Pre-consolidation snapshot: backends, steganalysis, platform presets, and WIP changes

Snapshot of all uncommitted work before merging stegasoo into soosef monorepo.
Includes: pluggable backends registry, steganalysis detection, platform presets,
and various in-progress modifications across core modules.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Aaron D. Lee
2026-04-01 18:56:36 -04:00
parent 14fce4d3ed
commit 70b941d55a
15 changed files with 1241 additions and 171 deletions

View File

@@ -46,6 +46,16 @@ from .image_utils import (
get_image_info,
)
# Backend registry
from .backends import EmbeddingBackend, registry as backend_registry
# Platform presets
from .platform_presets import PLATFORMS, get_preset
# Steganalysis
from .steganalysis import check_image
from .backends.registry import BackendNotFoundError
# Steganography functions
from .steganography import (
calculate_capacity_by_mode,
@@ -273,6 +283,15 @@ __all__ = [
"generate_filename",
# Crypto
"has_argon2",
# Backends
"EmbeddingBackend",
"backend_registry",
"BackendNotFoundError",
# Platform presets
"get_preset",
"PLATFORMS",
# Steganalysis
"check_image",
# Steganography
"has_dct_support",
"calculate_capacity_by_mode",

View File

@@ -0,0 +1,31 @@
"""
Stegasoo embedding backends.
Provides a typed plugin interface for all embedding algorithms.
Backends register with the module-level ``registry`` on import.
Usage::
from stegasoo.backends import registry
backend = registry.get("lsb")
stego, stats = backend.embed(data, carrier, key)
"""
from .dct import DCTBackend
from .lsb import LSBBackend
from .protocol import EmbeddingBackend
from .registry import BackendNotFoundError, BackendRegistry, registry
# Auto-register built-in backends
registry.register(LSBBackend())
registry.register(DCTBackend())
__all__ = [
"EmbeddingBackend",
"BackendRegistry",
"BackendNotFoundError",
"registry",
"LSBBackend",
"DCTBackend",
]

View File

@@ -0,0 +1,69 @@
"""
DCT (Discrete Cosine Transform) image embedding backend.
Wraps the existing frequency-domain DCT functions in dct_steganography.py.
"""
from __future__ import annotations
from typing import Any
class DCTBackend:
"""Frequency-domain DCT embedding for JPEG-resilient steganography."""
@property
def mode(self) -> str:
return "dct"
@property
def carrier_type(self) -> str:
return "image"
def is_available(self) -> bool:
from ..dct_steganography import HAS_SCIPY
return HAS_SCIPY
def embed(
self,
data: bytes,
carrier: bytes,
key: bytes,
*,
progress_file: str | None = None,
**options: Any,
) -> tuple[bytes, Any]:
from ..dct_steganography import embed_in_dct
output_format = options.get("dct_output_format", "png")
color_mode = options.get("dct_color_mode", "color")
quant_step = options.get("quant_step")
jpeg_quality = options.get("jpeg_quality")
max_dimension = options.get("max_dimension")
return embed_in_dct(
data, carrier, key, output_format, color_mode, progress_file,
quant_step=quant_step, jpeg_quality=jpeg_quality, max_dimension=max_dimension,
)
def extract(
self,
carrier: bytes,
key: bytes,
*,
progress_file: str | None = None,
**options: Any,
) -> bytes | None:
from ..dct_steganography import extract_from_dct
quant_step = options.get("quant_step")
try:
return extract_from_dct(carrier, key, progress_file, quant_step=quant_step)
except Exception:
return None
def calculate_capacity(self, carrier: bytes, **options: Any) -> int:
from ..dct_steganography import calculate_dct_capacity
info = calculate_dct_capacity(carrier)
return info.usable_capacity_bytes

View File

@@ -0,0 +1,63 @@
"""
LSB (Least Significant Bit) image embedding backend.
Wraps the existing spatial-domain LSB functions in steganography.py.
"""
from __future__ import annotations
from typing import Any
class LSBBackend:
"""Spatial-domain LSB embedding for lossless image formats."""
@property
def mode(self) -> str:
return "lsb"
@property
def carrier_type(self) -> str:
return "image"
def is_available(self) -> bool:
return True # Only needs Pillow, which is always present
def embed(
self,
data: bytes,
carrier: bytes,
key: bytes,
*,
progress_file: str | None = None,
**options: Any,
) -> tuple[bytes, Any]:
from ..steganography import _embed_lsb
bits_per_channel = options.get("bits_per_channel", 1)
output_format = options.get("output_format", None)
stego_bytes, stats, ext = _embed_lsb(
data, carrier, key, bits_per_channel, output_format, progress_file
)
# Attach output extension to stats for callers that need it
stats.output_extension = ext # type: ignore[attr-defined]
return stego_bytes, stats
def extract(
self,
carrier: bytes,
key: bytes,
*,
progress_file: str | None = None,
**options: Any,
) -> bytes | None:
from ..steganography import _extract_lsb
bits_per_channel = options.get("bits_per_channel", 1)
return _extract_lsb(carrier, key, bits_per_channel)
def calculate_capacity(self, carrier: bytes, **options: Any) -> int:
from ..steganography import calculate_capacity
bits_per_channel = options.get("bits_per_channel", 1)
return calculate_capacity(carrier, bits_per_channel)

View File

@@ -0,0 +1,91 @@
"""
Embedding backend protocol definition.
All embedding backends (LSB, DCT, audio, video, etc.) implement this protocol,
enabling registry-based dispatch instead of if/elif chains.
"""
from __future__ import annotations
from typing import Any, Protocol, runtime_checkable
@runtime_checkable
class EmbeddingBackend(Protocol):
"""Protocol that all embedding backends must satisfy.
Each backend handles a specific embedding mode (e.g. 'lsb', 'dct',
'audio_lsb', 'audio_spread') for a specific carrier type ('image',
'audio', 'video').
"""
@property
def mode(self) -> str:
"""The embedding mode identifier (e.g. 'lsb', 'dct')."""
...
@property
def carrier_type(self) -> str:
"""The carrier media type: 'image', 'audio', or 'video'."""
...
def is_available(self) -> bool:
"""Whether this backend's dependencies are installed."""
...
def embed(
self,
data: bytes,
carrier: bytes,
key: bytes,
*,
progress_file: str | None = None,
**options: Any,
) -> tuple[bytes, Any]:
"""Embed data into a carrier.
Args:
data: Encrypted payload bytes.
carrier: Raw carrier file bytes (image, audio, etc.).
key: Derived key for pixel/sample selection.
progress_file: Optional progress file path.
**options: Backend-specific options (bits_per_channel,
output_format, color_mode, chip_tier, etc.).
Returns:
Tuple of (stego carrier bytes, embed stats).
"""
...
def extract(
self,
carrier: bytes,
key: bytes,
*,
progress_file: str | None = None,
**options: Any,
) -> bytes | None:
"""Extract data from a carrier.
Args:
carrier: Stego carrier file bytes.
key: Derived key for pixel/sample selection.
progress_file: Optional progress file path.
**options: Backend-specific options.
Returns:
Extracted payload bytes, or None if no payload found.
"""
...
def calculate_capacity(self, carrier: bytes, **options: Any) -> int:
"""Calculate maximum embeddable payload size in bytes.
Args:
carrier: Raw carrier file bytes.
**options: Backend-specific options (e.g. bits_per_channel).
Returns:
Maximum payload capacity in bytes.
"""
...

