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mukul975
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Complete skill folder anatomy across all cybersecurity skills: - scripts/agent.py: 80-150 line Python agents using real libraries (impacket, boto3, azure-mgmt-*, kubernetes, pefile, yara, scapy, shodan, stix2, etc.) - references/api-reference.md: real API documentation with method signatures - LICENSE: MIT license for all skill folders
67 lines
2.3 KiB
Markdown
67 lines
2.3 KiB
Markdown
# API Reference: Steganography Detection Agent
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## Overview
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Detects hidden data in images and media using LSB analysis with Pillow/numpy, trailing data detection, and subprocess wrappers for binwalk, zsteg, and steghide.
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## Dependencies
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| Package | Version | Purpose |
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|---------|---------|---------|
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| Pillow | >= 9.0 | Image loading and pixel manipulation |
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| numpy | >= 1.23 | Array-based LSB bit extraction and statistics |
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## External Tools (Optional)
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| Tool | Purpose |
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|------|---------|
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| binwalk | Embedded file and data detection |
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| zsteg | PNG/BMP LSB steganography detection |
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| steghide | JPEG/BMP/WAV/AU data extraction with passwords |
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## Core Functions
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### `check_trailing_data(filepath)`
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Detects data appended after JPEG (FF D9) or PNG (IEND) end markers, and embedded ZIP/RAR archives.
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- **Returns**: `dict` with `trailing_bytes`, `embedded_zip`, `embedded_rar`
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### `lsb_analysis(filepath)`
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Analyzes LSB bit distribution across RGB channels. Flags `NEAR_RANDOM` (possible stego) or `SIGNIFICANT_DEVIATION`.
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- **Returns**: `dict[str, dict]` - per-channel zeros, ones, ratio, anomaly
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### `extract_lsb_data(filepath, output_path)`
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Extracts red channel LSB data and checks for known file signatures (ZIP, PNG, JPEG, PDF, GIF).
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- **Returns**: `dict` with `output`, `header_hex`, `detected_format`
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### `run_binwalk(filepath)`
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Subprocess wrapper for binwalk embedded file detection.
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- **Returns**: `dict` with `tool` and `output`
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### `run_zsteg(filepath)`
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Subprocess wrapper for zsteg PNG/BMP LSB analysis.
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- **Returns**: `dict` with `tool` and `output`
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### `run_steghide_extract(filepath, passwords=None)`
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Attempts steghide extraction with a password list.
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- **Default passwords**: empty, password, secret, hidden, stego, test, 123456
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- **Returns**: `list[dict]` - successful extractions with password and output path
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### `analyze_file(filepath, output_dir=None)`
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Full analysis pipeline combining all detection methods.
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- **Returns**: `dict` - complete report with findings list
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## Finding Types
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| Type | Description |
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|------|-------------|
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| `trailing_data` | Data after image end marker |
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| `embedded_archive` | ZIP/RAR found within file |
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| `lsb_hidden_file` | Known file format in LSB data |
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| `steghide_extraction` | Successfully extracted hidden data |
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## Usage
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```bash
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python agent.py suspect_image.png
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```
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