Agent skill

Analyzing Ransomware Encryption Mechanisms

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Analyzes encryption algorithms, key management, and file encryption routines used by ransomware families to assess decryption feasibility, identify implementation weaknesses, and support recovery…

Apache-2.0Auto-check passedSecurity

Install Analyzing Ransomware Encryption Mechanisms

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-ransomware-encryption-mechanisms -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-ransomware-encryption-mechanisms --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analyzing-ransomware-encryption-mechanisms .claude/skills/analyzing-ransomware-encryption-mechanisms && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
analyzing-ransomware-encryption-mechanisms
GitHub stars
34k
Token cost
~3.5k tokens
SKILL.md length
625 words
Files
4 (incl. scripts, references)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Analyzes encryption algorithms, key management, and file encryption routines used by ransomware families to assess decryption feasibility, identify implementation weaknesses, and support recovery…

  • Works in 6 steps: Identify the Encryption Algorithm → Analyze Key Generation and Management → Examine File Encryption Routine → …
  • Tasks that involve Cryptography
  • SKILL.md covers When to Use, Prerequisites, Workflow and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder; reaches nomoreransom.org

What it does

Analyzing Ransomware Encryption Mechanisms is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Analyzes encryption algorithms, key management, and file encryption routines used by ransomware families to assess decryption feasibility, identify implementation weaknesses, and support recovery efforts. Covers AES, RSA, ChaCha20, and hybrid encryption schemes. Activates for requests involving ransomware cryptanalysis, encryption analysis, key recovery assessment, or ransomware decryption feasibility.

Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).

It sits in Security, covering Cryptography. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Cryptography

Example prompts

  • “Use the analyzing-ransomware-encryption-mechanisms skill to analyz encryption algorithms, key management, and file encryption routines used by…”
  • “/analyzing-ransomware-encryption-mechanisms”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Identify the Encryption Algorithm
  2. Analyze Key Generation and Management
  3. Examine File Encryption Routine
  4. Check for Cryptographic Weaknesses
  5. Attempt Key Recovery
  6. Document Encryption Analysis

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • nomoreransom.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Analyzing Ransomware Encryption Mechanisms loads about 3.5k tokens when it runs, and up to ~4.5k if it reads all its reference files. Until then it costs about 112 tokens; SKILL.md has 625 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~112
When it runs · the whole SKILL.md, loaded when a task matches
~3.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 625 words, ~3,512 tokens.

Download SKILL.mdSave it as .claude/skills/analyzing-ransomware-encryption-mechanisms/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
analyzing-ransomware-encryption-mechanisms
description
Analyzes encryption algorithms, key management, and file encryption routines used by ransomware families to assess decryption feasibility, identify implementation weaknesses, and support recovery efforts. Covers AES, RSA, ChaCha20, and hybrid encryption schemes. Activates for requests involving ransomware cryptanalysis, encryption analysis, key recovery assessment, or ransomware decryption feasibility.
domain
cybersecurity
subdomain
malware-analysis
tags
malware, ransomware, encryption, cryptanalysis, reverse-engineering
version
1.0.0
author
mahipal
license
Apache-2.0
nist_csf
DE.AE-02, RS.AN-03, ID.RA-01, DE.CM-01
mitre_attack
T1486, T1573.001, T1573.002, T1027
mitre_f3.version
1.1
mitre_f3.tactics
monetization, positioning

Analyzing Ransomware Encryption Mechanisms

When to Use

  • A ransomware infection has occurred and recovery requires understanding the encryption scheme used
  • Assessing whether decryption is possible without paying the ransom (implementation flaws, known decryptors)
  • Reverse engineering ransomware to identify the encryption algorithm, key derivation, and key storage mechanism
  • Developing a decryptor tool when a weakness in the ransomware's cryptographic implementation is identified
  • Classifying a ransomware sample by its encryption approach to attribute it to a known family

Do not use for production data recovery operations without first verifying the decryption method on test copies of encrypted files.

Prerequisites

  • Ghidra or IDA Pro for reverse engineering the ransomware binary
  • Python 3.8+ with pycryptodome library for testing encryption/decryption routines
  • Sample encrypted files and their corresponding plaintext originals (known-plaintext pairs)
  • Access to the ransomware binary (unpacked if applicable)
  • Familiarity with symmetric (AES, ChaCha20) and asymmetric (RSA) cryptographic algorithms
  • NoMoreRansom.org database for checking existing free decryptors

