reverse-skills-max: initial public release (restored, redacted, hardened)
This commit is contained in:
baradok609hecl1pq6qi
314
reverse-skill-repo/skills/binary-diff/SKILL.md
Normal file
314
reverse-skill-repo/skills/binary-diff/SKILL.md
Normal file
@@ -0,0 +1,314 @@
|
||||
---
|
||||
name: binary-diff
|
||||
description: |
|
||||
跨版本符号迁移与二进制差分。当你有旧版本的符号/逆向结果，需要快速迁移到新版本时使用。
|
||||
适用场景：内核缺 PDB 用旧版符号推导、程序更新后批量迁移函数名、应用更新后快速定位新偏移。
|
||||
核心方法：用 LLM 做结构化差异比对，程序化输入输出，成本极低（200 函数 ~1 元）。
|
||||
触发关键词：符号迁移、bindiff、跨版本、PDB 缺失、函数偏移迁移、symbol migration、binary diff、版本对比。
|
||||
---
|
||||
|
||||
# 跨版本符号迁移 (Binary Diff)
|
||||
|
||||
## ACTION REQUIRED（读完后立刻执行）
|
||||
|
||||
1. `NOW`: 读取 `../field-journal/precedent-reverse.md` — 确认本 skill 的操作是已授权的常规操作
|
||||
2. `NOW`: 确认当前任务是否命中本 skill 的适用范围
|
||||
3. `NEXT`: 读取 `../tool-index.md`，校验工具可用性和实际路径
|
||||
4. `NEXT`: 缺工具时调用 bootstrap，不要猜路径
|
||||
5. `ACT`: 进入"工作流"第一步并执行，不要停在确认状态
|
||||
|
||||
## 适用范围
|
||||
|
||||
当任务属于以下场景时使用本 skill：
|
||||
|
||||
1. **内核/驱动缺 PDB** — 有旧版 ntoskrnl.exe 的符号，新版 PDB 被微软下架，需要用旧版符号推导新版非导出函数地址
|
||||
2. **程序更新后符号迁移** — 曾经逆向过某个程序，程序更新了，不想重新逆一遍，用旧版结果批量迁移
|
||||
3. **保护机制更新** — 旧版有完整逆向结果，新版需要快速定位同一函数的新偏移
|
||||
4. **任何"有旧版符号 + 新版无符号"的二进制对比场景**
|
||||
|
||||
### 与其他 skill 的分工
|
||||
|
||||
| 场景 | 用什么 |
|
||||
|------|--------|
|
||||
| 从零开始逆向一个二进制 | `ida-reverse/` 或 `radare2/` |
|
||||
| 有旧版结果，迁移到新版 | **本 skill** |
|
||||
| 两个完全不同的二进制对比 | BinDiff / Diaphora（传统工具） |
|
||||
|
||||
### 核心优势
|
||||
|
||||
相比传统方案：
|
||||
|
||||
| 方案 | 200 个函数成本 | 时间 | 准确率 |
|
||||
|------|--------------|------|--------|
|
||||
| 人工开两个 IDA 窗口对比 | 免费但耗命 | 数小时 | 高 |
|
||||
| BinDiff 自动匹配 | 免费 | 快 | 中（结构变化大时失效） |
|
||||
| 完全交给 Agent（CC/Codex） | 50-100 元 | 慢 | 高 |
|
||||
| **本 skill（LLM 批量比对）** | **~1 元** | **~10 秒/函数** | **高** |
|
||||
|
||||
## 核心原理
|
||||
|
||||
```text
|
||||
旧版函数（有符号） 新版同一函数（无符号）
|
||||
↓ ↓
|
||||
导出反汇编 + 伪代码 导出反汇编 + 伪代码
|
||||
↓ ↓
|
||||
└──────── LLM 结构化比对 ────────┘
|
||||
↓
|
||||
输出 YAML（符号映射表）
|
||||
↓
|
||||
程序化解析 → 批量应用到新版 IDB
|
||||
```
|
||||
|
||||
关键点：
|
||||
- prompt 是固定模板，程序化填充
|
||||
- 输入输出格式确定，程序化解析
|
||||
- LLM 只负责"看两段代码，找出对应关系"这一步
|
||||
- 时间成本和 token 成本极低
|
||||
|
||||
## Prompt 模板
|
||||
|
||||
### 标准比对 Prompt
|
||||
|
||||
```text
|
||||
I have disassembly outputs and procedure code of the same function.