View File

@@ -0,0 +1,63 @@
"""
Backend registry for embedding mode dispatch.
Backends register themselves by mode string. The registry replaces
if/elif dispatch in steganography.py with a lookup table.
"""
from __future__ import annotations
from ..exceptions import StegasooError
from .protocol import EmbeddingBackend
class BackendNotFoundError(StegasooError):
"""Raised when a requested backend mode is not registered."""
class BackendRegistry:
"""Registry mapping mode strings to embedding backends."""
def __init__(self) -> None:
self._backends: dict[str, EmbeddingBackend] = {}
def register(self, backend: EmbeddingBackend) -> None:
"""Register a backend for its mode string."""
self._backends[backend.mode] = backend
def get(self, mode: str) -> EmbeddingBackend:
"""Look up a backend by mode. Raises BackendNotFoundError if not found."""
if mode not in self._backends:
available = ", ".join(sorted(self._backends.keys())) or "(none)"
raise BackendNotFoundError(
f"No backend registered for mode '{mode}'. Available: {available}"
)
return self._backends[mode]
def has(self, mode: str) -> bool:
"""Check if a backend is registered for the given mode."""
return mode in self._backends
def available_modes(self, carrier_type: str | None = None) -> list[str]:
"""List registered mode strings, optionally filtered by carrier type.
Only includes modes whose backend reports is_available() == True.
"""
return sorted(
mode
for mode, backend in self._backends.items()
if backend.is_available()
and (carrier_type is None or backend.carrier_type == carrier_type)
)
def all_modes(self, carrier_type: str | None = None) -> list[str]:
"""List all registered mode strings (including unavailable ones)."""
return sorted(
mode
for mode, backend in self._backends.items()
if carrier_type is None or backend.carrier_type == carrier_type
)
# Module-level singleton
registry = BackendRegistry()

View File

@@ -184,8 +184,14 @@ def cli(ctx, json_output, debug_mode):
)
@click.option("--pin", prompt=True, hide_input=True, confirmation_prompt=True, help="PIN code")
@click.option("--dry-run", is_flag=True, help="Show capacity usage without encoding")
@click.option(
"--platform",
type=click.Choice(["telegram", "discord", "signal", "whatsapp"], case_sensitive=False),
help="DCT preset for social media platform (implies DCT+JPEG mode)",
)
@click.option("--verify/--no-verify", default=True, help="Pre-verify payload survives platform recompression")
@click.pass_context
def encode(ctx, carrier, reference, message, file_payload, output, passphrase, pin, dry_run):
def encode(ctx, carrier, reference, message, file_payload, output, passphrase, pin, dry_run, platform, verify):
"""
Encode a message or file into an image.
@@ -260,29 +266,48 @@ def encode(ctx, carrier, reference, message, file_payload, output, passphrase, p
from .steganography import EMBED_MODE_DCT, EMBED_MODE_LSB
# Platform preset overrides
preset = None
if platform:
from .platform_presets import get_preset
preset = get_preset(platform)
use_dct = True # Platform mode implies DCT+JPEG
if output_ext not in (".jpg", ".jpeg"):
output = str(Path(output).with_suffix(".jpg"))
click.echo(f" Platform mode: output changed to {output}")
try:
encode_kwargs = {
"reference_photo": reference_data,
"carrier_image": carrier_data,
"passphrase": passphrase,
"pin": pin,
"embed_mode": EMBED_MODE_DCT if use_dct else EMBED_MODE_LSB,
"dct_output_format": "jpeg" if use_dct else "png",
}
if preset:
encode_kwargs["platform"] = platform
if file_payload:
# Encode file
result = stegasoo_encode_file(
filepath=file_payload,
reference_photo=reference_data,
carrier_image=carrier_data,
passphrase=passphrase,
pin=pin,
embed_mode=EMBED_MODE_DCT if use_dct else EMBED_MODE_LSB,
dct_output_format="jpeg" if use_dct else "png",
)
result = stegasoo_encode_file(filepath=file_payload, **encode_kwargs)
else:
# Encode message
result = stegasoo_encode(
message=message,
reference_photo=reference_data,
carrier_image=carrier_data,
passphrase=passphrase,
pin=pin,
embed_mode=EMBED_MODE_DCT if use_dct else EMBED_MODE_LSB,
dct_output_format="jpeg" if use_dct else "png",
)
result = stegasoo_encode(message=message, **encode_kwargs)
# Pre-verify survival if platform mode
if preset and verify:
from .crypto import derive_pixel_key
from .platform_presets import pre_verify_survival
pixel_key = derive_pixel_key(reference_data, passphrase, pin)
survived = pre_verify_survival(result.stego_image, pixel_key, preset)
if not survived:
click.echo(
f" ⚠ Warning: Payload may not survive {preset.name} recompression. "
"Try a larger carrier image or shorter message.",
err=True,
)
# Write output
with open(output, "wb") as f:
@@ -325,8 +350,13 @@ def encode(ctx, carrier, reference, message, file_payload, output, passphrase, p
@click.option("--passphrase", prompt=True, hide_input=True, help="Passphrase")
@click.option("--pin", prompt=True, hide_input=True, help="PIN code")
@click.option("-o", "--output", type=click.Path(), help="Output path for file payloads")
@click.option(
"--platform",
type=click.Choice(["telegram", "discord", "signal", "whatsapp"], case_sensitive=False),
help="Platform preset (must match encoding platform)",
)
@click.pass_context
def decode(ctx, image, reference, passphrase, pin, output):
def decode(ctx, image, reference, passphrase, pin, output, platform):
"""
Decode a message or file from an image.
@@ -334,7 +364,7 @@ def decode(ctx, image, reference, passphrase, pin, output):
stegasoo decode encoded.png -r ref.jpg --passphrase --pin
stegasoo decode encoded.png -r ref.jpg -o ./extracted/
stegasoo decode encoded.png -r ref.jpg --platform telegram
"""
from .decode import decode as stegasoo_decode
@@ -344,12 +374,21 @@ def decode(ctx, image, reference, passphrase, pin, output):
with open(reference, "rb") as f:
reference_data = f.read()
# Resolve platform preset for DCT decoding
decode_kwargs = {}
if platform:
from .platform_presets import get_preset
preset = get_preset(platform)
decode_kwargs["platform"] = platform
try:
result = stegasoo_decode(
stego_image=stego_data,
reference_photo=reference_data,
passphrase=passphrase,
pin=pin,
**decode_kwargs,
)
if result.is_file:
@@ -1550,9 +1589,9 @@ def info(ctx, full):
# Check for DCT support
try:
from .dct_steganography import HAS_JPEGIO, HAS_SCIPY
from .dct_steganography import HAS_JPEGLIB, HAS_SCIPY
has_dct = HAS_SCIPY and HAS_JPEGIO
has_dct = HAS_SCIPY and HAS_JPEGLIB
except ImportError:
has_dct = False
@@ -2402,6 +2441,66 @@ def tools_convert(image, fmt, quality, output):
click.echo(f"Converted to: {output}")
# =============================================================================
# STEGANALYSIS COMMANDS
# =============================================================================
@cli.command()
@click.argument("image", type=click.Path(exists=True))
@click.option("--json", "as_json", is_flag=True, help="Output as JSON")
@click.option(
"--mode",
type=click.Choice(["lsb", "auto"]),
default="lsb",
help="Analysis mode (default: lsb)",
)
def check(image, as_json, mode):
"""Analyze an image for steganographic detectability.
Runs chi-square and RS (Regular-Singular) statistical tests to estimate
how detectable any hidden data might be. Outputs a risk level.
Examples:
stegasoo check carrier.png
stegasoo check stego.png --json
stegasoo check suspicious.bmp --mode lsb
"""
from .steganalysis import check_image
with open(image, "rb") as f:
image_data = f.read()
result = check_image(image_data, mode=mode)
result["filename"] = Path(image).name
if as_json:
click.echo(json.dumps(result, indent=2))
else:
risk = result["risk"]
risk_colors = {"low": "green", "medium": "yellow", "high": "red"}
risk_display = click.style(risk.upper(), fg=risk_colors.get(risk, "white"), bold=True)
click.echo(f"\n Steganalysis: {result['filename']}")
click.echo(f" Image: {result['width']}x{result['height']}, {result['channels']} channels")
click.echo(f" Detectability risk: {risk_display}")
click.echo("\n Chi-square (p-values):")
for ch, p in result["chi_square"].items():
indicator = "!" if p < 0.05 else " "
click.echo(f" {indicator} {ch}: {p:.6f}")
click.echo("\n RS embedding estimate:")
for ch, est in result["rs"].items():
indicator = "!" if est > 0.1 else " "
click.echo(f" {indicator} {ch}: {est:.4f} ({est * 100:.1f}%)")
click.echo()
# =============================================================================
# ADMIN COMMANDS (Web UI administration)
# =============================================================================

