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phasm-core

Pure-Rust steganography engine for hiding encrypted text messages in JPEG photos.

This is the core library behind Phasm — available on iOS, Android, and the web.

Two Embedding Modes

Ghost (Stealth)

Optimizes for undetectability. Uses the J-UNIWARD cost function to assign distortion costs per DCT coefficient, then embeds via Syndrome-Trellis Codes (STC) to minimize total distortion. The result resists state-of-the-art steganalysis detectors (SRNet, XedroudjNet) at typical embedding rates.

Use Ghost when the stego image will be stored or transmitted without recompression — the embedding does not survive JPEG re-encoding.

Ghost mode also supports file attachments (Brotli-compressed, multi-file).

Shadow Messages (Plausible Deniability)

Ghost mode supports shadow messages — multiple messages hidden in a single image, each with a different passphrase. If coerced into revealing a passphrase, you can give the shadow passphrase instead of the primary one. The adversary decodes a decoy message and has no way to detect whether additional messages exist.

Shadows use Y-channel direct LSB embedding with Reed-Solomon error correction. Key design properties:

  • Cost-pool position selection — shadow positions are drawn from the cheapest UNIWARD-cost regions via two-tier filtering (top-N% cost pool + keyed ChaCha20 permutation), ensuring modifications land in textured areas for maximum stealth
  • ∞-cost protection — when the primary message uses dynamic w ≥ 2, shadow positions receive f32::INFINITY cost in the STC Viterbi trellis, routing the primary encoder around them with BER ≈ 0%
  • Headerless brute-force decode — no magic bytes or agreed-upon parameters. A "first-block peek" decodes just the first RS block for each (fraction, parity) combination to read plaintext_len and derive the exact frame data length — ~30 RS block decodes instead of scanning thousands of FDL values. A small-FDL fallback handles tiny messages (single partial RS block). AES-256-GCM-SIV authentication is the only validator
  • Stego-cost verification — after STC embedding, the encoder re-runs UNIWARD on the stego image to verify shadow BER. If verification fails, an escalation cascade automatically increases RS parity (4 → 8 → 16 → … → 128) until the shadow survives or capacity is exhausted

smart_decode automatically tries shadow decode as a fallback after primary Ghost decode.

SI-UNIWARD (Deep Cover)

When the encoder has access to the original uncompressed pixels (e.g. PNG, HEIC, or RAW input converted to JPEG), SI-UNIWARD (Side-Informed UNIWARD) exploits JPEG quantization rounding errors to dramatically reduce embedding costs. Coefficients that were "close to the boundary" between two quantization levels can be flipped at near-zero cost, and the modification direction is chosen to move toward the pre-quantization value rather than the default nsF5 direction.

The result: ~43% higher capacity at the same detection risk, or equivalently the same capacity with significantly lower distortion. The decoder is completely unchanged — ghost_decode works identically on standard and SI-UNIWARD stego images.

Use ghost_encode_si / ghost_capacity_si when raw pixels are available alongside the JPEG cover.

Armor (Robust)

Optimizes for survivability. Uses Spread Transform Dither Modulation (STDM) to embed bits into stable low-frequency DCT coefficients, protected by adaptive Reed-Solomon ECC with soft-decision decoding via log-likelihood ratios. A DFT magnitude template provides geometric synchronization against rotation, scaling, and cropping.

Armor is the default mode on all platforms.

Fortress Sub-Mode

For short messages, Armor automatically activates Fortress — a BA-QIM (Block-Average Quantization Index Modulation) scheme that embeds one bit per 8x8 block into the block-average brightness. Fortress exploits three invariants of JPEG recompression — block averages, brightness ordering, and coefficient signs — that persist even through aggressive re-encoding.

Fortress survives WhatsApp recompression (QF ~62, resolution resize to 1600px). See how 15 messaging platforms process your photos for a comprehensive platform analysis.

Watson perceptual masking adapts the embedding strength per-block based on local texture energy, keeping modifications invisible in textured regions while protecting smooth areas.

Cover Image Optimizer

optimize_cover preprocesses raw pixels before JPEG compression to improve embedding quality and capacity. Each mode has a different pipeline:

  • Ghost: Texture-adaptive 4-stage pipeline (noise injection, micro-contrast, unsharp mask, smooth-region dithering). Per-pixel 5×5 variance map adapts strength to existing texture — avoids degrading pre-optimized images.
  • Armor: Light pipeline (block-boundary smoothing, DC stabilization) for STDM robustness.
  • Fortress: Minimal (block-boundary smoothing only) to stabilize DC averages for BA-QIM.