|
||||
|
||||
This is the function for reference:
|
||||
|
||||
**Disassembly for Reference**
|
||||
```c
|
||||
{disasm_for_reference}
|
||||
```
|
||||
|
||||
**Procedure code for Reference**
|
||||
```c
|
||||
{procedure_for_reference}
|
||||
```
|
||||
|
||||
This is the function you need to reverse-engineering:
|
||||
|
||||
**Disassembly to reverse-engineering**
|
||||
```c
|
||||
{disasm_code}
|
||||
```
|
||||
|
||||
**Procedure code to reverse-engineering**
|
||||
```c
|
||||
{procedure}
|
||||
```
|
||||
|
||||
What you need to do is to collect all references to "{symbol_name_list}" in the function you need to reverse-engineering and output those references as YAML.
|
||||
|
||||
Example:
|
||||
```yaml
|
||||
found_vcall: # This is for indirect call to virtual function or virtual function pointer fetching.
|
||||
- insn_va: '0x180777700' # Always be the instruction with displacement offset
|
||||
insn_disasm: call [rax+68h] # Always be the instruction with displacement offset
|
||||
vfunc_offset: '0x68'
|
||||
func_name: ILoopMode_OnLoopActivate
|
||||
- insn_va: '0x180777778' # Always be the instruction with displacement offset
|
||||
insn_disasm: mov rax, [rax+80h] # Always be the instruction with displacement offset
|
||||
vfunc_offset: '0x80'
|
||||
func_name: INetworkMessages_GetNetworkGroupCount
|
||||
|
||||
found_call: # This is for direct call to non-virtual regular function.
|
||||
- insn_va: '0x180888800'
|
||||
insn_disasm: call sub_180999900
|
||||
func_name: CLoopMode_RegisterEventMapInternal
|
||||
- insn_va: '0x180888880'
|
||||
insn_disasm: call sub_180555500
|
||||
func_name: CLoopMode_SetSystemState
|
||||
|
||||
found_funcptr: # This is for non-virtual regular function pointer.
|
||||
- insn_va: '0x180666600' # Must load/reference the function pointer target address
|
||||
insn_disasm: lea rdx, sub_15BC910 # Must load/reference the function pointer target address
|
||||
funcptr_name: CLoopMode_OnClientPollNetworking
|
||||
|
||||
found_gv: # This is for reference to global variable.
|
||||
- insn_va: '0x180444400'
|
||||
insn_disasm: mov rcx, cs:qword_180666600 # Must load/reference the global variable
|
||||
gv_name: g_pNetworkMessages
|
||||
- insn_va: '0x180333300'
|
||||
insn_disasm: lea rax, unk_180222200 # Must load/reference the global variable
|
||||
gv_name: s_EventManager
|
||||
|
||||
found_struct_offset: # This is for reference to struct offset. NOTE THAT virtual function pointer should not be here! virtual function pointer should ALWAYS be in found_vcall !
|
||||
- insn_va: '0x1801BA12A' # Always be the instruction with displacement offset
|
||||
insn_disasm: mov rcx, [r14+58h] # Always be the instruction with displacement offset
|
||||
offset: '0x58'
|
||||
size: 8
|
||||
struct_name: CResourceService
|
||||
member_name: m_pEntitySystem
|
||||
```
|
||||
|
||||
If nothing found, output an empty YAML. DO NOT output anything other than the desired YAML. DO NOT collect unrelated symbols.