View File

@@ -44,7 +44,9 @@ MAGIC_HEADER = b"\x89ST3"
# Version 1-3: Date-dependent encryption (v3.0.x - v3.1.x)
# Version 4: Date-independent encryption (v3.2.0)
# Version 5: Channel key support (v4.0.0) - adds flags byte to header
FORMAT_VERSION = 5
# Version 6: HKDF per-message key derivation (v4.4.0) - adds message nonce to header
FORMAT_VERSION = 6
FORMAT_VERSION_LEGACY = 5 # For backward-compatible decryption
# Payload type markers
PAYLOAD_TEXT = 0x01
@@ -66,6 +68,11 @@ ARGON2_PARALLELISM = 4
# PBKDF2 fallback parameters
PBKDF2_ITERATIONS = 600000
# HKDF per-message key derivation (v4.4.0 / FORMAT_VERSION 6)
MESSAGE_NONCE_SIZE = 16 # 128-bit random nonce per message
HKDF_INFO_ENCRYPT = b"stegasoo-v6-encrypt" # HKDF info for encryption key
HKDF_INFO_PIXEL = b"stegasoo-v6-pixel" # HKDF info for pixel selection key (reserved)
# ============================================================================
# INPUT LIMITS
# ============================================================================
@@ -244,6 +251,17 @@ def get_wordlist() -> list[str]:
return _bip39_words
# =============================================================================
# STEGANALYSIS (v4.4.0)
# =============================================================================
# Chi-square p-value threshold: HIGH p-value = equalized PoV pairs = suspicious
STEGANALYSIS_CHI_SUSPICIOUS_THRESHOLD = 0.95 # p > 0.95 → pairs suspiciously equalized
# RS embedding rate thresholds (primary metric): higher = more likely embedded
STEGANALYSIS_RS_HIGH_THRESHOLD = 0.3 # > 30% estimated embedding → high risk
STEGANALYSIS_RS_MEDIUM_THRESHOLD = 0.1 # > 10% estimated embedding → medium risk
# =============================================================================
# DCT STEGANOGRAPHY (v3.0+)
# =============================================================================

View File

@@ -29,7 +29,9 @@ import secrets
import struct
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.primitives import hashes as _hashes
from cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes
from cryptography.hazmat.primitives.kdf.hkdf import HKDFExpand
from PIL import Image
from .constants import (
@@ -37,9 +39,12 @@ from .constants import (
ARGON2_PARALLELISM,
ARGON2_TIME_COST,
FORMAT_VERSION,
FORMAT_VERSION_LEGACY,
HKDF_INFO_ENCRYPT,
IV_SIZE,
MAGIC_HEADER,
MAX_FILENAME_LENGTH,
MESSAGE_NONCE_SIZE,
PAYLOAD_FILE,
PAYLOAD_TEXT,
PBKDF2_ITERATIONS,
@@ -63,6 +68,7 @@ except ImportError:
from cryptography.hazmat.primitives.kdf.pbkdf2 import PBKDF2HMAC
# =============================================================================
# CHANNEL KEY RESOLUTION
# =============================================================================
@@ -314,6 +320,30 @@ def derive_pixel_key(
return hashlib.sha256(material + b"pixel_selection").digest()
def derive_message_key(root_key: bytes, nonce: bytes) -> bytes:
"""
Derive a per-message encryption key via HKDF-Expand.
Each message gets a unique encryption key even with identical credentials,
because the nonce is random per message. This provides key diversification:
compromising the ciphertext of one message doesn't help with another.
Args:
root_key: 32-byte root key from Argon2id/PBKDF2
nonce: 16-byte random nonce (unique per message)
Returns:
32-byte per-message encryption key
"""
hkdf = HKDFExpand(
algorithm=_hashes.SHA256(),
length=32,
info=HKDF_INFO_ENCRYPT + nonce,
backend=default_backend(),
)
return hkdf.derive(root_key)
def _pack_payload(
content: str | bytes | FilePayload,
) -> tuple[bytes, int]:
@@ -472,7 +502,12 @@ def encrypt_message(
"""
try:
salt = secrets.token_bytes(SALT_SIZE)
key = derive_hybrid_key(photo_data, passphrase, salt, pin, rsa_key_data, channel_key)
root_key = derive_hybrid_key(photo_data, passphrase, salt, pin, rsa_key_data, channel_key)
# v6: Per-message key via HKDF — each message gets a unique encryption key
message_nonce = secrets.token_bytes(MESSAGE_NONCE_SIZE)
key = derive_message_key(root_key, message_nonce)
iv = secrets.token_bytes(IV_SIZE)
# Determine flags
@@ -502,28 +537,36 @@ def encrypt_message(
"Padded message: %d bytes (payload + %d padding)", len(padded_message), padding_needed
)
# Build header for AAD
# Build header for AAD (v6: includes nonce in authenticated data)
header = MAGIC_HEADER + bytes([FORMAT_VERSION, flags])
# Encrypt with AES-256-GCM
cipher = Cipher(algorithms.AES(key), modes.GCM(iv), backend=default_backend())
encryptor = cipher.encryptor()
encryptor.authenticate_additional_data(header)
encryptor.authenticate_additional_data(header + message_nonce)
ciphertext = encryptor.update(padded_message) + encryptor.finalize()
total_size = len(header) + len(salt) + len(iv) + len(encryptor.tag) + len(ciphertext)
total_size = (
len(header)
+ MESSAGE_NONCE_SIZE
+ len(salt)
+ len(iv)
+ len(encryptor.tag)
+ len(ciphertext)
)
logger.debug(
"Encrypted output: %d bytes (header=%d, salt=%d, iv=%d, tag=%d, ciphertext=%d)",
"Encrypted output: %d bytes (header=%d, nonce=%d, salt=%d, iv=%d, tag=%d, ct=%d)",
total_size,
len(header),
MESSAGE_NONCE_SIZE,
len(salt),
len(iv),
len(encryptor.tag),
len(ciphertext),
)
# v4.0.0: Header with flags byte
return header + salt + iv + encryptor.tag + ciphertext
# v6: [magic|version|flags|nonce|salt|iv|tag|ciphertext]
return header + message_nonce + salt + iv + encryptor.tag + ciphertext
except Exception as e:
logger.error("Encryption failed: %s", e)
@@ -534,43 +577,78 @@ def parse_header(encrypted_data: bytes) -> dict | None:
"""
Parse the header from encrypted data.
v4.0.0: Includes flags byte for channel key indicator.
Supports both v5 (legacy) and v6 (HKDF) header formats.
v5: [magic:4][ver:1][flags:1][salt:32][iv:12][tag:16][ciphertext] (66+ bytes)
v6: [magic:4][ver:1][flags:1][nonce:16][salt:32][iv:12][tag:16][ciphertext] (82+ bytes)
Args:
encrypted_data: Raw encrypted bytes
Returns:
Dict with salt, iv, tag, ciphertext, flags or None if invalid
Dict with version, salt, iv, tag, ciphertext, flags, and optionally
message_nonce (v6). Returns None if invalid.
"""
# Min size: Magic(4) + Version(1) + Flags(1) + Salt(32) + IV(12) + Tag(16) = 66 bytes
# Min v5 size: 4+1+1+32+12+16 = 66 bytes
if len(encrypted_data) < 66 or encrypted_data[:4] != MAGIC_HEADER:
return None
try:
version = encrypted_data[4]
if version != FORMAT_VERSION:
if version == FORMAT_VERSION:
# v6: has message nonce
if len(encrypted_data) < 82:
return None
flags = encrypted_data[5]
offset = 6
message_nonce = encrypted_data[offset : offset + MESSAGE_NONCE_SIZE]
offset += MESSAGE_NONCE_SIZE
salt = encrypted_data[offset : offset + SALT_SIZE]
offset += SALT_SIZE
iv = encrypted_data[offset : offset + IV_SIZE]
offset += IV_SIZE
tag = encrypted_data[offset : offset + TAG_SIZE]
offset += TAG_SIZE
ciphertext = encrypted_data[offset:]
return {
"version": version,
"flags": flags,
"has_channel_key": bool(flags & FLAG_CHANNEL_KEY),
"message_nonce": message_nonce,
"salt": salt,
"iv": iv,
"tag": tag,
"ciphertext": ciphertext,
}
elif version == FORMAT_VERSION_LEGACY:
# v5: no nonce
flags = encrypted_data[5]
offset = 6
salt = encrypted_data[offset : offset + SALT_SIZE]
offset += SALT_SIZE
iv = encrypted_data[offset : offset + IV_SIZE]
offset += IV_SIZE
tag = encrypted_data[offset : offset + TAG_SIZE]
offset += TAG_SIZE
ciphertext = encrypted_data[offset:]
return {
"version": version,
"flags": flags,
"has_channel_key": bool(flags & FLAG_CHANNEL_KEY),
"message_nonce": None,
"salt": salt,
"iv": iv,
"tag": tag,
"ciphertext": ciphertext,
}
else:
return None
flags = encrypted_data[5]
offset = 6
salt = encrypted_data[offset : offset + SALT_SIZE]
offset += SALT_SIZE
iv = encrypted_data[offset : offset + IV_SIZE]
offset += IV_SIZE
tag = encrypted_data[offset : offset + TAG_SIZE]
offset += TAG_SIZE
ciphertext = encrypted_data[offset:]
return {
"version": version,
"flags": flags,
"has_channel_key": bool(flags & FLAG_CHANNEL_KEY),
"salt": salt,
"iv": iv,
"tag": tag,
"ciphertext": ciphertext,
}
except Exception:
return None
@@ -622,12 +700,21 @@ def decrypt_message(
message_has_key = header["has_channel_key"]
try:
key = derive_hybrid_key(
root_key = derive_hybrid_key(
photo_data, passphrase, header["salt"], pin, rsa_key_data, channel_key
)
# Reconstruct header for AAD verification
aad_header = MAGIC_HEADER + bytes([FORMAT_VERSION, header["flags"]])
version = header["version"]
message_nonce = header["message_nonce"]
if version == FORMAT_VERSION and message_nonce is not None:
# v6: Derive per-message key via HKDF
key = derive_message_key(root_key, message_nonce)
aad_header = MAGIC_HEADER + bytes([FORMAT_VERSION, header["flags"]]) + message_nonce
else:
# v5 (legacy): Root key used directly
key = root_key
aad_header = MAGIC_HEADER + bytes([FORMAT_VERSION_LEGACY, header["flags"]])
cipher = Cipher(
algorithms.AES(key), modes.GCM(header["iv"], header["tag"]), backend=default_backend()
@@ -647,7 +734,7 @@ def decrypt_message(
payload_data = padded_plaintext[:original_length]
result = _unpack_payload(payload_data)
logger.debug("Decryption successful: %s", result.payload_type)
logger.debug("Decryption successful: %s (v%d)", result.payload_type, version)
return result
except Exception as e:

