reverse-skills-max: initial public release (restored, redacted, hardened)
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Apache License 2.0 — see the repository root LICENSE file for the full text.
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Copyright the AnalystAIPack contributors.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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---
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name: analyzing-ransomware-encryption-behavior
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description: 'Analyzes how a ransomware sample encrypts files: identifying the crypto scheme
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(symmetric/asymmetric/hybrid), key handling, file targeting and extension/marker changes,
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shadow-copy deletion, and ransom-note artifacts. Activates for requests to analyze
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ransomware encryption, assess decryptability, or study ransomware behavior.'
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domain: cybersecurity
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subdomain: malware-analysis
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tags:
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- malware
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- ransomware
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- cryptography
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- encryption
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- file-marker
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- impact
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version: 1.0.0
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author: analyst-ai-pack
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license: Apache-2.0
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mitre_attack:
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- T1486
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- T1490
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- T1083
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- T1027
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d3fend:
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- D3-FA
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- D3-DA
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references:
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- 'No More Ransom project — https://www.nomoreransom.org/'
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- 'NIST cryptographic standards (AES/RSA) — https://csrc.nist.gov/'
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---
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# Analyzing Ransomware Encryption Behavior
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## When to Use
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- You need to understand how a ransomware sample encrypts data and whether recovery without
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the key is feasible.
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- You are documenting file targeting, markers, and the ransom workflow for an IR report.
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- You want to identify the crypto primitives to assess decryptability and detection points.
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**Do not use** this to attempt key recovery on production data without backups; analyze in the
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lab on disposable test files only.
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## Prerequisites
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- Isolated lab with disposable test files of varied types/sizes.
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- Static/RE tools (see the Ghidra and crypto-identification skills) and the dynamic-analysis
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setup.
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- A clean snapshot to revert.
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## Safety & Handling
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- Detonate only against **throwaway** files in the isolated victim VM; never real data.
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- Treat the sample and any dropped components as live; revert after each run.
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## Workflow
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### Step 1: Identify the crypto scheme statically
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Locate crypto constants and APIs to classify the scheme:
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```text
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Symmetric only (AES/ChaCha/RC4) -> key may be derivable/recoverable if mishandled
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Asymmetric (RSA/ECC) wrapping -> per-file symmetric key wrapped with attacker pubkey
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Hybrid (typical) -> AES per file, RSA-wrapped key in the encrypted file/footer
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```
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Look for AES S-boxes, ChaCha constants ("expand 32-byte k"), and `CryptImportKey`/`BCrypt*`.
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### Step 2: Trace key generation and handling
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Determine where the symmetric key comes from (CSPRNG vs weak source), whether it is stored,
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and how it is protected. Weak/reused keys or keys left in memory are recovery opportunities.
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### Step 3: Map file targeting
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Identify which directories/extensions are targeted or skipped (allowlist of system paths),
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size thresholds, and partial-vs-full encryption (many encrypt only the first N bytes/blocks
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for speed).
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### Step 4: Capture markers and metadata
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Most families append an extension, write a per-file footer/magic marker, and store the
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wrapped key or IV there. The script fingerprints before/after test files to extract markers.
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```bash
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python scripts/analyst.py compare plain/ encrypted/
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```
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### Step 5: Document recovery-relevant facts
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Note shadow-copy/backup deletion (`vssadmin delete shadows`), the ransom note, and any
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cryptographic mistakes that affect decryptability.
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## Validation
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- The identified scheme matches observed file changes (e.g. hybrid → high-entropy body + a
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fixed-size footer).
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- File markers/extensions are consistent across encrypted test files.
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- Shadow-copy deletion and note-drop are confirmed dynamically.
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## Pitfalls
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- Assuming decryptability from the algorithm name; correct AES/RSA usage is not recoverable.
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Recovery hinges on implementation flaws or leaked keys.
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- Missing partial-encryption schemes, leading to wrong impact assessment.
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- Running against real files instead of disposable test data.
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## References
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- See [`references/api-reference.md`](references/api-reference.md) for the file-marker
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comparison tool.
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- No More Ransom and NIST crypto standards (linked in frontmatter).