Workflow

Step 1: Identify the Encryption Algorithm

Determine which cryptographic algorithm the ransomware uses:

python
# Check for Windows Crypto API usage in imports
import pefile

pe = pefile.PE("ransomware.exe")

crypto_apis = {
    "CryptAcquireContextA": "Windows CryptoAPI",
    "CryptAcquireContextW": "Windows CryptoAPI",
    "CryptGenKey": "Windows CryptoAPI key generation",
    "CryptEncrypt": "Windows CryptoAPI encryption",
    "CryptImportKey": "Windows CryptoAPI key import",
    "BCryptOpenAlgorithmProvider": "Windows CNG (modern crypto)",
    "BCryptEncrypt": "Windows CNG encryption",
    "BCryptGenerateKeyPair": "Windows CNG asymmetric key gen",
}

print("Crypto API Imports:")
for entry in pe.DIRECTORY_ENTRY_IMPORT:
    for imp in entry.imports:
        if imp.name and imp.name.decode() in crypto_apis:
            print(f"  {entry.dll.decode()} -> {imp.name.decode()}: {crypto_apis[imp.name.decode()]}")
Common Ransomware Encryption Schemes:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
AES-256-CBC + RSA-2048:    Most common hybrid scheme (LockBit, REvil, Conti)
AES-256-CTR + RSA-4096:    Stream cipher mode variant (BlackCat/ALPHV)
ChaCha20 + RSA-4096:       Modern stream cipher (Hive, Royal)
Salsa20 + ECDH:            Curve25519 key exchange (Babuk)
AES-128-ECB:               Weak mode - potential decryption via known-plaintext
XOR-only:                  Trivial encryption - always recoverable
Custom algorithm:          Often contains implementation flaws
Step 2: Analyze Key Generation and Management

Reverse engineer how encryption keys are generated and stored:

Key Management Patterns in Ransomware:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
1. STRONG (no recovery possible without key):
   - Per-file AES key generated with CryptGenRandom
   - AES key encrypted with embedded RSA public key
   - Encrypted key appended to each file or stored separately
   - RSA private key held only by attacker's C2 server

2. WEAK (potential recovery):
   - AES key derived from predictable seed (timestamp, PID)
   - Same AES key used for all files (single key compromise = full recovery)
   - Key transmitted to C2 before encryption starts (PCAP may contain key)
   - XOR with short repeating key (brute-forceable)
   - PRNG seeded with GetTickCount or time() (limited keyspace)

3. FLAWED IMPLEMENTATION:
   - ECB mode (preserves plaintext patterns)
   - Initialization vector (IV) reuse across files
   - Key stored in plaintext in memory (recoverable from memory dump)
   - Partial encryption (only first N bytes encrypted)
Step 3: Examine File Encryption Routine

Reverse engineer the file processing logic:

c
// Typical ransomware file encryption flow (decompiled pseudo-code from Ghidra):

void encrypt_file(char *filepath) {
    // 1. Check file extension against target list
    if (!is_target_extension(filepath)) return;

    // 2. Generate per-file AES key (32 bytes for AES-256)
    BYTE aes_key[32];
    CryptGenRandom(hProv, 32, aes_key);

    // 3. Generate random IV (16 bytes)
    BYTE iv[16];
    CryptGenRandom(hProv, 16, iv);

    // 4. Read file contents
    HANDLE hFile = CreateFile(filepath, GENERIC_READ, ...);
    BYTE *plaintext = read_entire_file(hFile);

    // 5. Encrypt with AES-256-CBC
    aes_cbc_encrypt(plaintext, file_size, aes_key, iv);

    // 6. Encrypt AES key with RSA public key
    BYTE encrypted_key[256];  // RSA-2048 output
    rsa_encrypt(aes_key, 32, rsa_pubkey, encrypted_key);

    // 7. Write: encrypted_data + encrypted_key + IV to file
    write_file(filepath, encrypted_data, encrypted_key, iv);

    // 8. Rename file with ransomware extension
    rename_file(filepath, strcat(filepath, ".locked"));
}
Step 4: Check for Cryptographic Weaknesses

Test the implementation for exploitable flaws:

python
from Crypto.Cipher import AES
import os
import struct

# Test 1: Check if same key is used for multiple files
# Compare encrypted versions of known files
def check_key_reuse(file1_enc, file2_enc):
    with open(file1_enc, "rb") as f:
        data1 = f.read()
    with open(file2_enc, "rb") as f:
        data2 = f.read()

    # Extract IVs (location depends on ransomware family)
    # If IVs are same and files share encrypted blocks -> same key
    iv1 = data1[-16:]  # Example: IV at end
    iv2 = data2[-16:]
    if iv1 == iv2:
        print("[!] Same IV detected - key reuse likely")