View File

@@ -12,7 +12,7 @@ Why is this cool?
Two approaches depending on what you want:
1. PNG output: We do our own DCT math via scipy (works on any image)
2. JPEG output: We use jpeglib to directly tweak the coefficients (chef's kiss)
2. JPEG output: We use jpeglib to directly modify the coefficients (chef's kiss)
v4.1.0 - The "please stop corrupting my data" release:
- Reed-Solomon error correction (can fix up to 16 byte errors per chunk)
@@ -56,13 +56,12 @@ except ImportError:
idctn = None
# Check for jpeglib availability (for proper JPEG mode)
# jpeglib replaces jpegio for Python 3.13+ compatibility
try:
import jpeglib
HAS_JPEGIO = True # Keep variable name for compatibility
HAS_JPEGLIB = True
except ImportError:
HAS_JPEGIO = False
HAS_JPEGLIB = False
jpeglib = None
# Import custom exceptions
@@ -170,20 +169,20 @@ QUANT_STEP = 25
# Magic bytes so we can identify our own images
DCT_MAGIC = b"DCTS" # scipy DCT mode marker
JPEGIO_MAGIC = b"JPGS" # jpegio native JPEG mode marker
JPEGLIB_MAGIC = b"JPGS" # jpeglib native JPEG mode marker
HEADER_SIZE = 10 # Magic (4) + version (1) + flags (1) + length (4)
OUTPUT_FORMAT_PNG = "png"
OUTPUT_FORMAT_JPEG = "jpeg"
JPEG_OUTPUT_QUALITY = 95 # High quality but not 100 (100 causes issues, see below)
# For jpegio mode: we only embed in coefficients with magnitude >= 2
# For jpeglib mode: we only embed in coefficients with magnitude >= 2
# Coefficients of 0 or 1 are usually quantized noise - unreliable
JPEGIO_MIN_COEF_MAGNITUDE = 2
JPEGLIB_MIN_COEF_MAGNITUDE = 2
# We embed in the Y (luminance) channel only - it has the most capacity
# Cb/Cr are often subsampled 4:2:0 anyway
JPEGIO_EMBED_CHANNEL = 0
JPEGLIB_EMBED_CHANNEL = 0
# Header flags
FLAG_COLOR_MODE = 0x01 # Set if we preserved color (YCbCr mode)
@@ -204,10 +203,10 @@ RS_LENGTH_PREFIX_SIZE = RS_LENGTH_HEADER_SIZE * RS_LENGTH_COPIES # 24 bytes tot
MAX_CHUNK_HEIGHT = 512 # Process in strips to keep memory sane
# Fun bug: JPEGs saved with quality=100 have quantization tables full of 1s
# This makes the DCT coefficients HUGE and jpegio crashes spectacularly
# This makes the DCT coefficients HUGE and jpeglib crashes spectacularly
# Solution: detect and re-save at quality 95 first
JPEGIO_NORMALIZE_QUALITY = 95
JPEGIO_MAX_QUANT_VALUE_THRESHOLD = 1 # All 1s in quant table = bad news
JPEGLIB_NORMALIZE_QUALITY = 95
JPEGLIB_MAX_QUANT_VALUE_THRESHOLD = 1 # All 1s in quant table = bad news
# ============================================================================
@@ -261,8 +260,8 @@ def has_dct_support() -> bool:
return HAS_SCIPY
def has_jpegio_support() -> bool:
return HAS_JPEGIO
def has_jpeglib_support() -> bool:
return HAS_JPEGLIB
# ============================================================================
@@ -654,11 +653,11 @@ def _parse_header(header_bits: list) -> tuple[int, int, int]:
# ============================================================================
# JPEGIO HELPERS
# JPEGLIB HELPERS
# ============================================================================
def _jpegio_bytes_to_file(data: bytes, suffix: str = ".jpg") -> str:
def _jpeglib_bytes_to_file(data: bytes, suffix: str = ".jpg") -> str:
import os
import tempfile
@@ -670,19 +669,19 @@ def _jpegio_bytes_to_file(data: bytes, suffix: str = ".jpg") -> str:
return path
def _jpegio_get_usable_positions(coef_array: np.ndarray) -> list:
def _jpeglib_get_usable_positions(coef_array: np.ndarray) -> list:
positions = []
h, w = coef_array.shape
for row in range(h):
for col in range(w):
if (row % BLOCK_SIZE == 0) and (col % BLOCK_SIZE == 0):
continue
if abs(coef_array[row, col]) >= JPEGIO_MIN_COEF_MAGNITUDE:
if abs(coef_array[row, col]) >= JPEGLIB_MIN_COEF_MAGNITUDE:
positions.append((row, col))
return positions
def _jpegio_generate_order(num_positions: int, seed: bytes) -> list:
def _jpeglib_generate_order(num_positions: int, seed: bytes) -> list:
hash_bytes = hashlib.sha256(seed + b"jpeg_coef_order").digest()
rng = np.random.RandomState(int.from_bytes(hash_bytes[:4], "big"))
order = list(range(num_positions))
@@ -690,15 +689,15 @@ def _jpegio_generate_order(num_positions: int, seed: bytes) -> list:
return order
def _jpegio_create_header(data_length: int, flags: int = 0) -> bytes:
return struct.pack(">4sBBI", JPEGIO_MAGIC, 1, flags, data_length)
def _jpeglib_create_header(data_length: int, flags: int = 0) -> bytes:
return struct.pack(">4sBBI", JPEGLIB_MAGIC, 1, flags, data_length)
def _jpegio_parse_header(header_bytes: bytes) -> tuple[int, int, int]:
def _jpeglib_parse_header(header_bytes: bytes) -> tuple[int, int, int]:
if len(header_bytes) < HEADER_SIZE:
raise ValueError("Insufficient header data")
magic, version, flags, length = struct.unpack(">4sBBI", header_bytes[:HEADER_SIZE])
if magic != JPEGIO_MAGIC:
if magic != JPEGLIB_MAGIC:
raise InvalidMagicBytesError("Not a Stegasoo JPEG or wrong mode")
return version, flags, length
@@ -782,7 +781,7 @@ def estimate_capacity_comparison(image_data: bytes) -> dict:
"available": HAS_SCIPY,
},
"jpeg_native": {
"available": HAS_JPEGIO,
"available": HAS_JPEGLIB,
"note": "Uses jpeglib for proper JPEG coefficient embedding",
},
}
@@ -795,24 +794,54 @@ def embed_in_dct(
output_format: str = OUTPUT_FORMAT_PNG,
color_mode: str = "color",
progress_file: str | None = None,
quant_step: int | None = None,
jpeg_quality: int | None = None,
max_dimension: int | None = None,
) -> tuple[bytes, DCTEmbedStats]:
"""Embed data using DCT coefficient modification."""
"""Embed data using DCT coefficient modification.
Args:
data: Payload bytes to embed.
carrier_image: Carrier image bytes.
seed: Key for block selection.
output_format: 'png' or 'jpeg'.
color_mode: 'color' or 'grayscale'.
progress_file: Optional progress file.
quant_step: Override QIM quantization step (default: QUANT_STEP).
Higher = more robust to recompression, more visible.
jpeg_quality: Override JPEG output quality (default: JPEG_OUTPUT_QUALITY).
max_dimension: Resize carrier if larger than this.
"""
if output_format not in (OUTPUT_FORMAT_PNG, OUTPUT_FORMAT_JPEG):
raise ValueError(f"Invalid output format: {output_format}")
if color_mode not in ("color", "grayscale"):
color_mode = "color"
qs = quant_step if quant_step is not None else QUANT_STEP
# Apply EXIF orientation to carrier image before embedding
# This ensures portrait photos are embedded in their correct visual orientation
carrier_image = _apply_exif_orientation(carrier_image)
if output_format == OUTPUT_FORMAT_JPEG and HAS_JPEGIO:
return _embed_jpegio(data, carrier_image, seed, color_mode, progress_file)
# Resize if max_dimension specified (for platform presets)
if max_dimension is not None:
img_check = Image.open(io.BytesIO(carrier_image))
w, h = img_check.size
if max(w, h) > max_dimension:
scale = max_dimension / max(w, h)
new_size = (int(w * scale), int(h * scale))
img_check = img_check.resize(new_size, Image.LANCZOS)
buf = io.BytesIO()
img_check.save(buf, format="PNG")
carrier_image = buf.getvalue()
img_check.close()
if output_format == OUTPUT_FORMAT_JPEG and HAS_JPEGLIB:
return _embed_jpeglib(data, carrier_image, seed, color_mode, progress_file)
_check_scipy()
return _embed_scipy_dct_safe(
data, carrier_image, seed, output_format, color_mode, progress_file
data, carrier_image, seed, output_format, color_mode, progress_file, quant_step=qs
)
@@ -823,6 +852,7 @@ def _embed_scipy_dct_safe(
output_format: str,
color_mode: str = "color",
progress_file: str | None = None,
quant_step: int = QUANT_STEP,
) -> tuple[bytes, DCTEmbedStats]:
"""
Embed using scipy DCT with safe memory handling.
@@ -885,7 +915,9 @@ def _embed_scipy_dct_safe(
gc.collect()
# Embed in Y channel
Y_embedded = _embed_in_channel_safe(Y_padded, bits, block_order, blocks_x, progress_file)
Y_embedded = _embed_in_channel_safe(
Y_padded, bits, block_order, blocks_x, progress_file, quant_step=quant_step
)
del Y_padded
gc.collect()
@@ -909,7 +941,9 @@ def _embed_scipy_dct_safe(
del image
gc.collect()
embedded = _embed_in_channel_safe(padded, bits, block_order, blocks_x, progress_file)
