About binary-triage
binary-triage is a skill for quickly surveying a binary before deeper analysis. It helps analysts identify its structure and notable behaviors, flag areas of interest, and produce prioritized, actionable follow-up tasks.
Key features
- 01Memory-section survey
- 02String and import inspection
- 03Function and cross-reference review
- 04Selective initial decompilation
- 05Prioritized follow-up task list
Use cases
- 01Preparing an initial malware binary assessment
- 02Finding suspicious APIs or strings for investigation
- 03Planning deeper analysis of a packed or stripped binary
MCP support
The skill uses ReVa's MCP tools to inspect program files, memory, strings, symbols, functions, references, and decompilation.
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ cyberkaida/ reverse-engineering-assistant --skill binary-triageAfter installing, type/binary-triagein Claude Code to confirm it loaded.
Details
From the project READMEBinary 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:
- Identify key components and behaviors
- Flag suspicious or interesting areas
- 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-programto see the active program - Or use
list-project-filesto 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-blocksto 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-countto see total string count - Use
get-stringswith 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-countwithincludeExternal=trueto count imports - Use
get-symbolswithincludeExternal=trueandfilterDefaultNames=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-countwithfilterDefaultNames=trueto count named functions - Use
get-function-countwithfilterDefaultNames=falseto count all functions - Calculate ratio of named vs unnamed functions (high unnamed ratio = stripped binary)
- Use
get-functionswithfilterDefaultNames=trueto 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
- Entry points:
6. Cross-Reference Analysis for Key Findings
- For interesting strings found in Step 3:
- Use
find-cross-referenceswithdirection="to"andincludeContext=true - Identify which functions reference suspicious strings
- Use
- For suspicious imports found in Step 4:
- Use
find-cross-referenceswithdirection="to"andincludeContext=true - Identify which functions call suspicious APIs
- Use
- This helps prioritize which functions need detailed examination
7. Selective Initial Decompilation
- Use
get-decompilationon entry point or main function- Set
limit=30to get ~30 lines initially - Set
includeIncomingReferences=trueto see callers - Set
includeReferenceContext=truefor context snippets
- Set
- Use
get-decompilationon 1-2 suspicious functions identified in Step 6- Set
limit=20-30for quick overview
- Set
- 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
TodoWritetool 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=truefor 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.