"Do no harm" guarantee: if optimization reduces average gradient energy (a proxy for stego capacity), the original pixels are returned unchanged. Modifications are imperceptible (PSNR > 44 dB, SSIM > 0.993).

use phasm_core::{optimize_cover, OptimizerConfig, OptimizerMode};

let optimized = optimize_cover(&raw_pixels_rgb, width, height, &OptimizerConfig {
    strength: 0.85,
    seed: [0u8; 32], // ChaCha20 seed for deterministic noise
    mode: OptimizerMode::Ghost,
});

Decode Auto-Detection

smart_decode tries all modes automatically — Ghost primary → Ghost shadow → Armor → Fortress — no mode selector needed on the decode side.

Quick Start

use phasm_core::{ghost_encode, ghost_decode};

let cover = std::fs::read("photo.jpg").unwrap();
let stego = ghost_encode(&cover, "secret message", "passphrase").unwrap();
let decoded = ghost_decode(&stego, "passphrase").unwrap();
assert_eq!(decoded.text, "secret message");
use phasm_core::{armor_encode, armor_decode};

let cover = std::fs::read("photo.jpg").unwrap();
let stego = armor_encode(&cover, "secret message", "passphrase").unwrap();
let (decoded, quality) = armor_decode(&stego, "passphrase").unwrap();
assert_eq!(decoded.text, "secret message");
println!("Integrity: {:.0}%", quality.integrity_percent);
use phasm_core::{ghost_encode_si, ghost_decode};

// SI-UNIWARD: when you have original uncompressed pixels + the JPEG cover
let raw_pixels_rgb = /* RGB pixel data from PNG/HEIC/RAW */;
let cover = std::fs::read("photo.jpg").unwrap();
let stego = ghost_encode_si(
    &cover, raw_pixels_rgb, width, height, "secret message", "passphrase"
).unwrap();
// Decode is identical — no special decoder needed
let decoded = ghost_decode(&stego, "passphrase").unwrap();
assert_eq!(decoded.text, "secret message");
use phasm_core::{ghost_encode_with_shadows, ghost_decode, ghost_shadow_decode, ShadowLayer};

let cover = std::fs::read("photo.jpg").unwrap();
let shadows = vec![
    ShadowLayer {
        message: "decoy message".into(),
        passphrase: "decoy_pass".into(),
        files: vec![],
    },
];
let stego = ghost_encode_with_shadows(
    &cover, "real secret", &[], "real_pass", &shadows, None
).unwrap();

// Primary message — with the real passphrase
let primary = ghost_decode(&stego, "real_pass").unwrap();
assert_eq!(primary.text, "real secret");

// Shadow message — with the decoy passphrase
let shadow = ghost_shadow_decode(&stego, "decoy_pass").unwrap();
assert_eq!(shadow.text, "decoy message");

API

// Ghost mode (stealth)
ghost_encode(jpeg_bytes, message, passphrase) -> Result<Vec<u8>>
ghost_encode_with_quality(jpeg_bytes, message, passphrase) -> Result<(Vec<u8>, EncodeQuality)>
ghost_decode(jpeg_bytes, passphrase) -> Result<PayloadData>
ghost_encode_with_files(jpeg_bytes, message, files, passphrase) -> Result<Vec<u8>>
ghost_encode_with_files_quality(jpeg_bytes, message, files, passphrase) -> Result<(Vec<u8>, EncodeQuality)>
ghost_capacity(jpeg_image) -> Result<usize>

// Ghost shadow messages (plausible deniability)
ghost_encode_with_shadows(jpeg_bytes, message, files, passphrase, shadows, si) -> Result<Vec<u8>>
ghost_encode_with_shadows_quality(jpeg_bytes, message, files, passphrase, shadows, si) -> Result<(Vec<u8>, EncodeQuality)>
ghost_encode_si_with_shadows(jpeg_bytes, raw_rgb, width, height, message, files, passphrase, shadows) -> Result<Vec<u8>>
ghost_encode_si_with_shadows_quality(jpeg_bytes, raw_rgb, width, height, message, files, passphrase, shadows) -> Result<(Vec<u8>, EncodeQuality)>
ghost_shadow_decode(stego_bytes, passphrase) -> Result<PayloadData>
shadow_capacity(jpeg_bytes) -> Result<usize>
estimate_shadow_capacity(jpeg_image) -> Result<usize>
ghost_capacity_with_shadows(jpeg_bytes, shadows) -> Result<usize>