# Test 2: Check for predictable key derivation
# If key is derived from timestamp, iterate possible values
def brute_force_timestamp_key(encrypted_file, known_header, timestamp_range):
    with open(encrypted_file, "rb") as f:
        encrypted_data = f.read()

    for ts in timestamp_range:
        # Derive key the same way ransomware does
        import hashlib
        key = hashlib.sha256(str(ts).encode()).digest()
        iv = encrypted_data[-16:]
        cipher = AES.new(key, AES.MODE_CBC, iv)
        decrypted = cipher.decrypt(encrypted_data[:16])

        if decrypted[:len(known_header)] == known_header:
            print(f"[!] Key found! Timestamp: {ts}")
            return key

    return None

# Test 3: Check for ECB mode (pattern preservation)
def check_ecb_mode(encrypted_file):
    with open(encrypted_file, "rb") as f:
        data = f.read()
    # ECB produces identical ciphertext for identical plaintext blocks
    blocks = [data[i:i+16] for i in range(0, len(data), 16)]
    unique = len(set(blocks))
    total = len(blocks)
    if unique < total * 0.95:
        print(f"[!] ECB mode likely: {total-unique} duplicate blocks out of {total}")
Step 5: Attempt Key Recovery

Use identified weaknesses for key recovery:

python
# Recovery Method 1: Extract key from memory dump
# Volatility plugin to scan for AES key schedules
# vol3 -f memory.dmp windows.yarascan --yara-rule "aes_key_schedule"

# Recovery Method 2: Known-plaintext attack (weak algorithms)
def xor_key_recovery(encrypted_file, known_plaintext):
    """Recover XOR key from known plaintext-ciphertext pair"""
    with open(encrypted_file, "rb") as f:
        ciphertext = f.read()

    key = bytes(c ^ p for c, p in zip(ciphertext, known_plaintext))
    # Find repeating key length
    for key_len in range(1, 256):
        candidate = key[:key_len]
        if all(key[i] == candidate[i % key_len] for i in range(min(len(key), key_len * 4))):
            print(f"XOR key (length {key_len}): {candidate.hex()}")
            return candidate
    return None

# Recovery Method 3: Check NoMoreRansom for existing decryptors
# https://www.nomoreransom.org/en/decryption-tools.html
Step 6: Document Encryption Analysis

Compile findings into a structured report:

Analysis should document:
- Algorithm identified (AES, RSA, ChaCha20, custom)
- Key size and mode of operation (CBC, CTR, ECB, GCM)
- Key generation method (CSPRNG, predictable seed, static key)
- Key storage location (appended to file, registry, C2 transmission)
- File modification pattern (full encryption, partial, header-only)
- Targeted file extensions
- Ransom note format and payment infrastructure
- Decryption feasibility assessment (possible/impossible/partial)
- Recommended recovery approach

Key Concepts

TermDefinition
Hybrid EncryptionCombining symmetric (AES) for fast file encryption with asymmetric (RSA) for secure key wrapping; the standard ransomware approach
Key WrappingEncrypting the per-file symmetric key with the attacker's RSA public key so only the attacker's private key can decrypt it
ECB ModeElectronic Codebook mode encrypts each block independently; preserves patterns in plaintext, a critical weakness enabling partial recovery
Known-Plaintext AttackUsing a known original file and its encrypted version to derive the encryption key; effective against XOR and weak stream ciphers
Key ScheduleThe expanded form of an AES key in memory; scannable in memory dumps to recover encryption keys before they are erased
CSPRNGCryptographically Secure Pseudo-Random Number Generator; ransomware using CryptGenRandom produces unpredictable keys
Partial EncryptionSome ransomware only encrypts the first N bytes or every Nth block for speed; unencrypted portions may aid recovery
Show full SKILL.md (254 more words)Show less

Tools & Systems

  • Ghidra: Reverse engineering suite for analyzing ransomware encryption routines at the assembly level
  • PyCryptodome: Python cryptographic library for implementing and testing decryption routines
  • NoMoreRansom.org: Free decryption tool repository maintained by Europol and security vendors for known ransomware families
  • Volatility: Memory forensics framework for extracting encryption keys from RAM dumps of infected systems
  • CryptoTester: Tool for identifying cryptographic algorithms based on constants and code patterns

Common Scenarios

Scenario: Assessing Decryption Feasibility for a Ransomware Incident

Context: An organization is hit with ransomware encrypting file servers. Management needs to know if decryption is possible without paying the ransom before making a recovery decision.

Approach:

  1. Identify the ransomware family from ransom note, file extension, and sample hash (check ID Ransomware)
  2. Check NoMoreRansom.org for existing free decryptors for this family
  3. Reverse engineer the encryption routine in Ghidra to identify the algorithm and key management
  4. Test for implementation weaknesses (key reuse, predictable seeds, ECB mode)
  5. Check if PCAP from the incident captured the key transmission to C2 (if key was sent before encryption)
  6. Scan memory dumps from affected machines for AES key schedules in RAM
  7. Report findings: decryption possible/impossible with specific technical justification

Pitfalls:

  • Testing decryption methods on the only copy of encrypted files (always work on copies)
  • Assuming all files use the same key without verifying (some ransomware uses per-file keys)
  • Not checking for volume shadow copies (vssadmin) which ransomware may have failed to delete
  • Confusing the file encryption algorithm with the key wrapping algorithm in reports

Output Format

RANSOMWARE ENCRYPTION ANALYSIS
================================
Sample:           lockbit3.exe
Family:           LockBit 3.0 / LockBit Black
SHA-256:          abc123def456...