embedded = _embed_in_channel_safe(
padded, bits, block_order, blocks_x, progress_file, quant_step=quant_step
)
del padded
gc.collect()
@@ -943,6 +977,7 @@ def _embed_in_channel_safe(
block_order: list,
blocks_x: int,
progress_file: str | None = None,
quant_step: int = QUANT_STEP,
) -> np.ndarray:
"""
Embed bits in channel using vectorized DCT operations.
@@ -1005,17 +1040,17 @@ def _embed_in_channel_safe(
coeffs = dct_blocks[i, embed_rows, embed_cols]
bit_array = np.array(block_bits)
# QIM embedding: round to grid, adjust for bit
quantized = np.round(coeffs / QUANT_STEP).astype(int)
quantized = np.round(coeffs / quant_step).astype(int)
# If quantized % 2 != bit, nudge coefficient
needs_adjust = (quantized % 2) != bit_array
# Determine direction to nudge
dct_blocks[i, embed_rows[needs_adjust], embed_cols[needs_adjust]] = (
(quantized[needs_adjust] + (1 - 2 * (quantized[needs_adjust] % 2 == 1)))
* QUANT_STEP
* quant_step
).astype(np.float64)
# For bits that already match, just quantize
dct_blocks[i, embed_rows[~needs_adjust], embed_cols[~needs_adjust]] = (
quantized[~needs_adjust] * QUANT_STEP
quantized[~needs_adjust] * quant_step
).astype(np.float64)
else:
# Partial block - process remaining bits individually
@@ -1052,12 +1087,12 @@ def _embed_in_channel_safe(
return result
def _normalize_jpeg_for_jpegio(image_data: bytes) -> bytes:
def _normalize_jpeg_for_jpeglib(image_data: bytes) -> bytes:
"""
Normalize a JPEG image to ensure jpegio can process it safely.
Normalize a JPEG image to ensure jpeglib can process it safely.
JPEGs saved with quality=100 have quantization tables with all values = 1,
which causes jpegio to crash due to huge coefficient magnitudes.
which causes jpeglib to crash due to huge coefficient magnitudes.
This function detects such images and re-saves them at a safe quality level.
Args:
@@ -1078,7 +1113,7 @@ def _normalize_jpeg_for_jpegio(image_data: bytes) -> bytes:
if hasattr(img, "quantization") and img.quantization:
for table_id, table in img.quantization.items():
# If all values in any table are <= threshold, normalize
if max(table) <= JPEGIO_MAX_QUANT_VALUE_THRESHOLD:
if max(table) <= JPEGLIB_MAX_QUANT_VALUE_THRESHOLD:
needs_normalization = True
break
@@ -1091,25 +1126,25 @@ def _normalize_jpeg_for_jpegio(image_data: bytes) -> bytes:
img = img.convert("RGB")
buffer = io.BytesIO()
img.save(buffer, format="JPEG", quality=JPEGIO_NORMALIZE_QUALITY, subsampling=0)
img.save(buffer, format="JPEG", quality=JPEGLIB_NORMALIZE_QUALITY, subsampling=0)
img.close()
return buffer.getvalue()
def _embed_jpegio(
def _embed_jpeglib(
data: bytes,
carrier_image: bytes,
seed: bytes,
color_mode: str = "color",
progress_file: str | None = None,
) -> tuple[bytes, DCTEmbedStats]:
"""Embed using jpegio for proper JPEG coefficient modification."""
"""Embed using jpeglib for proper JPEG coefficient modification."""
import os
import tempfile
# Normalize JPEG to avoid crashes with quality=100 images
carrier_image = _normalize_jpeg_for_jpegio(carrier_image)
carrier_image = _normalize_jpeg_for_jpeglib(carrier_image)
img = Image.open(io.BytesIO(carrier_image))
width, height = img.size
@@ -1122,20 +1157,20 @@ def _embed_jpegio(
carrier_image = buffer.getvalue()
img.close()
input_path = _jpegio_bytes_to_file(carrier_image, suffix=".jpg")
input_path = _jpeglib_bytes_to_file(carrier_image, suffix=".jpg")
output_path = tempfile.mktemp(suffix=".jpg")
flags = FLAG_COLOR_MODE if color_mode == "color" else 0
try:
jpeg = jpeglib.to_jpegio(jpeglib.read_dct(input_path))
coef_array = jpeg.coef_arrays[JPEGIO_EMBED_CHANNEL]
coef_array = jpeg.coef_arrays[JPEGLIB_EMBED_CHANNEL]
all_positions = _jpegio_get_usable_positions(coef_array)
order = _jpegio_generate_order(len(all_positions), seed)
all_positions = _jpeglib_get_usable_positions(coef_array)
order = _jpeglib_generate_order(len(all_positions), seed)
# Build raw payload (header + data)
header = _jpegio_create_header(len(data), flags)
header = _jpeglib_create_header(len(data), flags)
raw_payload = header + data
# Apply Reed-Solomon error correction to entire payload if available
@@ -1402,6 +1437,7 @@ def extract_from_dct(
stego_image: bytes,
seed: bytes,
progress_file: str | None = None,
quant_step: int | None = None,
) -> bytes:
"""
Extract data from DCT stego image.
@@ -1412,6 +1448,7 @@ def extract_from_dct(
Uses quick header validation to skip obviously invalid rotations.
"""
qs = quant_step if quant_step is not None else QUANT_STEP
rotations_to_try = [0, 90, 180, 270]
last_error = None
valid_rotations = []
@@ -1429,7 +1466,7 @@ def extract_from_dct(
# If no rotations pass quick check, try all anyway (fallback)
if not valid_rotations:
# Must try all rotations - quick validation might have failed due to
# scipy vs jpegio differences or other edge cases
# scipy vs jpeglib differences or other edge cases
for rotation in rotations_to_try:
if rotation == 0:
valid_rotations.append((0, stego_image))
@@ -1443,9 +1480,9 @@ def extract_from_dct(
fmt = img.format
img.close()
if fmt == "JPEG" and HAS_JPEGIO:
if fmt == "JPEG" and HAS_JPEGLIB:
try:
result = _extract_jpegio(image_to_decode, seed, progress_file)
result = _extract_jpeglib(image_to_decode, seed, progress_file)
if rotation != 0:
try:
from . import debug
@@ -1459,7 +1496,7 @@ def extract_from_dct(
continue
_check_scipy()
result = _extract_scipy_dct_safe(image_to_decode, seed, progress_file)
result = _extract_scipy_dct_safe(image_to_decode, seed, progress_file, quant_step=qs)
if rotation != 0:
try:
from . import debug
@@ -1481,6 +1518,7 @@ def _extract_scipy_dct_safe(
stego_image: bytes,
seed: bytes,
progress_file: str | None = None,
quant_step: int = QUANT_STEP,
) -> bytes:
"""Extract using safe DCT operations with vectorized processing."""
# Progress starts at 25% (decode.py writes 20% for Argon2, 25% before extraction)
@@ -1542,7 +1580,7 @@ def _extract_scipy_dct_safe(
coeffs = dct_blocks[:, embed_rows, embed_cols]
# Quantize and extract bits (vectorized)
quantized = np.round(coeffs / QUANT_STEP).astype(int)
quantized = np.round(coeffs / quant_step).astype(int)
bits = (quantized % 2).flatten().tolist()
all_bits.extend(bits)
@@ -1660,28 +1698,28 @@ def _extract_scipy_dct_safe(
return data
def _extract_jpegio(
def _extract_jpeglib(
stego_image: bytes,
seed: bytes,
progress_file: str | None = None,
) -> bytes:
"""Extract using jpegio for JPEG images."""
"""Extract using jpeglib for JPEG images."""
import os
# Progress starts at 25% (decode.py writes 20% for Argon2, 25% before extraction)
# Normalize JPEG to avoid crashes with quality=100 images
# (shouldn't happen with stego images, but be defensive)
stego_image = _normalize_jpeg_for_jpegio(stego_image)
stego_image = _normalize_jpeg_for_jpeglib(stego_image)
temp_path = _jpegio_bytes_to_file(stego_image, suffix=".jpg")
temp_path = _jpeglib_bytes_to_file(stego_image, suffix=".jpg")
try:
jpeg = jpeglib.to_jpegio(jpeglib.read_dct(temp_path))
coef_array = jpeg.coef_arrays[JPEGIO_EMBED_CHANNEL]
coef_array = jpeg.coef_arrays[JPEGLIB_EMBED_CHANNEL]
all_positions = _jpegio_get_usable_positions(coef_array)
order = _jpegio_generate_order(len(all_positions), seed)
all_positions = _jpeglib_get_usable_positions(coef_array)
order = _jpeglib_generate_order(len(all_positions), seed)
_write_progress(progress_file, 30, 100, "extracting")
@@ -1751,7 +1789,7 @@ def _extract_jpegio(
_write_progress(progress_file, 75, 100, "decoding")
raw_payload = _rs_decode(rs_encoded)
_write_progress(progress_file, 95, 100, "decoding")
_, flags, data_length = _jpegio_parse_header(raw_payload[:HEADER_SIZE])
_, flags, data_length = _jpeglib_parse_header(raw_payload[:HEADER_SIZE])
data = raw_payload[HEADER_SIZE : HEADER_SIZE + data_length]
_write_progress(progress_file, 100, 100, "complete")
return data
@@ -1772,7 +1810,7 @@ def _extract_jpegio(
]
)
_, flags, data_length = _jpegio_parse_header(header_bytes)
_, flags, data_length = _jpeglib_parse_header(header_bytes)
total_bits_needed = (HEADER_SIZE + data_length) * 8
all_bits = []

