Agent skill · Audited from source

deep-analysis

skill · cyberkaida/reverse-engineering-assistantApache-2.0 licenceAudited 22 Oct 2026 · source 81890607feb9

★ 878pushed 2 days ago
✓SAFEGrade B · 89/100 · 22 Oct 2026 · 8189060
878repo stars · whole cyberkaida/reverse-engineering-assistant

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 81890607feb9 and found no filesystem, network or shell access and no hard-coded secrets. What it does: 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?",…

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Cite this page

ModelsAtlas. “deep-analysis (cyberkaida/reverse-engineering-assistant)”. Retrieved 22 Oct 2026. https://modelsatlas.com/skills/cyberkaida/deep-analysis

Trust audit

Audit 0.4.1 · source read 22 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium0 low0 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 13,985 of 14,816 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codeNA0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (0)

No findings at any severity. We re-audit when the source changes.

Audit 0.4.1 · source sha 81890607feb9 · 22 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • Publishercyberkaida GitHub userOwner of the repository this skill is read from
  • Source foldercyberkaida/reverse-engineering-assistant/ReVa/skills/deep-analysisThe exact folder we audited
  • LicenceApache-2.0As the repository states it
  • Commit pinned for this verdict81890607feb9A new audit runs when the source changes
  • Repository statusNot archivedLast push 2 days ago
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its 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?",…

---
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

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit 8189060

Download folder ↗
git clone https://github.com/cyberkaida/reverse-engineering-assistant
git -C reverse-engineering-assistant checkout 81890607feb9

The author documents no install command, so this uses the repository directly. Our verdict covers commit 81890607feb9 only.

Works in

The author has not said which agents this skill supports, and we have not tested it in any.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source 81890607feb9

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Questions about deep-analysis

What does the deep-analysis skill do?
MCP server for reverse engineering tasks in Ghidra 👩💻
Is deep-analysis safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can deep-analysis access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (81890607feb9), read on 2026-10-22. The repository is watched, and a new audit runs when it changes — this is the first audit.

Sources

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