|
||||
```
|
||||
|
||||
### 变量说明
|
||||
|
||||
| 变量 | 来源 | 说明 |
|
||||
|------|------|------|
|
||||
| `{disasm_for_reference}` | 旧版 IDA 导出 | 有符号的反汇编 |
|
||||
| `{procedure_for_reference}` | 旧版 IDA 导出 | 有符号的伪代码 |
|
||||
| `{disasm_code}` | 新版 IDA 导出 | 无符号的反汇编 |
|
||||
| `{procedure}` | 新版 IDA 导出 | 无符号的伪代码 |
|
||||
| `{symbol_name_list}` | 从旧版提取 | 需要在新版中定位的符号列表 |
|
||||
|
||||
## 工作流
|
||||
|
||||
### 完整流程
|
||||
|
||||
```text
|
||||
Step 1: 准备数据
|
||||
- 旧版二进制加载到 IDA（有 PDB/符号）
|
||||
- 新版二进制加载到 IDA（无符号）
|
||||
- 找到两个版本中相同的锚点函数（导出函数、字符串引用等）
|
||||
|
||||
Step 2: 批量导出
|
||||
- 从旧版导出：锚点函数的反汇编 + 伪代码（含符号名）
|
||||
- 从新版导出：同一锚点函数的反汇编 + 伪代码（无符号名）
|
||||
|
||||
Step 3: LLM 比对
|
||||
- 用 prompt 模板填充数据
|
||||
- 调用 LLM API（推荐：deepseek 量大便宜，超大函数切 gpt）
|
||||
- 解析返回的 YAML
|
||||
|
||||
Step 4: 应用结果
|
||||
- 将 YAML 中的符号映射批量应用到新版 IDB
|
||||
- 用 idapro_rename 或 IDAPython 脚本批量重命名
|
||||
|
||||
Step 5: 迭代
|
||||
- 第一轮迁移的函数成为新的锚点
|
||||
- 进入这些函数，继续对比内部调用
|
||||
- 重复直到覆盖所有目标函数
|
||||
```
|
||||
|
||||
### 锚点选择策略
|
||||
|
||||
| 锚点类型 | 可靠性 | 说明 |
|
||||
|---------|--------|------|
|
||||
| 导出函数 | 最高 | 名字不变，地址可能变 |
|
||||
| 字符串引用 | 高 | 字符串内容不变，引用位置可能变 |
|
||||
| 常量/魔数 | 中 | 特征值不变 |
|
||||
| 代码模式 | 中 | 函数结构相似但地址全变 |
|
||||
|
||||
### 批量处理建议
|
||||
|
||||
- 每次比对 1 个函数（避免 context 爆炸）
|
||||
- 中等函数（<200 行）用 deepseek
|
||||
- 超大函数（>500 行）切 gpt-4o 或 claude
|
||||
- 并发调用提高速度（10-20 并发）
|
||||
- 结果缓存，避免重复调用
|
||||
|
||||
## 输出格式
|
||||
|
||||
### YAML 输出的 5 种符号类型
|
||||
|
||||
| 类型 | 含义 | 关键字段 |
|
||||
|------|------|---------|
|
||||
| `found_vcall` | 虚函数调用（间接 call） | `vfunc_offset`, `func_name` |
|
||||
| `found_call` | 直接函数调用 | `insn_va`, `func_name` |
|
||||
| `found_funcptr` | 函数指针引用 | `insn_va`, `funcptr_name` |
|
||||
| `found_gv` | 全局变量引用 | `insn_va`, `gv_name` |
|
||||
| `found_struct_offset` | 结构体偏移引用 | `offset`, `struct_name`, `member_name` |
|
||||
|
||||
### 解析后的应用动作
|
||||
|
||||
```text
|
||||
found_call → idapro_rename(addr=call_target, name=func_name)
|
||||
found_vcall → idapro_set_comments(addr=insn_va, comment="vcall: {func_name} @ +{offset}")
|
||||
found_funcptr → idapro_rename(addr=funcptr_target, name=funcptr_name)
|
||||
found_gv → idapro_rename(addr=gv_addr, name=gv_name)
|
||||
found_struct_offset → idapro_set_comments(addr=insn_va, comment="{struct_name}.{member_name}")
|
||||
```
|
||||
|
||||
## 典型场景示例
|
||||
|
||||
### 场景 1：ntoskrnl.exe 缺 PDB
|
||||
|
||||
```text
|
||||
已有：ntoskrnl.exe 10.0.26100.2000 + 完整 PDB
|
||||