ENCRYPTION SCHEME
File Cipher:      AES-256-CTR (per-file unique key)
Key Wrapping:     RSA-2048 (public key embedded in binary)
Key Generation:   CryptGenRandom (CSPRNG - unpredictable)
IV Generation:    Random 16 bytes per file
File Structure:   [encrypted_data][rsa_encrypted_key(256B)][iv(16B)][magic(8B)]

TARGETED EXTENSIONS
Total:            412 extensions targeted
Categories:       Documents (.doc, .xls, .pdf), Databases (.sql, .mdb),
                  Archives (.zip, .7z), Source code (.py, .java, .cs)
Excluded:         .exe, .dll, .sys, .lnk (system files preserved)

IMPLEMENTATION ANALYSIS
Key Strength:     STRONG - per-file random keys, no reuse
Mode Security:    STRONG - CTR mode with unique nonces
Key Storage:      RSA-encrypted key appended to each file
Shadow Copies:    Deleted via vssadmin and WMI

DECRYPTION FEASIBILITY
Without Key:      NOT POSSIBLE
  - No implementation flaws identified
  - RSA-2048 key wrapping prevents brute force
  - CSPRNG prevents key prediction
  - No existing free decryptor available

RECOVERY OPTIONS
1. Restore from offline backups (recommended)
2. Check for volume shadow copies (low probability - ransomware deletes them)
3. Memory forensics if machine was not rebooted (key may persist in RAM)
4. Negotiate with attacker (last resort - no guarantee of decryption)

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in skills/analyzing-ransomware-encryption-mechanisms of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • references/api-reference.md
  • scripts/agent.py

Open the folder on GitHubat commit 54a7988

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Categories

Questions about Analyzing Ransomware Encryption Mechanisms

What does Analyzing Ransomware Encryption Mechanisms do?

Analyzes encryption algorithms, key management, and file encryption routines used by ransomware families to assess decryption feasibility, identify implementation weaknesses, and support recovery…. Analyzing Ransomware Encryption Mechanisms is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Analyzes encryption algorithms, key management, and file encryption routines used by ransomware families to assess decryption feasibility, identify implementation weaknesses, and support recovery efforts.

When should I use Analyzing Ransomware Encryption Mechanisms?

Analyzing Ransomware Encryption Mechanisms fits situations like: tasks that involve Cryptography.

How do I install Analyzing Ransomware Encryption Mechanisms in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-ransomware-encryption-mechanisms -a claude-code`. Or copy the skill folder (skills/analyzing-ransomware-encryption-mechanisms in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/analyzing-ransomware-encryption-mechanisms in your project. Claude Code loads it when a task matches its description.

How do I install Analyzing Ransomware Encryption Mechanisms in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-ransomware-encryption-mechanisms -a codex`. Or copy the skill folder (skills/analyzing-ransomware-encryption-mechanisms in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/analyzing-ransomware-encryption-mechanisms in your project. Codex loads it when a task matches its description.

Can I use Analyzing Ransomware Encryption Mechanisms in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-ransomware-encryption-mechanisms -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analyzing-ransomware-encryption-mechanisms, .gemini/skills/analyzing-ransomware-encryption-mechanisms, .github/skills/analyzing-ransomware-encryption-mechanisms and .opencode/skills/analyzing-ransomware-encryption-mechanisms in your project.

What does Analyzing Ransomware Encryption Mechanisms need to run?

Going by SKILL.md and its folder, Analyzing Ransomware Encryption Mechanisms needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Analyzing Ransomware Encryption Mechanisms access the network?

SKILL.md names 1 domain. In commands or code: nomoreransom.org; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Analyzing Ransomware Encryption Mechanisms safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Analyzing Ransomware Encryption Mechanisms use?

Analyzing Ransomware Encryption Mechanisms is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Analyzing Ransomware Encryption Mechanisms use?

About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1k tokens, read only when the agent opens those files.

What are the alternatives to Analyzing Ransomware Encryption Mechanisms?

Skills that share tags, products or a category with Analyzing Ransomware Encryption Mechanisms: Bom Explore (cdxgen/cdxgen, 1.1k stars), Crypto Analysis (hypnguyen1209/offensive-claude, 388 stars), Security Review (valory-xyz/open-autonomy, 129 stars) and Hashcat Password Recovery Workflow (AgentSecOps/SecOpsAgentKit, 220 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Analyzing Ransomware Encryption Mechanisms?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.