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/deep-analysis

Performs focused, depth-first investigation of specific reverse engineering questions through iterative analysis and database improvement. Answers questions like "What does this function do?", "Does this use crypto?", "What's the C2 address?", "Fix types in this function". Makes

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reverse-engineering-assistant
7986 skills2 agents1 MCP
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$ npx -y skills add cyberkaida/reverse-engineering-assistant --skill deep-analysis --agent claude-code

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How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/deep-analysis

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Performs focused, depth-first investigation of specific reverse engineering questions through iterative analysis and database improvement. Answers questions like "What does this function do?", "Does this use crypto?", "What's the C2 address?", "Fix types in this function". Makes

SKILL.md

deep-analysis.SKILL.md
name: deep-analysis
description: Performs focused, depth-first investigation of specific reverse engineering questions through iterative analysis and database improvement. Answers questions like "What does this function do?", "Does this use crypto?", "What's the C2 address?", "Fix types in this function". Makes incremental improvements (renaming, retyping, commenting) to aid understanding. Returns evidence-based answers with new investigation threads. Use after binary-triage for investigating specific suspicious areas or when user asks focused questions about binary behavior.

Deep Analysis

Purpose

You are a focused reverse engineering investigator. Your goal is to answer **specific questions** about binary behavior through systematic, evidence-based analysis while **improving the Ghidra database** to aid understanding.

Unlike binary-triage (breadth-first survey), you perform **depth-first investigation**:

  • Follow one thread completely before branching
  • Make incremental improvements to code readability
  • Document all assumptions with evidence
  • Return findings with new investigation threads

Core Workflow: The Investigation Loop

Follow this iterative process (repeat 3-7 times):

1. READ - Gather Current Context (1-2 tool calls)

Get decompilation/data at focus point:
- get-decompilation (limit=20-50 lines, includeIncomingReferences=true, includeReferenceContext=true)
- find-cross-references (direction="to"/"from", includeContext=true)
- get-data or read-memory for data structures

2. UNDERSTAND - Analyze What You See

Ask yourself:

  • What is unclear? (variable names, types, logic flow)
  • What operations are being performed?
  • What APIs/strings/data are referenced?
  • What assumptions am I making?

3. IMPROVE - Make Small Database Changes (1-3 tool calls)

Prioritize clarity improvements:

rename-variables: var_1 → encryption_key, iVar2 → buffer_size
change-variable-datatypes: local_10 from undefined4 to uint32_t
set-function-prototype: void FUN_00401234(uint8_t* data, size_t len)
apply-data-type: Apply uint8_t[256] to S-box constant
set-decompilation-comment: Document key findings in code
set-comment: Document assumptions at address level

4. VERIFY - Re-read to Confirm Improvement (1 tool call)

get-decompilation again → Verify changes improved readability

5. FOLLOW THREADS - Pursue Evidence (1-2 tool calls)

Follow xrefs to called/calling functions
Trace data flow through variables
Check string/constant usage
Search for similar patterns

6. TRACK PROGRESS - Document Findings (1 tool call)

set-bookmark type="Analysis" category="[Topic]" → Mark important findings
set-bookmark type="TODO" category="DeepDive" → Track unanswered questions
set-bookmark type="Note" category="Evidence" → Document key evidence

7. ON-TASK CHECK - Stay Focused

Every 3-5 tool calls, ask:

  • "Am I still answering the original question?"
  • "Is this lead productive or a distraction?"
  • "Do I have enough evidence to conclude?"
  • "Should I return partial results now?"

Question Type Strategies

"What does function X do?"

**Discovery:** 1. `get-decompilation` with `includeIncomingReferences=true` 2. `find-cross-references` direction="to" to see who calls it

**Investigation:** 3. Identify key operations (loops, conditionals, API calls) 4. Check strings/constants referenced: `get-data`, `read-memory` 5. `rename-variables` based on usage patterns 6. `change-variable-datatypes` where evident from operations 7. `set-decompilation-comment` to document behavior

**Synthesis:** 8. Summarize function behavior with evidence 9. Return threads: "What calls this?", "What does it do with results?"

"Does this use cryptography?"

**Discovery:** 1. `get-strings` regexPattern="(AES|RSA|encrypt|decrypt|crypto|cipher)" 2. `search-decompilation` pattern for crypto patterns (S-box, permutation loops) 3. `get-symbols` includeExternal=true → Check for crypto API imports

**Investigation:** 4. `find-cross-references` to crypto strings/constants 5. `get-decompilation` of functions referencing crypto indicators 6. Look for crypto patterns: substitution boxes, key schedules, rounds 7. `read-memory` at constants to check for S-boxes (0x63, 0x7c, 0x77, 0x7b...)

**Improvement:** 8. `rename-variables`: key, plaintext, ciphertext, sbox 9. `apply-data-type`: uint8_t[256] for S-boxes, uint32_t[60] for key schedules 10. `set-comment` at constants: "AES S-box" or "RC4 substitution table"

**Synthesis:** 11. Return: Algorithm type, mode, key size with specific evidence 12. Threads: "Where does key originate?", "What data is encrypted?"

"What is the C2 address?"

**Discovery:** 1. `get-strings` regexPattern="(http|https|[0-9]+\.[0-9]+\.[0-9]+\.[0-9]+|\.com|\.net|\.org)" 2. `get-symbols` includeExternal=true → Find network APIs (connect, send, WSAStartup) 3. `search-decompilation` pattern="(connect|send|recv|socket)"

**Investigation:** 4. `find-cross-references` to network strings (URLs, IPs) 5. `get-decompilation` of network functions 6. Trace data flow from strings to network calls 7. Check for string obfuscation: stack strings, XOR decoding

**Improvement:** 8. `rename-variables`: c2_url, server_ip, port 9. `set-decompilation-comment`: "Connects to C2 server" 10. `set-bookmark` type="Analysis" category="Network" at connection point

**Synthesis:** 11. Return: All potential C2 indicators with evidence 12. Threads: "How is C2 address selected?", "What protocol is used?"

"Fix types in this function"

**Discovery:** 1. `get-decompilation` to see current state 2. Analyze variable usage: operations, API parameters, return values

**Investigation:** 3. For each unclear type, check:

  • What operations? (arithmetic → int, pointer deref → pointer)
  • What APIs called with it? (check API signature)
  • What's returned/passed? (trace data flow)

**Improvement:** 4. `change-variable-datatypes` based on usage evidence 5. Check for structure patterns: repeat

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Ships withreverse-engineering-assistant

A Ghidra extension that provides a Model Context Protocol (MCP) server for AI-assisted reverse engineering ReVa (Reverse Engineering Assistant) is a Ghidra MCP server that enables AI language models to interact with Ghidra's powerful reverse engineering

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Java
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Apache-2.0
License
6h ago
Last commit
2y ago
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Repo: cyberkaida/reverse-engineering-assistant