目标：ntoskrnl.exe 10.0.26100.2605（PDB 被下架）
|
||||
需求：定位 PspSetCreateProcessNotifyRoutine 的新地址
|
||||
|
||||
步骤：
|
||||
1. 两个版本都加载到 IDA
|
||||
2. 找到导出函数 PsSetCreateProcessNotifyRoutine（两个版本都有）
|
||||
3. 旧版中它调用了 PspSetCreateProcessNotifyRoutine（有符号）
|
||||
4. 新版中它调用了 sub_140822108（无符号）
|
||||
5. LLM 一眼看出：sub_140822108 = PspSetCreateProcessNotifyRoutine
|
||||
6. 批量应用
|
||||
```
|
||||
|
||||
### 场景 2：应用更新后迁移
|
||||
|
||||
```text
|
||||
已有：target.exe v1.0 的完整逆向结果（200+ 函数已命名）
|
||||
目标：target.exe v1.1（所有符号丢失）
|
||||
需求：批量迁移 200 个函数名
|
||||
|
||||
步骤：
|
||||
1. 从旧版导出所有已命名函数的反汇编+伪代码
|
||||
2. 在新版中通过导出函数/字符串找到对应锚点
|
||||
3. 批量调用 LLM 比对
|
||||
4. 解析 YAML，批量 rename
|
||||
5. 迭代深入
|
||||
```
|
||||
|
||||
## LLM 选择建议
|
||||
|
||||
| 模型 | 适合场景 | 成本 | 速度 |
|
||||
|------|---------|------|------|
|
||||
| DeepSeek V3 | 中小函数（<200 行），批量处理 | 极低 | 快 |
|
||||
| GPT-4o | 超大函数，复杂控制流 | 中 | 快 |
|
||||
| Claude Sonnet | 中大函数，需要推理 | 中 | 快 |
|
||||
| Claude Opus | 极复杂函数，需要深度理解 | 高 | 慢 |
|
||||
|
||||
推荐策略：默认 DeepSeek，遇到 context 超限或结果不准时自动升级。
|
||||
|
||||
## 注意事项
|
||||
|
||||
- **不要把整个二进制丢给 LLM** — 一次只比对一个函数
|
||||
- **锚点必须可靠** — 如果锚点本身就对错了，后续全部白费
|
||||
- **结果需要人工抽检** — LLM 不是 100% 准确，关键符号要验证
|
||||
- **缓存中间结果** — 避免重复调用浪费 token
|
||||
- **注意 context 限制** — 超大函数（>1000 行反汇编）需要拆分或用大 context 模型
|
||||
|
||||
---
|
||||
|
||||
## 按需自举（On-Demand Bootstrap）
|
||||
|
||||
### 工具依赖
|
||||
|
||||
| 工具 | 用途 | 可自动安装 |
|
||||
|------|------|-----------|
|
||||
| IDA Pro | 导出反汇编/伪代码 | ✗（商业软件） |
|
||||
| Python | 脚本执行、API 调用 | ✓ |
|
||||
| PyYAML | 解析 LLM 返回的 YAML | ✓（pip install pyyaml） |
|
||||
| LLM API | 执行比对 | 需要 API key |
|
||||
|
||||
### 说明
|
||||
|
||||
本 skill 的核心不依赖重型工具安装，主要依赖：
|
||||
- IDA Pro 已有（用 `ida-reverse/` skill 管理）
|
||||
- Python + requests/httpx（调 API）
|
||||
- 一个 LLM API endpoint
|
||||
|
||||
---
|
||||
|
||||
## 路由上下文
|
||||
|
||||
**上游入口**: `skills/SKILL.md`（总控）、`routing.md`
|
||||
**触发条件**: 有旧版符号/逆向结果，需要迁移到新版本
|
||||
**下游出口**:
|
||||
- 需要先打开二进制 → `ida-reverse/`
|
||||
- 需要快速侦察确认版本差异 → `radare2/`
|
||||
|
||||
**同级关联模块**: `ida-reverse/`（数据导出和符号应用都通过 IDA）
|
||||
|
||||
|
||||
## 任务完成自检（声称完成前 MUST 通过）
|
||||
|
||||
- [ ] 我是否执行了工作流中的每一步（而不是只阅读）？
|
||||
- [ ] 我是否基于 `tool-index` 使用了真实工具路径？
|
||||
- [ ] 我是否产出了可复现证据（命令/脚本/截图/报告）？
|
||||
- [ ] 我是否完成并回写了 RULES 要求的 Checklist 项？
|
||||
@@ -0,0 +1,173 @@
|
||||
# Symbol Migration Prompt Template
|
||||
|
||||
## 标准比对 Prompt（直接复制使用）
|
||||
|
||||
```text
|
||||
I have disassembly outputs and procedure code of the same function.