View File

@@ -54,6 +54,7 @@ def decode(
embed_mode: str = EMBED_MODE_AUTO,
channel_key: str | bool | None = None,
progress_file: str | None = None,
platform: str | None = None,
) -> DecodeResult:
"""
Decode a message or file from a stego image.
@@ -124,12 +125,21 @@ def decode(
# Progress: key derivation done, starting extraction
_write_progress(progress_file, 25, 100, "extracting")
# Resolve platform preset for DCT extraction
extract_kwargs = {}
if platform:
from .platform_presets import get_preset
preset = get_preset(platform)
extract_kwargs["quant_step"] = preset.quant_step
# Extract encrypted data
encrypted = extract_from_image(
stego_image,
pixel_key,
embed_mode=embed_mode,
progress_file=progress_file,
**extract_kwargs,
)
if not encrypted:

View File

@@ -51,6 +51,7 @@ def encode(
dct_color_mode: str = "color",
channel_key: str | bool | None = None,
progress_file: str | None = None,
platform: str | None = None,
) -> EncodeResult:
"""
Encode a message or file into an image.
@@ -123,6 +124,18 @@ def encode(
# Derive pixel/coefficient selection key (with channel key)
pixel_key = derive_pixel_key(reference_photo, passphrase, pin, rsa_key_data, channel_key)
# Resolve platform preset for DCT encoding
platform_kwargs = {}
if platform:
from .platform_presets import get_preset
preset = get_preset(platform)
platform_kwargs = {
"quant_step": preset.quant_step,
"max_dimension": preset.max_dimension,
"jpeg_quality": preset.jpeg_quality,
}
# Embed in image
stego_data, stats, extension = embed_in_image(
encrypted,
@@ -133,6 +146,7 @@ def encode(
dct_output_format=dct_output_format,
dct_color_mode=dct_color_mode,
progress_file=progress_file,
**platform_kwargs,
)
# Generate filename

View File

@@ -0,0 +1,169 @@
"""
Platform-Calibrated DCT Presets (v4.4.0)
Pre-tuned DCT embedding parameters for social media platforms. Each platform
recompresses uploaded images differently — these presets bake in the known
parameters so payloads survive the round-trip.
Usage::
from stegasoo.platform_presets import get_preset, PLATFORMS
preset = get_preset("telegram")
# Use preset.quant_step, preset.jpeg_quality, etc. in DCT encode
Preset parameters were derived from empirical testing. Platform compression
behavior can change without notice — use ``pre_verify_survival()`` to confirm
payloads survive before relying on a preset.
"""
from __future__ import annotations
from dataclasses import dataclass
@dataclass(frozen=True)
class PlatformPreset:
"""Tuned DCT parameters for a specific platform."""
name: str
jpeg_quality: int # Platform's recompression quality
max_dimension: int # Max width/height before platform resizes
quant_step: int # QIM quantization step (higher = more robust)
embed_start: int # Start index into EMBED_POSITIONS (skip low-freq)
embed_end: int # End index into EMBED_POSITIONS (skip high-freq)
recompress_quality: int # Quality to simulate platform recompression for pre-verify
notes: str = ""
# Platform presets — derived from empirical testing of each platform's
# image processing pipeline. These WILL change as platforms update.
# Last verified: 2026-03-25
PRESETS: dict[str, PlatformPreset] = {
"telegram": PlatformPreset(
name="Telegram",
jpeg_quality=82,
max_dimension=2560,
quant_step=35,
embed_start=4,
embed_end=16,
recompress_quality=80,
notes="~81KB max embeddable. Moderate recompression.",
),
"discord": PlatformPreset(
name="Discord",
jpeg_quality=85,
max_dimension=4096,
quant_step=30,
embed_start=4,
embed_end=18,
recompress_quality=83,
notes="Varies with Nitro. Non-Nitro users get more aggressive compression.",
),
"signal": PlatformPreset(
name="Signal",
jpeg_quality=80,
max_dimension=2048,
quant_step=40,
embed_start=5,
embed_end=15,
recompress_quality=78,
notes="Aggressive recompression. Use smaller payloads for reliability.",
),
"whatsapp": PlatformPreset(
name="WhatsApp",
jpeg_quality=70,
max_dimension=1600,
quant_step=50,
embed_start=5,
embed_end=14,
recompress_quality=68,
notes="Most lossy. Capacity is significantly reduced.",
),
}
PLATFORMS = sorted(PRESETS.keys())
def get_preset(platform: str) -> PlatformPreset:
"""Get the preset for a platform.
Args:
platform: Platform name (telegram, discord, signal, whatsapp).
Returns:
PlatformPreset with tuned DCT parameters.
Raises:
ValueError: If platform is not recognized.
"""
key = platform.lower()
if key not in PRESETS:
available = ", ".join(PLATFORMS)
raise ValueError(f"Unknown platform '{platform}'. Available: {available}")
return PRESETS[key]
def get_embed_positions(preset: PlatformPreset) -> list[tuple[int, int]]:
"""Get the embed positions for a preset.
Args:
preset: Platform preset.
Returns:
List of (row, col) DCT coefficient positions.
"""
from .dct_steganography import EMBED_POSITIONS
return EMBED_POSITIONS[preset.embed_start : preset.embed_end]
def pre_verify_survival(
stego_image: bytes,
seed: bytes,
preset: PlatformPreset,
) -> bool:
"""Verify that a payload survives simulated platform recompression.
Encodes → recompresses at platform quality → attempts extraction.
If extraction succeeds, the payload should survive the real platform.
Args:
stego_image: The stego JPEG image bytes (already encoded).
seed: The same seed used for encoding.
preset: Platform preset to simulate.
Returns:
True if payload survived simulated recompression.
"""
import io
from PIL import Image
from .dct_steganography import extract_from_dct
# Simulate platform recompression
img = Image.open(io.BytesIO(stego_image))
# Resize if over max dimension
w, h = img.size
if max(w, h) > preset.max_dimension:
scale = preset.max_dimension / max(w, h)
new_size = (int(w * scale), int(h * scale))
img = img.resize(new_size, Image.LANCZOS)
# Recompress at platform quality
buf = io.BytesIO()
if img.mode != "RGB":
img = img.convert("RGB")
img.save(buf, format="JPEG", quality=preset.recompress_quality)
img.close()
recompressed = buf.getvalue()
# Try extraction
try:
result = extract_from_dct(recompressed, seed)
return result is not None and len(result) > 0
except Exception:
return False