// Ghost SI-UNIWARD (stealth + side-informed, ~43% more capacity)
ghost_encode_si(jpeg_bytes, raw_rgb, width, height, message, passphrase) -> Result<Vec<u8>>
ghost_encode_si_with_quality(jpeg_bytes, raw_rgb, width, height, message, passphrase) -> Result<(Vec<u8>, EncodeQuality)>
ghost_encode_si_with_files(jpeg_bytes, raw_rgb, width, height, message, files, passphrase) -> Result<Vec<u8>>
ghost_encode_si_with_files_quality(jpeg_bytes, raw_rgb, width, height, message, files, passphrase) -> Result<(Vec<u8>, EncodeQuality)>
ghost_capacity_si(jpeg_image) -> Result<usize>

// Armor mode (robust)
armor_encode(jpeg_bytes, message, passphrase) -> Result<Vec<u8>>
armor_encode_with_quality(jpeg_bytes, message, passphrase) -> Result<(Vec<u8>, EncodeQuality)>
armor_decode(jpeg_bytes, passphrase) -> Result<(PayloadData, DecodeQuality)>
armor_capacity(jpeg_image) -> Result<usize>

// Unified decode (auto-detects mode)
smart_decode(jpeg_bytes, passphrase) -> Result<(PayloadData, DecodeQuality)>

// Cover image optimizer (preprocessing before JPEG compression)
optimize_cover(pixels_rgb, width, height, config) -> Vec<u8>

// Capacity estimation with Brotli compression
compressed_payload_size(text, files) -> usize

// Image dimension validation
validate_encode_dimensions(width, height) -> Result<()>

// Real-time progress tracking
progress::init(total)      // reset and set total steps
progress::advance()        // increment step (capped at total)
progress::finish()         // mark complete (step = total)
progress::get() -> (u32, u32) // read (step, total)
progress::cancel()         // request cancellation
progress::check_cancelled() -> Result<()> // returns Err(Cancelled) if set

Types

  • PayloadData — decoded message text + optional file attachments
  • FileEntry — file attachment (filename + content bytes)
  • ShadowLayer — shadow message for plausible deniability (message + passphrase + optional files)
  • EncodeQuality — encode-time score (0-100), contextual hint key, mode (stealth for Ghost, robustness for Armor)
  • DecodeQuality — signal integrity percentage, RS error count/capacity, fortress flag
  • ArmorCapacityInfo — capacity breakdown by encoding tier (Phase 1/2/3, Fortress)
  • OptimizerConfig — optimizer settings (strength, seed, mode)
  • OptimizerMode — pipeline variant (Ghost, Armor, Fortress)

The SI-UNIWARD functions (ghost_encode_si, ghost_encode_si_with_files) accept additional parameters for the raw uncompressed pixels (raw_rgb: &[u8], pixel_width: u32, pixel_height: u32). The decoder does not need side information — ghost_decode and smart_decode work for both standard and SI-UNIWARD encoded images.

Cargo Features

Feature Description
parallel Enables Rayon parallelism for J-UNIWARD cost computation, STC embedding, and Armor decode sweeps. Recommended for native builds.
wasm WASM bridge support via wasm-bindgen + js-sys.

CLI

A command-line interface is available in the cli/ directory:

# Install
cargo install --path cli

# Encode (Armor mode, default)
phasm encode photo.jpg -m "secret message" -p "passphrase"

# Encode (Ghost mode)
phasm encode photo.jpg --mode ghost -m "secret" -p "pass" -o secret.jpg

# PNG input → auto Deep Cover (SI-UNIWARD)
phasm encode photo.png --mode ghost -m "hello" -p "pass"

# Shadow messages (plausible deniability)
phasm encode photo.jpg --mode ghost -m "real" -p "main" --m2 "decoy" --p2 "shadow"

# File attachments
phasm encode photo.jpg --mode ghost -m "see attached" -p "pass" --attach plans.pdf

# Decode (auto-detects mode)
phasm decode stego.jpg -p "passphrase"

# Extract file attachments
phasm decode stego.jpg -p "pass" --extract ./output/

# Show capacity
phasm capacity photo.jpg

# Pipe message from stdin
echo "hello" | phasm encode photo.jpg -p "pass"

# Machine-readable output
phasm encode photo.jpg -m "hello" -p "pass" --json
phasm decode stego.jpg -p "pass" --quiet

See phasm encode --help, phasm decode --help, phasm capacity --help for all options.