|
||||
|
||||
This is the function for reference:
|
||||
|
||||
**Disassembly for Reference**
|
||||
```c
|
||||
{disasm_for_reference}
|
||||
```
|
||||
|
||||
**Procedure code for Reference**
|
||||
```c
|
||||
{procedure_for_reference}
|
||||
```
|
||||
|
||||
This is the function you need to reverse-engineering:
|
||||
|
||||
**Disassembly to reverse-engineering**
|
||||
```c
|
||||
{disasm_code}
|
||||
```
|
||||
|
||||
**Procedure code to reverse-engineering**
|
||||
```c
|
||||
{procedure}
|
||||
```
|
||||
|
||||
What you need to do is to collect all references to "{symbol_name_list}" in the function you need to reverse-engineering and output those references as YAML.
|
||||
|
||||
Example:
|
||||
```yaml
|
||||
found_vcall:
|
||||
- insn_va: '0x180777700'
|
||||
insn_disasm: call [rax+68h]
|
||||
vfunc_offset: '0x68'
|
||||
func_name: ILoopMode_OnLoopActivate
|
||||
|
||||
found_call:
|
||||
- insn_va: '0x180888800'
|
||||
insn_disasm: call sub_180999900
|
||||
func_name: CLoopMode_RegisterEventMapInternal
|
||||
|
||||
found_funcptr:
|
||||
- insn_va: '0x180666600'
|
||||
insn_disasm: lea rdx, sub_15BC910
|
||||
funcptr_name: CLoopMode_OnClientPollNetworking
|
||||
|
||||
found_gv:
|
||||
- insn_va: '0x180444400'
|
||||
insn_disasm: mov rcx, cs:qword_180666600
|
||||
gv_name: g_pNetworkMessages
|
||||
|
||||
found_struct_offset:
|
||||
- insn_va: '0x1801BA12A'
|
||||
insn_disasm: mov rcx, [r14+58h]
|
||||
offset: '0x58'
|
||||
size: 8
|
||||
struct_name: CResourceService
|
||||
member_name: m_pEntitySystem
|
||||
```
|
||||
|
||||
If nothing found, output an empty YAML. DO NOT output anything other than the desired YAML. DO NOT collect unrelated symbols.
