
"""Model representing an image file in the database."""
|
||||
|
||||
hash: Column[str] = Column(
|
||||
hash: Column[String] = Column(
|
||||
String(64), primary_key=True, unique=True, nullable=False
|
||||
)
|
||||
file: Column[str] = Column(String(128), unique=True, nullable=False)
|
||||
size: Column[int] = Column(Integer, nullable=False)
|
||||
first_submission_date: Column[datetime] = Column(
|
||||
file: Column[String] = Column(String(128), unique=True, nullable=False)
|
||||
size: Column[Integer] = Column(Integer, nullable=False)
|
||||
first_submission_date: Column[DateTime] = Column(
|
||||
DateTime, nullable=False, default=lambda: datetime.now(timezone.utc)
|
||||
)
|
||||
last_submission_date: Column[datetime] = Column(
|
||||
last_submission_date: Column[DateTime] = Column(
|
||||
DateTime,
|
||||
nullable=False,
|
||||
default=lambda: datetime.now(timezone.utc),
|
||||
onupdate=lambda: datetime.now(timezone.utc),
|
||||
)
|
||||
upload_count: Column[int] = Column(Integer)
|
||||
upload_count: Column[Integer] = Column(Integer)
|
||||
submissions = db.relationship("Submission", backref="image", lazy=True)
|
||||
|
||||
|
||||
@@ -37,14 +39,14 @@ class Submission(db.Model): # type: ignore
|
||||
option.
|
||||
"""
|
||||
|
||||
hash: Column[str] = Column(
|
||||
hash: Column[String] = Column(
|
||||
String(128), primary_key=True, unique=True, nullable=False
|
||||
)
|
||||
filename: Column[str] = Column(String(128), nullable=False)
|
||||
password: Column[str] = Column(String(128))
|
||||
deep_analysis: Column[bool] = Column(Boolean, default=False)
|
||||
status: Column[str] = Column(String(20), default="pending")
|
||||
date: Column[Decimal] = Column(
|
||||
filename: Column[String] = Column(String(128), nullable=False)
|
||||
password: Column[String] = Column(String(128))
|
||||
deep_analysis: Column[Boolean] = Column(Boolean, default=False)
|
||||
status: Column[String] = Column(String(20), default="pending")
|
||||
date: Column[Float] = Column(
|
||||
Float, nullable=False, default=lambda: datetime.now(timezone.utc)
|
||||
)
|
||||
|
||||
@@ -52,10 +54,84 @@ class Submission(db.Model): # type: ignore
|
||||
image_hash = Column(String, db.ForeignKey("image.hash"), nullable=False)
|
||||
|
||||
|
||||
class IHDR(db.Model): # type: ignore
|
||||
"""IHDR CRC lookup table"""
|
||||
|
||||
iid: Column[Integer] = Column(Integer, primary_key=True, autoincrement=True)
|
||||
crc: Column[BigInteger] = Column(BigInteger, nullable=False)
|
||||
packed: Column[BigInteger] = Column(BigInteger, nullable=False)
|
||||
|
||||
|
||||
def create_crc_db() -> None:
|
||||
"""
|
||||
Creates a database of common PNG IHDR (Image Header) entries by generating
|
||||
combinations of standard PNG parameters such as resolutions, bit depths,
|
||||
color types, and interlace methods. The function checks for existing entries
|
||||
in the database to avoid duplicates and inserts new entries in batches of
|
||||
5000, committing the changes to the database periodically.
|
||||
|
||||
Returns:
|
||||
None
|
||||
"""
|
||||
# Standard PNG IHDR parameters
|
||||
resolutions = get_resolutions()
|
||||
bit_color_pairs = get_valid_depth_color_pairs()
|
||||
interlace_methods = [0, 1]
|
||||
|
||||
combinations = itertools.product(
|
||||
resolutions,
|
||||
bit_color_pairs,
|
||||
interlace_methods,
|
||||
)
|
||||
|
||||
count = 0
|
||||
|
||||
with db.session.no_autoflush: # pylint: disable=no-member
|
||||
for (w, h), (bd, ct), inter in combinations:
|
||||
p = PNG(width=w, height=h, bit_depth=bd, color_type=ct, interlace=inter)
|
||||
|
||||
exists = db.session.execute( # pylint: disable=no-member
|
||||
db.select(IHDR.iid).where(IHDR.packed == p.packed)
|
||||
).first()
|
||||
|
||||
if exists: # Skip if already present
|
||||
continue
|
||||
|
||||
db.session.add(IHDR(packed=p.packed, crc=p.crc)) # pylint: disable=no-member
|
||||
count += 1
|
||||
|
||||
if count % 5000 == 0:
|
||||
print(f"Inserted {count} common IHDR entries...")
|
||||
db.session.commit()
|
||||
|
||||
db.session.commit() # pylint: disable=no-member
|
||||
print(f"Precomputed {count} common IHDR entries.")