Building & Testing

cargo test -p phasm-core                    # default (single-threaded)
cargo test -p phasm-core --features parallel # with Rayon parallelism

Examples

# Encode and decode a message
cargo run -p phasm-core --example test_encode -- photo.jpg "Hello" "passphrase"
cargo run -p phasm-core --example test_encode -- --decode stego.jpg "passphrase"

# Timing benchmark
cargo run -p phasm-core --example test_timing -- stego.jpg

# Quick decode test
cargo run -p phasm-core --example test_link -- stego.jpg

Architecture

Design Principles

  • Zero C FFI — pure Rust from JPEG parsing to AES encryption, compiles to native and WASM
  • Deterministic — identical output across x86, ARM, and WASM using FDLIBM-based math (no f64::sin/cos — they compile to non-deterministic Math.* in WASM)
  • Memory-efficient — strip-based wavelet computation, compact positions (8 bytes each), 1-bit packed Viterbi back pointers (32× reduction), segmented checkpoint for large images (O(√n) memory), i8-quantized SI-UNIWARD rounding errors (8× smaller than f64), strip-by-strip luma block computation, strategic drop() calls before JPEG output. Supports 200 MP images under ~1 GB peak memory.
  • Short messages — optimized for text payloads under 1 KB
  • Stego output is raw — the JPEG bytes after encoding must be saved/shared without re-encoding

JPEG Codec

The jpeg module is a from-scratch JPEG coefficient codec — zero dependencies beyond std. It parses JPEG files into DCT coefficient grids, allows modification, and writes them back with byte-for-byte round-trip fidelity. Supports both baseline (SOF0) and progressive (SOF2) JPEG input, always outputs baseline.

Original Huffman tables are preserved from the cover image (with fallback to rebuild if needed).

Cryptography

All payloads are encrypted before embedding:

  • Key derivation: Argon2id (RFC 9106) — two tiers:
    • Structural key (deterministic from passphrase + fixed salt): drives coefficient permutation and STC matrix generation
    • Encryption key (passphrase + random salt): AES-256-GCM-SIV (RFC 8452) with nonce-misuse resistance
  • PRNG: ChaCha20 for all key-derived randomness (permutations, spreading vectors, template peaks)
  • Payload compression: Brotli (RFC 7932) for compact payloads; flags byte indicates compression

Ghost Pipeline

  1. Parse JPEG into DCT coefficients
  2. Derive structural key (Argon2id, overlapped with step 3 on multi-core) → permutation seed + STC seed
  3. Compute J-UNIWARD costs strip-by-strip (Daubechies-8 wavelet, 3 subbands, parallel row+column filtering) — positions collected inline, no full CostMap materialized
  4. (SI-UNIWARD only) Modulate costs inline using quantized rounding errors (i8, <2% precision loss): cost *= (1 - 2|error|). Luma blocks computed in strips of 50 block-rows to minimize peak memory.
  5. Permute coefficient order (Fisher-Yates with ChaCha20)
  6. Encrypt payload (AES-256-GCM-SIV) and frame (length + CRC)
  7. Short STC with dynamic w: embed only the actual m message bits (not zero-padded to m_max). The encoder picks w = min(⌊n/m⌋, 10) — for small messages this means 2,500× fewer coefficient modifications compared to fixed w. The decoder brute-forces all w values 1–10 in parallel (rayon::find_map_first); CRC32 in the frame format provides instant validation (~0 false positive rate at 2⁻³²).
  8. (Shadow mode) Assign f32::INFINITY cost to shadow positions → Viterbi routes around them
  9. Embed via STC (h=7) minimizing weighted distortion; SI-UNIWARD uses informed modification direction (toward pre-quantization value)
  10. Write modified coefficients back to JPEG (with progress reporting per MCU row)

STC Viterbi Optimizer

The STC encoder uses a Viterbi-style dynamic programming algorithm to find the minimum-cost modification sequence across a trellis with 2^h = 128 states. Two key memory optimizations make it practical for large images (32MP+ photos, 48MP camera sensors):

1-bit packed back pointers — The standard Viterbi stores one predecessor state (u32) per trellis state per cover step. Since there are exactly 2 candidate predecessors per target state (stego_bit = 0 or 1), only 1 bit is needed. One u128 (16 bytes) stores all 128 states' decisions per step, replacing a Vec<u32> of 128 entries (512 bytes). 32× memory reduction.