View File

@@ -0,0 +1,281 @@
"""
Steganalysis Self-Check Module (v4.4.0)
Statistical analysis to estimate detectability risk of stego images.
Runs chi-square and RS (Regular-Singular) analysis on pixel data
to assess how visible the embedding is to an attacker.
Currently LSB-only. DCT steganalysis (calibration attack) deferred.
Usage::
from stegasoo.steganalysis import check_image
result = check_image(image_data)
print(result["risk"]) # "low", "medium", or "high"
print(result["chi_square"]) # per-channel chi-square p-values
print(result["rs"]) # per-channel RS embedding estimates
"""
from __future__ import annotations
import io
from dataclasses import dataclass, field
import numpy as np
from PIL import Image
from .constants import (
STEGANALYSIS_CHI_SUSPICIOUS_THRESHOLD,
STEGANALYSIS_RS_HIGH_THRESHOLD,
STEGANALYSIS_RS_MEDIUM_THRESHOLD,
)
@dataclass
class SteganalysisResult:
"""Result of steganalysis on an image."""
risk: str # "low", "medium", or "high"
chi_square: dict = field(default_factory=dict) # per-channel p-values
rs: dict = field(default_factory=dict) # per-channel embedding estimates
width: int = 0
height: int = 0
channels: int = 0
mode: str = "lsb"
def chi_square_analysis(channel_data: np.ndarray) -> float:
"""Chi-square test on LSB distribution of a single channel.
Groups pixel values into pairs (2i, 2i+1) — so-called "pairs of values"
(PoVs). In a clean image, each pair has a natural frequency ratio.
LSB embedding with random data forces each pair toward equal frequency.
The test measures H0: "pairs are equalized" (consistent with embedding).
Args:
channel_data: Flattened 1-D array of pixel values (uint8).
Returns:
p-value from chi-square test.
HIGH p-value (close to 1.0) → pairs are equalized → suspicious.
LOW p-value (close to 0.0) → pairs are not equalized → less suspicious.
"""
from scipy.stats import chi2
# Count occurrences of each value 0-255
histogram = np.bincount(channel_data.ravel(), minlength=256)
# Group into 128 pairs: (0,1), (2,3), ..., (254,255)
chi_sq = 0.0
degrees_of_freedom = 0
for i in range(0, 256, 2):
observed_even = histogram[i]
observed_odd = histogram[i + 1]
total = observed_even + observed_odd
if total == 0:
continue
expected = total / 2.0
chi_sq += (observed_even - expected) ** 2 / expected
chi_sq += (observed_odd - expected) ** 2 / expected
degrees_of_freedom += 1
if degrees_of_freedom == 0:
return 1.0 # No data to analyze
# p-value: probability of observing this chi-square value by chance
# Low p-value = LSBs are suspiciously uniform = likely embedded
p_value = 1.0 - chi2.cdf(chi_sq, degrees_of_freedom)
return float(p_value)
def rs_analysis(channel_data: np.ndarray, block_size: int = 8) -> float:
"""Regular-Singular groups analysis on a single channel.
Divides the image channel into groups of `block_size` pixels and measures
the "smoothness" (variation) of each group. Applying a flipping function
F1 (flip LSB) and F-1 (flip LSB of value-1) produces Regular (smoother)
and Singular (rougher) groups.
In a clean image: R_m ≈ R_{-m} and S_m ≈ S_{-m}.
LSB embedding causes R_m and S_{-m} to converge while S_m and R_{-m}
diverge, allowing estimation of the embedding rate.
Args:
channel_data: Flattened 1-D array of pixel values (uint8).
block_size: Number of pixels per group (default 8).
Returns:
Estimated embedding rate (0.0 = clean, 1.0 = fully embedded).
Values > 0.5 strongly indicate LSB embedding.
"""
data = channel_data.ravel().astype(np.int16)
n = len(data)
# Trim to multiple of block_size
n_blocks = n // block_size
if n_blocks < 10:
return 0.0 # Not enough data
data = data[: n_blocks * block_size].reshape(n_blocks, block_size)
def variation(block: np.ndarray) -> float:
"""Sum of absolute differences between adjacent pixels."""
return float(np.sum(np.abs(np.diff(block))))
def flip_positive(block: np.ndarray) -> np.ndarray:
"""F1: flip LSB (0↔1, 2↔3, 4↔5, ...)."""
return block ^ 1
def flip_negative(block: np.ndarray) -> np.ndarray:
"""F-1: flip LSB of (value - 1), i.e. -1↔0, 1↔2, 3↔4, ..."""
result = block.copy()
even_mask = (block % 2) == 0
result[even_mask] -= 1
result[~even_mask] += 1
return result
r_m = s_m = r_neg = s_neg = 0
for i in range(n_blocks):
block = data[i]
v_orig = variation(block)
v_f1 = variation(flip_positive(block))
if v_f1 > v_orig:
r_m += 1
elif v_f1 < v_orig:
s_m += 1
v_fn1 = variation(flip_negative(block))
if v_fn1 > v_orig:
r_neg += 1
elif v_fn1 < v_orig:
s_neg += 1
# Estimate embedding rate using the RS quadratic formula
# d0 = R_m - S_m, d1 = R_{-m} - S_{-m}
# The embedding rate p satisfies: d(p/2) = d0, d(1 - p/2) = d1
# Simplified estimator: p ≈ (R_m - S_m) / (R_{-m} - S_{-m}) divergence
d0 = r_m - s_m
d1 = r_neg - s_neg
if n_blocks == 0:
return 0.0
# Use the simplified dual-statistic estimator
# In clean images: d0 ≈ d1 (both positive)
# In embedded images: d0 → 0 while d1 stays positive
if d1 == 0:
# Can't estimate — likely very embedded or degenerate
return 0.5 if d0 == 0 else 0.0
# Ratio-based estimate: how much has d0 dropped relative to d1
ratio = d0 / d1
if ratio >= 1.0:
return 0.0 # d0 ≥ d1 means no evidence of embedding
if ratio <= 0.0:
return 1.0 # d0 collapsed or inverted
# Linear interpolation: ratio=1 → 0% embedded, ratio=0 → 100% embedded
estimate = 1.0 - ratio
return float(np.clip(estimate, 0.0, 1.0))
def assess_risk(chi_p_values: dict[str, float], rs_estimates: dict[str, float]) -> str:
"""Map analysis results to a risk level.
RS analysis is the primary metric (reliable for both sequential and
random-order embedding). Chi-square is supplementary — high p-values
indicate equalized PoV pairs, which is suspicious for random LSB embedding.
Args:
chi_p_values: Per-channel chi-square p-values (high = suspicious).
rs_estimates: Per-channel RS embedding rate estimates (high = suspicious).
Returns:
"low", "medium", or "high" detectability risk.
"""
if not chi_p_values and not rs_estimates:
return "low"
# RS is the primary indicator: any channel with high embedding estimate
max_rs = max(rs_estimates.values()) if rs_estimates else 0.0
# Chi-square: high p-value means pairs are equalized (suspicious)
max_chi_p = max(chi_p_values.values()) if chi_p_values else 0.0
chi_suspicious = max_chi_p > STEGANALYSIS_CHI_SUSPICIOUS_THRESHOLD
# High risk: RS strongly indicates embedding
if max_rs > STEGANALYSIS_RS_HIGH_THRESHOLD:
return "high"
# Medium risk: moderate RS signal, or RS + chi-square both flagging
if max_rs > STEGANALYSIS_RS_MEDIUM_THRESHOLD:
return "medium"
if chi_suspicious and max_rs > 0.05:
return "medium"
return "low"
def check_image(image_data: bytes, mode: str = "lsb") -> dict:
"""Run steganalysis on an image and return detectability assessment.
Args:
image_data: Raw image bytes (PNG, BMP, etc.).
mode: Analysis mode — currently only "lsb" is supported.
Returns:
Dict with keys: risk, chi_square, rs, width, height, channels, mode.
"""
if mode not in ("lsb", "auto"):
raise ValueError(f"Unsupported steganalysis mode: {mode}. Use 'lsb' or 'auto'.")
img = Image.open(io.BytesIO(image_data))
if img.mode not in ("RGB", "RGBA", "L"):
img = img.convert("RGB")
width, height = img.size
pixels = np.array(img)
img.close()
channel_names = ["R", "G", "B"] if pixels.ndim == 3 else ["L"]
if pixels.ndim == 2:
pixels = pixels[:, :, np.newaxis]
num_channels = min(pixels.shape[2], 3) # Skip alpha
chi_p_values = {}
rs_estimates = {}
for i in range(num_channels):
name = channel_names[i]
channel = pixels[:, :, i].ravel()
chi_p_values[name] = chi_square_analysis(channel)
rs_estimates[name] = rs_analysis(channel)
risk = assess_risk(chi_p_values, rs_estimates)
result = SteganalysisResult(
risk=risk,
chi_square=chi_p_values,
rs=rs_estimates,
width=width,
height=height,
channels=num_channels,
mode=mode,
)
return {
"risk": result.risk,
"chi_square": result.chi_square,
"rs": result.rs,
"width": result.width,
"height": result.height,
"channels": result.channels,
"mode": result.mode,
}