|
||||
```
|
||||
|
||||
## 变量填充说明
|
||||
|
||||
| 变量 | 来源 | 获取方式 |
|
||||
|------|------|---------|
|
||||
| `{disasm_for_reference}` | 旧版 IDA | `idapro_disasm(addr="函数名")` |
|
||||
| `{procedure_for_reference}` | 旧版 IDA | `idapro_decompile(addr="函数名")` |
|
||||
| `{disasm_code}` | 新版 IDA | `idapro_disasm(addr="对应地址")` |
|
||||
| `{procedure}` | 新版 IDA | `idapro_decompile(addr="对应地址")` |
|
||||
| `{symbol_name_list}` | 旧版提取 | 从 reference 代码中提取所有非 sub_/loc_ 的符号名 |
|
||||
|
||||
## 批量调用脚本骨架（Python）
|
||||
|
||||
```python
|
||||
import yaml
|
||||
import httpx
|
||||
import json
|
||||
from pathlib import Path
|
||||
|
||||
PROMPT_TEMPLATE = open("prompt-template.txt").read()
|
||||
|
||||
def migrate_function(ref_disasm, ref_procedure, target_disasm, target_procedure, symbols, api_url, api_key, model="deepseek-chat"):
|
||||
prompt = PROMPT_TEMPLATE.format(
|
||||
disasm_for_reference=ref_disasm,
|
||||
procedure_for_reference=ref_procedure,
|
||||
disasm_code=target_disasm,
|
||||
procedure=target_procedure,
|
||||
symbol_name_list=", ".join(symbols)
|
||||
)
|
||||
|
||||
resp = httpx.post(api_url, json={
|
||||
"model": model,
|
||||
"messages": [{"role": "user", "content": prompt}],
|
||||
"temperature": 0
|
||||
}, headers={"Authorization": f"Bearer {api_key}"}, timeout=60)
|
||||
|
||||
content = resp.json()["choices"][0]["message"]["content"]
|
||||
|
||||
# 提取 YAML 块
|
||||
if "```yaml" in content:
|
||||
yaml_str = content.split("```yaml")[1].split("```")[0]
|
||||
elif "```" in content:
|
||||
yaml_str = content.split("```")[1].split("```")[0]
|
||||
else:
|
||||
yaml_str = content
|
||||
|
||||
return yaml.safe_load(yaml_str)
|
||||
|
||||
|
||||
def apply_results(results, ida_session):
|
||||
"""将解析后的 YAML 结果应用到 IDA"""
|
||||
if not results:
|
||||
return
|
||||
|
||||
renames = []
|
||||
comments = []
|
||||
|
||||
if "found_call" in results:
|
||||
for item in results["found_call"]:
|
||||
# 从 insn_disasm 中提取 call target
|
||||
# call sub_XXXXXXX → 提取 sub_XXXXXXX 的地址
|
||||
renames.append({"addr": item["insn_va"], "name": item["func_name"], "type": "call_target"})
|
||||
|
||||
if "found_funcptr" in results:
|
||||
for item in results["found_funcptr"]:
|
||||
renames.append({"addr": item["insn_va"], "name": item["funcptr_name"], "type": "funcptr_target"})
|
||||
|
||||
if "found_gv" in results:
|
||||
for item in results["found_gv"]:
|
||||
renames.append({"addr": item["insn_va"], "name": item["gv_name"], "type": "gv"})
|
||||
|
||||
if "found_vcall" in results:
|
||||
for item in results["found_vcall"]:
|
||||
comments.append({
|
||||
"addr": item["insn_va"],
|
||||
"comment": f"vcall: {item['func_name']} @ +{item['vfunc_offset']}"
|
||||
})
|
||||
|
||||
if "found_struct_offset" in results:
|
||||
for item in results["found_struct_offset"]:
|
||||
comments.append({
|
||||
"addr": item["insn_va"],
|
||||
"comment": f"{item['struct_name']}.{item['member_name']} @ +{item['offset']}"
|
||||
})
|
||||
|
||||
return {"renames": renames, "comments": comments}
|
||||
```
|
||||
|
||||
## API 配置建议
|
||||
|
||||
```yaml
|
||||
# 默认用 DeepSeek（便宜）
|
||||
default:
|
||||
api_url: "https://api.deepseek.com/v1/chat/completions"
|
||||
model: "deepseek-chat"
|
||||
|
||||
# 超大函数回退到 GPT
|
||||
fallback:
|
||||
api_url: "https://api.openai.com/v1/chat/completions"
|
||||
model: "gpt-4o"
|
||||
|
||||
# 或者用 Claude
|
||||
alternative:
|
||||
api_url: "https://api.anthropic.com/v1/messages"
|
||||
model: "claude-sonnet-4-20250514"
|
||||
```
|
||||
Reference in New Issue
Block a user