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# API Reference: Analyzing Ransomware Encryption Behavior
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## Overview
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`scripts/analyst.py` compares original test files against their encrypted counterparts to
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extract the appended extension, measure entropy change, and recover a common trailing footer
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(where families often store a wrapped key or IV). It runs on disposable test files only.
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## Dependencies
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| Package | Version | Purpose |
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|---------|---------|---------|
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| (stdlib) | — | Entropy, file IO |
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## External tools
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| Tool | Purpose |
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|------|---------|
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| Ghidra / radare2 | Identify crypto routines and key handling |
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| Detect-It-Easy / capa | Crypto-constant detection |
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## Core functions
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### `compare(plain_dir, enc_dir)`
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Returns added extensions, a common encrypted footer, per-file entropy, size deltas, and an
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encryption-coverage estimate (full vs partial).
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### `_common_suffix(blobs)`
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Finds the longest shared trailing bytes across encrypted files (candidate footer/marker).
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## Usage
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```bash
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python scripts/analyst.py compare ./plain ./encrypted
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```
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## Sources
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- No More Ransom project — https://www.nomoreransom.org/
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- NIST cryptographic standards (AES, RSA) — https://csrc.nist.gov/
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- Hybrid-encryption ransomware design (per-file AES + RSA-wrapped key), widely documented
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#!/usr/bin/env python3
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"""Compare plaintext vs ransomware-encrypted test files to extract markers and assess scheme.
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Given a directory of original test files and a directory of their encrypted counterparts, it
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reports added extensions, entropy change, and any common trailing footer/magic (often where a
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wrapped key or IV is stored). Operates on inert test files only.
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"""
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from __future__ import annotations
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import argparse
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import json
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import math
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import sys
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from collections import Counter
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from pathlib import Path
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def entropy(data: bytes) -> float:
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if not data:
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return 0.0
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counts = Counter(data)
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n = len(data)
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return -sum((c / n) * math.log2(c / n) for c in counts.values())
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def _common_suffix(blobs: list[bytes], max_len: int = 512) -> bytes:
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if not blobs:
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return b""
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shortest = min(len(b) for b in blobs)
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limit = min(shortest, max_len)
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suffix = bytearray()
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for i in range(1, limit + 1):
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col = {b[-i] for b in blobs}
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if len(col) == 1:
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suffix.insert(0, col.pop())
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else:
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break
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return bytes(suffix)
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def compare(plain_dir: str, enc_dir: str) -> dict:
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plain = {p.stem: p for p in Path(plain_dir).iterdir() if p.is_file()}
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enc = [p for p in Path(enc_dir).iterdir() if p.is_file()]
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added_ext = sorted({"".join(p.suffixes) for p in enc})
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enc_blobs = [p.read_bytes() for p in enc]
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footer = _common_suffix(enc_blobs)
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per_file = []
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for p in enc:
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base = p.name
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# strip a possible appended extension to match the plaintext stem
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stem = p.stem
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orig = plain.get(stem)
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row = {
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"encrypted": base,
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"encrypted_entropy": round(entropy(p.read_bytes()), 3),
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}
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if orig:
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row["original"] = orig.name
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row["original_entropy"] = round(entropy(orig.read_bytes()), 3)
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row["size_delta"] = p.stat().st_size - orig.stat().st_size
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per_file.append(row)
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likely_full = all(r.get("encrypted_entropy", 0) > 7.5 for r in per_file)
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return {
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"added_extensions": added_ext,
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"common_footer_len": len(footer),
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"common_footer_hex": footer.hex(),
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"encryption_coverage": "full/high-entropy" if likely_full else "partial/mixed",
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"files": per_file,
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}
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def main(argv: list[str] | None = None) -> int:
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parser = argparse.ArgumentParser(description="Compare plain vs encrypted test files")
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sub = parser.add_subparsers(dest="cmd", required=True)
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p = sub.add_parser("compare")
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p.add_argument("plain_dir")
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p.add_argument("enc_dir")
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args = parser.parse_args(argv)
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print(json.dumps(compare(args.plain_dir, args.enc_dir), indent=2))
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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