View File

@@ -107,13 +107,14 @@ EXT_TO_FORMAT = {
# - v3.1.0: 76 bytes (had date field - 10+1 bytes)
# - v3.2.0: 65 bytes (removed date, simpler)
# - v4.0.0: 66 bytes (added flags byte for channel key)
# - v4.4.0: 82 bytes (added 16-byte message nonce for HKDF)
HEADER_OVERHEAD = 66 # What the crypto layer adds to any message
HEADER_OVERHEAD = 82 # What the crypto layer adds to any message (v6 format)
LENGTH_PREFIX = 4 # We prepend the payload length for LSB extraction
ENCRYPTION_OVERHEAD = HEADER_OVERHEAD + LENGTH_PREFIX # Total: 70 bytes
ENCRYPTION_OVERHEAD = HEADER_OVERHEAD + LENGTH_PREFIX # Total: 86 bytes
# That 70 bytes is your minimum image capacity requirement.
# A tiny 100x100 image gives you ~3750 bytes capacity, minus 70 = ~3680 usable.
# That 86 bytes is your minimum image capacity requirement.
# A tiny 100x100 image gives you ~3750 bytes capacity, minus 86 = ~3664 usable.
# DCT output format options (v3.0.1)
DCT_OUTPUT_PNG = "png"
@@ -609,6 +610,9 @@ def embed_in_image(
dct_output_format: str = DCT_OUTPUT_PNG,
dct_color_mode: str = "color",
progress_file: str | None = None,
quant_step: int | None = None,
jpeg_quality: int | None = None,
max_dimension: int | None = None,
) -> tuple[bytes, Union[EmbedStats, "DCTEmbedStats"], str]:
"""
Embed data into an image using specified mode.
@@ -636,49 +640,54 @@ def embed_in_image(
embed_mode in VALID_EMBED_MODES, f"Invalid embed_mode: {embed_mode}. Use 'lsb' or 'dct'"
)
# DCT MODE
if embed_mode == EMBED_MODE_DCT:
if not has_dct_support():
raise ImportError(
"scipy is required for DCT embedding mode. " "Install with: pip install scipy"
)
# Dispatch via backend registry
from .backends import registry
# Validate DCT output format
backend = registry.get(embed_mode)
if not backend.is_available():
raise ImportError(
f"Dependencies for '{embed_mode}' mode are not installed. "
f"Install with: pip install stegasoo[dct]"
)
if embed_mode == EMBED_MODE_DCT:
# Validate DCT-specific options
if dct_output_format not in (DCT_OUTPUT_PNG, DCT_OUTPUT_JPEG):
debug.print(f"Invalid dct_output_format '{dct_output_format}', defaulting to PNG")
dct_output_format = DCT_OUTPUT_PNG
# Validate DCT color mode (v3.0.1)
if dct_color_mode not in ("grayscale", "color"):
debug.print(f"Invalid dct_color_mode '{dct_color_mode}', defaulting to color")
dct_color_mode = "color"
dct_mod = _get_dct_module()
# Pass output_format and color_mode to DCT module (v3.0.1)
stego_bytes, dct_stats = dct_mod.embed_in_dct(
stego_bytes, dct_stats = backend.embed(
data,
image_data,
pixel_key,
output_format=dct_output_format,
color_mode=dct_color_mode,
progress_file=progress_file,
dct_output_format=dct_output_format,
dct_color_mode=dct_color_mode,
quant_step=quant_step,
jpeg_quality=jpeg_quality,
max_dimension=max_dimension,
)
# Determine extension based on output format
if dct_output_format == DCT_OUTPUT_JPEG:
ext = "jpg"
else:
ext = "png"
ext = "jpg" if dct_output_format == DCT_OUTPUT_JPEG else "png"
debug.print(
f"DCT embedding complete: {dct_output_format.upper()} output, "
f"color_mode={dct_color_mode}, ext={ext}"
)
return stego_bytes, dct_stats, ext
# LSB MODE
return _embed_lsb(data, image_data, pixel_key, bits_per_channel, output_format, progress_file)
# LSB and other image backends
stego_bytes, stats = backend.embed(
data,
image_data,
pixel_key,
progress_file=progress_file,
bits_per_channel=bits_per_channel,
output_format=output_format,
)
ext = getattr(stats, "output_extension", "png")
return stego_bytes, stats, ext
def _embed_lsb(
@@ -844,6 +853,7 @@ def extract_from_image(
bits_per_channel: int = 1,
embed_mode: str = EMBED_MODE_AUTO,
progress_file: str | None = None,
quant_step: int | None = None,
) -> bytes | None:
"""
Extract hidden data from a stego image.
@@ -860,32 +870,40 @@ def extract_from_image(
"""
debug.print(f"extract_from_image: mode={embed_mode}")
# AUTO MODE: Try LSB first, then DCT
from .backends import registry
# AUTO MODE: Try LSB first (cheaper), then other backends
if embed_mode == EMBED_MODE_AUTO:
result = _extract_lsb(image_data, pixel_key, bits_per_channel)
if result is not None:
debug.print("Auto-detect: LSB extraction succeeded")
return result
if has_dct_support():
debug.print("Auto-detect: LSB failed, trying DCT")
result = _extract_dct(image_data, pixel_key, progress_file)
auto_order = [EMBED_MODE_LSB] + [
m for m in registry.available_modes(carrier_type="image") if m != EMBED_MODE_LSB
]
for mode in auto_order:
backend = registry.get(mode)
debug.print(f"Auto-detect: trying {mode}")
result = backend.extract(
image_data,
pixel_key,
progress_file=progress_file,
bits_per_channel=bits_per_channel,
quant_step=quant_step,
)
if result is not None:
debug.print("Auto-detect: DCT extraction succeeded")
debug.print(f"Auto-detect: {mode} extraction succeeded")
return result
debug.print("Auto-detect: All modes failed")
return None
# EXPLICIT DCT MODE
elif embed_mode == EMBED_MODE_DCT:
if not has_dct_support():
raise ImportError("scipy required for DCT mode")
return _extract_dct(image_data, pixel_key, progress_file)
# EXPLICIT LSB MODE
else:
return _extract_lsb(image_data, pixel_key, bits_per_channel)
# EXPLICIT MODE
backend = registry.get(embed_mode)
if not backend.is_available():
raise ImportError(f"Dependencies for '{embed_mode}' mode are not installed.")
return backend.extract(
image_data,
pixel_key,
progress_file=progress_file,
bits_per_channel=bits_per_channel,
quant_step=quant_step,
)
def _extract_dct(
@@ -1099,9 +1117,9 @@ def peek_image(image_data: bytes) -> dict:
# Try DCT extraction (requires scipy/jpeglib)
try:
from .dct_steganography import HAS_JPEGIO, HAS_SCIPY
from .dct_steganography import HAS_JPEGLIB, HAS_SCIPY
if HAS_SCIPY or HAS_JPEGIO:
if HAS_SCIPY or HAS_JPEGLIB:
from .dct_steganography import extract_from_dct
# Extract first few bytes to check header