The forward pass iterates over target states instead of source states:

for s in 0..num_states {
    let cost_0 = prev_cost[s]       + rho_0;  // stego=0, pred=s
    let cost_1 = prev_cost[s ^ col] + rho_1;  // stego=1, pred=s^col
    if cost_1 < cost_0 {
        curr_cost[s] = cost_1;
        packed_bp |= 1u128 << s;  // 1 bit records the choice
    } else {
        curr_cost[s] = cost_0;
    }
}

Traceback reconstructs predecessors from the single bit:

let bit = ((back_ptr[j] >> s) & 1) as u8;
if bit == 1 { s ^= col; }  // undo XOR to get predecessor

At message-block boundaries (shift steps), the pre-shift state is fully determined from the known message bit — no storage needed:

s = ((s << 1) | message_bit) & (num_states - 1);  // invertible shift

Segmented checkpoint Viterbi — For images with >1M usable positions, even 16 bytes/step can exceed mobile memory (e.g., 100M positions × 16 bytes = 1.6 GB). The segmented approach reduces memory to O(√n):

  • Phase A (forward scan): Run the full Viterbi without storing back pointers. Save cost array checkpoints every K = ⌈√m⌉ message blocks (~1 KB each). Total checkpoint memory: ~1.5 MB for maximum payload.
  • Phase B (segment recomputation): Process segments in reverse order. For each segment, re-run the forward pass from its checkpoint storing back pointers for that segment only, then traceback and free. Peak memory: ~200 KB per segment.

The dispatcher auto-selects the optimal path:

const SEGMENTED_THRESHOLD: usize = 1_000_000;

if n_used <= SEGMENTED_THRESHOLD {
    stc_embed_inline(...)   // single pass, all back_ptr in memory
} else {
    stc_embed_segmented(...) // checkpoint/recompute, O(√n) memory
}

Both paths produce bit-for-bit identical output (verified by equivalence tests). The segmented path trades 2× compute time for O(√n) memory — typically ~3 MB total for any image size.

Image n_used Inline memory Segmented memory
12 MP phone 2M 32 MB 3 MB
32 MB PNG 5M 80 MB 3 MB
48 MP camera 10M 160 MB 3 MB
100 MP medium format 30M 480 MB 3 MB
200 MP flagship 59M 944 MB 3 MB

Strip-Based UNIWARD & Compact Positions

The J-UNIWARD cost function requires wavelet decomposition of the entire decompressed image — three directional subbands (LH, HL, HH) via Daubechies-8 filters. For a 200 MP image, storing the full pixel array + 3 wavelet subbands would need ~3.2 GB.

The strip-based streaming approach eliminates this:

  1. Process the image in horizontal strips of 50 block rows (~400 pixels)
  2. Each strip decompresses its pixel rows (with ±22px padding for the 16-tap wavelet filter boundary), computes row/column-filtered wavelet subbands, and evaluates per-coefficient costs
  3. Embeddable positions are collected inline into a compact Vec<CoeffPos> — no full CostMap is ever materialized
  4. Strip memory is freed before the next strip begins

The CoeffPos type uses compact representation: u32 flat index + f32 cost = 8 bytes per position (down from 16 bytes with usize + f64). The STC accepts f32 costs directly, promoting to f64 only for internal Viterbi accumulation.

Image DctGrid Positions Strip buffers Total peak
12 MP phone 24 MB 48 MB 12 MB 84 MB
48 MP camera 96 MB 190 MB 30 MB 316 MB
100 MP medium format 200 MB 400 MB 50 MB 650 MB
200 MP flagship 400 MB 800 MB 170 MB ~1 GB

Capacity estimation is instantaneous: it counts non-zero AC coefficients directly from the DctGrid (no wavelet computation needed), since J-UNIWARD assigns finite costs to all non-zero coefficients.

Armor Pipeline

  1. Parse JPEG, derive structural keys
  2. Compute stability map (select low-frequency AC coefficients)
  3. Encrypt and frame payload with adaptive RS parity
  4. Embed via STDM with spreading vectors (ChaCha20-derived)
  5. For short messages: activate Fortress (BA-QIM on block averages with Watson masking)
  6. Embed DFT magnitude template for geometric resilience
  7. Decode: three-phase parallel sweep with soft-decision concatenated codes

Progress Reporting

Both encode and decode pipelines report real-time progress via global atomics (progress::advance()). This enables responsive UI feedback on all platforms:

  • Ghost encode: 177 steps — 5 (parse) + 100 (UNIWARD sub-steps) + 50 (STC Viterbi sub-steps) + 2 (permute + key derivation) + 20 (JPEG write MCU rows)
  • Ghost encode with shadows: 277 steps — adds 100 (verification UNIWARD pass) for stego-cost check
  • Ghost decode: 107 steps — 5 (parse) + 100 (UNIWARD) + 2 (STC extraction + decrypt). Dynamic w brute-force runs in parallel.
  • Armor encode: 6 steps (STDM path) or 3 steps (Fortress path, auto-adjusted at runtime)
  • Armor decode: dynamic total based on candidate count (~50 steps). Phase 1 delta sweep parallelized across ~21 candidates.