|
||||
|
||||
|
||||
def init_db(app: Flask) -> None:
|
||||
"""Initialize the database with the given Flask app."""
|
||||
"""
|
||||
Initialize the database by creating tables and populating lookup data.
|
||||
|
||||
This function creates the database schema if it doesn't already exist,
|
||||
and populates the CRC lookup table for PNG IHDR validation.
|
||||
|
||||
Args:
|
||||
app (Flask): The Flask application instance used to establish the application context
|
||||
for database operations.
|
||||
|
||||
Returns:
|
||||
None
|
||||
|
||||
Side Effects:
|
||||
- Creates all database tables if the "image" table doesn't exist
|
||||
- Populates the IHDR CRC lookup table with initial data
|
||||
- Prints status messages to console during initialization
|
||||
"""
|
||||
with app.app_context():
|
||||
if not db.engine.dialect.has_table(db.engine.connect(), "image"):
|
||||
print("Creating database...")
|
||||
db.create_all()
|
||||
print("Database created successfully.")
|
||||
print("Database structure created successfully.")
|
||||
print("Filling IHDR lookup table...")
|
||||
create_crc_db()
|
||||
print("IHDR table filled successfully.")
|
||||
|
||||
@@ -279,6 +279,12 @@ function parseResult(result) {
|
||||
)}'/></div>`;
|
||||
}
|
||||
|
||||
if ("png_images" in result[tool]) {
|
||||
for (const image of result[tool]["png_images"]) {
|
||||
analyzer.innerHTML += `<div class='results_img'><img src='${escapeHtml(image)}'/></div>`;
|
||||
}
|
||||
}
|
||||
|
||||
// Parse text output
|
||||
|
||||
|
||||
|
||||
+29
-5
@@ -8,19 +8,43 @@ from .analyzers.binwalk import analyze_binwalk
|
||||
from .analyzers.decomposer import analyze_decomposer
|
||||
from .analyzers.exiftool import analyze_exiftool
|
||||
from .analyzers.foremost import analyze_foremost
|
||||
from .analyzers.image_resize import analyze_image_resize
|
||||
from .analyzers.outguess import analyze_outguess
|
||||
from .analyzers.pngcheck import analyze_pngcheck
|
||||
from .analyzers.steghide import analyze_steghide
|
||||
from .analyzers.strings import analyze_strings
|
||||
from .analyzers.zsteg import analyze_zsteg
|
||||
from .analyzers.pngcheck import analyze_pngcheck
|
||||
from .analyzers.image_resize import analyze_image_resize
|
||||
from .app import app, db
|
||||
from .config import RESULT_FOLDER
|
||||
from .models import Image, Submission
|
||||
|
||||
|
||||
def analyze_image(submission_hash: str) -> None:
|
||||
"""Analyze an image submission in separate threads."""
|
||||
"""
|
||||
Analyze an image submission by running multiple analysis tools concurrently.
|
||||
|
||||
This function retrieves a submission and its associated image from the database,
|
||||
then executes various image analysis tools in parallel threads. The analysis tools
|
||||
include binwalk, decomposer, exiftool, foremost, strings, pngcheck, steghide,
|
||||
zsteg, and image resize. If deep analysis is enabled, additional tools like
|
||||
outguess are included.
|
||||
|
||||
Args:
|
||||
submission_hash (str): The unique hash identifier of the submission to analyze.
|
||||
|
||||
Returns:
|
||||
None
|
||||
|
||||
Raises:
|
||||
Implicitly catches and handles exceptions during analysis, setting submission
|
||||
status to "error" if an exception occurs.
|
||||
|
||||
Side Effects:
|
||||
- Queries the database for the submission and associated image
|
||||
- Updates submission status in the database ("running" -> "completed" or "error")
|
||||
- Creates result directories and generates analysis output files
|
||||
- Modifies the database session and commits changes
|
||||
"""
|
||||
with app.app_context():
|
||||
submission: Submission = Submission.query.get(submission_hash) # type: ignore
|
||||
image = Image.query.get_or_404(submission.image_hash) # type: ignore
|
||||
@@ -29,7 +53,7 @@ def analyze_image(submission_hash: str) -> None:
|
||||
return
|
||||
|
||||
submission.status = "running" # type: ignore
|
||||
db.session.commit()
|
||||
db.session.commit() # pylint: disable=no-member
|
||||
|
||||
try:
|
||||
img_path: Path = Path(image.file)
|
||||
@@ -77,4 +101,4 @@ def analyze_image(submission_hash: str) -> None:
|
||||
except Exception:
|
||||
submission.status = "error"
|
||||
finally:
|
||||
db.session.commit()
|
||||
db.session.commit() # pylint: disable=no-member
|
||||
|
||||
Reference in New Issue
Block a user