cyberkaida/reverse-engineering-assistant/binary-triage

Claude Code and agent skill by cyberkaida/reverse-engineering-assistant

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Performs initial binary triage by surveying memory layout, strings, imports/exports, and functions to quickly understand what a binary does and identify suspicious behavior. Use when first examining a binary, when user asks to triage/survey/analyze a program, or wants an overview before deeper reverse engineering.

Install

npx vskill@latest install cyberkaida/reverse-engineering-assistant/binary-triage

SKILL.md

Binary Triage

Instructions

We are triaging a binary to quickly understand what it does. This is an initial survey, not deep analysis. Our goal is to:

  1. Identify key components and behaviors
  2. Flag suspicious or interesting areas
  3. Create a task list of next steps for deeper investigation

Binary triage with ReVa

Follow this systematic workflow using ReVa's MCP tools:

1. Identify the Program
  • Use get-current-program to see the active program
  • Or use list-project-files to see available programs in the project
  • Note the programPath (e.g., "/Hatchery.exe") for use in subsequent tools
2. Survey Memory Layout
  • Use get-memory-blocks to understand the binary structure
  • Examine key sections:
  • .text - executable code
  • .data - initialized data
  • .rodata - read-only data (strings, constants)
  • .bss - uninitialized data
  • Flag unusual characteristics:
  • Unusually large sections
  • Packed/encrypted sections
  • Executable data sections
  • Writable code sections
3. Survey Strings
  • Use get-strings-count to see total string count
  • Use get-strings with pagination (100-200 strings at a time)
  • Look for indicators of functionality or malicious behavior:
  • Network: URLs, IP addresses, domain names, API endpoints
  • File System: File paths, registry keys, configuration files
  • APIs: Function names, library references
  • Messages: Error messages, debug strings, log messages
  • Suspicious Keywords: admin, password, credential, token, crypto, encrypt, decrypt, download, execute, inject, shellcode, payload
4. Survey Symbols and Imports
  • Use get-symbols-count with includeExternal=true to count imports
  • Use get-symbols with includeExternal=true and filterDefaultNames=true
  • Focus on external symbols (imports from libraries)
  • Flag interesting/suspicious imports by category:
  • Network APIs: connect, send, recv, WSAStartup, getaddrinfo, curl_*, socket
  • File I/O: CreateFile, WriteFile, ReadFile, fopen, fwrite, fread
  • Process Manipulation: CreateProcess, exec, fork, system, WinExec, ShellExecute
  • Memory Operations: VirtualAlloc, VirtualProtect, mmap, mprotect
  • Crypto: CryptEncrypt, CryptDecrypt, EVP_, AES_, bcrypt, RC4
  • Anti-Analysis: IsDebuggerPresent, CheckRemoteDebuggerPresent, ptrace
  • Registry: RegOpenKey, RegSetValue, RegQueryValue
  • Note the ratio of imports to total symbols (heavy import usage may indicate reliance on libraries)
5. Survey Functions
  • Use get-function-count with filterDefaultNames=true to count named functions
  • Use get-function-count with filterDefaultNames=false to count all functions
  • Calculate ratio of named vs unnamed functions (high unnamed ratio = stripped binary)
  • Use get-functions with filterDefaultNames=true to list named functions
  • Identify key functions:
  • Entry points: entry, start, _start
  • Main functions: main, WinMain, DllMain, _main
  • Suspicious names: If not stripped, look for revealing function names
6. Cross-Reference Analysis for Key Findings
  • For interesting strings found in Step 3:
  • Use find-cross-references with direction="to" and includeContext=true
  • Identify which functions reference suspicious strings
  • For suspicious imports found in Step 4:
  • Use find-cross-references with direction="to" and includeContext=true
  • Identify which functions call suspicious APIs
  • This helps prioritize which functions need detailed examination
7. Selective Initial Decompilation
  • Use get-decompilation on entry point or main function
  • Set limit=30 to get ~30 lines initially
  • Set includeIncomingReferences=true to see callers
  • Set includeReferenceContext=true for context snippets
  • Use get-decompilation on 1-2 suspicious functions identified in Step 6
  • Set limit=20-30 for quick overview
  • Look for high-level patterns:
  • Loops (encryption/decryption routines)
  • Network operations
  • File operations
  • Process creation
  • Suspicious control flow (obfuscation indicators)
  • Do not do deep analysis yet - this is just to understand general behavior
8. Document Findings and Create Task List
  • Use the TodoWrite tool to create an actionable task list with items like:
  • "Investigate string 'http://malicious-c2.com' (referenced at 0x00401234)"
  • "Decompile function sub_401000 (calls VirtualAlloc + memcpy + CreateThread)"
  • "Analyze crypto usage in function encrypt_payload (uses CryptEncrypt)"
  • "Trace anti-debugging checks (IsDebuggerPresent at 0x00402000)"
  • "Examine packed section .UPX0 for unpacking routine"
  • Each todo should be:
  • Specific (include addresses, function names, strings)
  • Actionable (what needs to be investigated)
  • Prioritized (most suspicious first)

Output Format

Present triage findings to the user in this structured format:

Program Overview
  • Name: [Program name from programPath]
  • Type: [Executable type - PE, ELF, Mach-O, etc.]
  • Platform: [Windows, Linux, macOS, etc.]
Memory Layout
  • Total Size: [Size in bytes/KB/MB]
  • Key Sections: [List main sections with sizes and permissions]
  • Unusual Characteristics: [Any packed/encrypted/suspicious sections]
String Analysis
  • Total Strings: [Count from get-strings-count]
  • Notable Findings: [Bullet list of interesting strings with context]
  • Suspicious Indicators: [URLs, IPs, suspicious keywords found]
Import Analysis
  • Total Symbols: [Count from get-symbols-count]
  • External Imports: [Count of external symbols]
  • Key Libraries: [Main libraries imported]
  • Suspicious APIs: [Categorized list of concerning imports]
Function Analysis
  • Total Functions: [Count with filterDefaultNames=false]
  • Named Functions: [Count with filterDefaultNames=true]
  • Stripped Status: [Yes/No based on ratio]
  • Entry Point: [Address and name]
  • Main Function: [Address and name]
  • Key Functions: [List of important functions identified]
Suspicious Indicators

[Bulleted list of red flags discovered, prioritized by severity]

Recommended Next Steps

[Present the task list created in Step 8]

  • Each item should be specific and actionable
  • Prioritize by severity/importance
  • Include addresses, function names, and context

Important Notes

  • Speed over depth: This is triage, not full analysis. Move quickly through steps.
  • Use pagination: Don't request thousands of strings/functions at once. Use chunks of 100-200.
  • Focus on anomalies: Flag things that are unusual, suspicious, or interesting.
  • Context is key: When using cross-references, enable includeContext=true for code snippets.
  • Create actionable todos: Each next step should be specific enough for another agent to execute.
  • Be systematic: Follow all 8 steps in order for comprehensive coverage.

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
731
Repository forks
63
7-day trend score
33

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 7 Apr 2026, 6 months ago.

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