Cancellation is cooperative: progress::cancel() sets a flag checked at natural loop boundaries via progress::check_cancelled().

FFT

In-house Cooley-Tukey + Bluestein FFT implementation using deterministic twiddle factors (det_sincos()). No external FFT crate — guarantees bit-identical results across all platforms.

Project Structure

src/
  lib.rs            Public API re-exports
  det_math.rs       Deterministic math (FDLIBM sin/cos/atan2/hypot)
  jpeg/
    mod.rs          JpegImage: parse, modify, serialize
    bitio.rs        Bit-level reader/writer with JPEG byte stuffing
    dct.rs          DCT coefficient grids and quantization tables
    error.rs        JPEG parsing errors
    frame.rs        SOF frame info (dimensions, components, subsampling)
    huffman.rs      Huffman coding tables (two-level decode, encode)
    marker.rs       JPEG marker iterator
    pixels.rs       IDCT/DCT for pixel-domain operations (forward DCT, luma extraction)
    scan.rs         Entropy-coded scan reader/writer
    tables.rs       DQT/DHT table parsing
    zigzag.rs       Zigzag scan order mapping
  stego/
    mod.rs          Ghost/Armor encode/decode entry points
    pipeline.rs     Ghost mode pipeline (J-UNIWARD + STC)
    crypto.rs       AES-256-GCM-SIV + Argon2id key derivation
    frame.rs        Payload framing (length, CRC, mode byte, salt, nonce)
    payload.rs      Payload serialization (Brotli, file attachments)
    permute.rs      Fisher-Yates coefficient permutation
    side_info.rs    SI-UNIWARD: rounding errors, cost modulation, direction selection
    shadow.rs       Shadow messages (Y-channel direct LSB + RS ECC, plausible deniability)
    optimizer.rs    Cover image optimizer (texture-adaptive preprocessing, do-no-harm)
    quality.rs      Encode quality scoring (stealth for Ghost, robustness for Armor)
    capacity.rs     Ghost capacity estimation
    progress.rs     Real-time progress tracking (atomics + WASM callback)
    error.rs        StegoError enum
    cost/
      mod.rs        Cost function trait
      uniward.rs    J-UNIWARD (Daubechies-8 wavelet, 3 subbands)
      uerd.rs       UERD cost function (legacy)
    stc/
      mod.rs        Syndrome-Trellis Codes
      embed.rs      STC Viterbi embedding (1-bit packed + segmented checkpoint)
      extract.rs    STC extraction (syndrome computation)
      hhat.rs       H-hat submatrix generation (ChaCha20-derived)
    armor/
      mod.rs        Armor mode re-exports
      pipeline.rs   Armor encode/decode (STDM + Fortress + DFT template)
      embedding.rs  STDM embed/extract with adaptive delta
      selection.rs  Coefficient stability map
      spreading.rs  ChaCha20-derived spreading vectors
      ecc.rs        Reed-Solomon GF(2^8) encoder/decoder
      repetition.rs Repetition coding with soft majority voting
      capacity.rs   Armor capacity estimation
      fortress.rs   BA-QIM block-average embedding + Watson masking
      template.rs   DFT magnitude template (geometric resilience)
      dft_payload.rs DFT ring-based payload embedding
      fft2d.rs      2D FFT (Cooley-Tukey + Bluestein)
      resample.rs   Bilinear resampling for geometric correction
cli/                Command-line interface (phasm binary)
test-vectors/       Synthetic JPEG test images
tests/              Integration tests (round-trip, cross-platform, geometry)
examples/           CLI tools (encode/decode, timing, diagnostics)

Research & Publications

The algorithms in phasm-core are documented in detail on the Phasm blog:

Steganography Fundamentals

Robustness & Error Correction

Geometric Resilience

Plausible Deniability

Implementation

Platform Analysis

License

GPL-3.0-only. See LICENSE.

Third-party dependency licenses are listed in THIRD_PARTY_LICENSES.

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Phasm.app Core Steganography Module

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v0.1.0 Latest
Mar 18, 2026

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