## 使用

Inquisitor 有五个基本命令，包括 `scan`、`status`、`classify`、`dump` 和 `visualize`。```
usage: inq [-h] {scan,status,classify,dump,visualize} ...

optional arguments:
  -h, --help            show this help message and exit

command:
  {scan,status,classify,dump,visualize}
                        The action to perform.
    scan                Search OSINT sources for intelligence based on known
                        assets belonging to the target.
    status              Prints out the current status of the specified
                        intelligence database.
    classify            Classifies an existing asset as either belonging or
                        not belonging to the target. Adds a new asset with the
                        specified classification if none is present.
    dump                Dumps the contents of the database into a JSON file
    visualize           Create a D3.js visualization based on the contents of
                        the specified intelligence database.

### 状态

在状态模式下，该工具仅输出扫描数据库状态的快速摘要。```
usage: inq status [-h] [-s] DATABASE

positional arguments:
  DATABASE      The path to the intelligence database to use. If specified
                file does not exist, a new one will be created.

optional arguments:
  -h, --help    show this help message and exit
  -s, --strong  Indicates if the status will be based on the strong ownership
                classification.

### 转储

在转储模式下，您可以将情报数据库的内容转储为人类可读的JSON文件。```
usage: inq dump [-h] [-j FILE] [-a] DATABASE

positional arguments:
  DATABASE              The path to the intelligence database to use. If
                        specified file does not exist, a new one will be
                        created.

optional arguments:
  -h, --help            show this help message and exit
  -j FILE, --json FILE  The path to dump the JSON file to. Overwrites existing
                        files.
  -a, --all             Include rejected assets in dump.

## 工作流程

现在你已经了解了 Inquisitor 的基本功能，是时候学习如何*实际*使用它了。Inquisitor 的设计遵循以下步骤：

### 种子数据（Seeding）

在这一步，你的情报数据库中还没有任何数据。我们需要从某个地方开始，所以请先使用你确认属于目标组织的资产来填充数据库。你可以使用 `classify` 命令来完成。

### 扫描（Scanning）

现在数据库中已经有确认为目标组织所有的资产。接下来你可以进行扫描。你可以使用 `scan` 命令来完成。

当你对情报数据库执行 `scan` 命令时，Inquisitor 会对分类为 `accepted` 的资产运行 `transform` 方法。扫描完成后，你可能会得到更多可能属于目标组织的资产。

如果你没有获得任何新资产，你可以向情报数据库填充新信息，或者直接进入报告步骤以结束流程。

### 分类（Classifying）

虽然 Inquisitor 会为你自动分类资产，但它可能会遗漏一些实际上属于你目标组织的资产。

当这种情况发生时，你需要检查数据库内容并手动对这些资产进行分类。通常，你应该特别关注 **注册方（Registrant）** 资产，因为这种资产类型无法自动确定所有权。此外，大多数其他资产类型依赖于注册方资产的所有权分类来判断它们是否属于你的目标，因此最好密切关注你的注册方资产。另外，最初你获得的注册方资产数量并不多，所以筛选起来也不会太困难。

### 报告（Reporting）

你可以使用 `visualize` 命令或 `dump` 命令生成属于目标组织的资产可视化图。

## 演示

我通过以下链接提供了工具运行的视频演示：https://drive.google.com/open?id=0B_O70BVu38TRclo5dWRBWkdTTWc

不过，由于我的免费屏幕录制软件只能录制最多 10 分钟，我没能完整录制 `scan` 命令的运行过程。

## 开发

Inquisitor 项目的目录结构如下：```
.
|-- README.md
|-- inquisitor
|   |-- __init__.py
|   |-- assets
|   |   |-- __init__.py
|   |   |-- block.py
|   |   |-- email.py
|   |   |-- host.py
|   |   |-- linkedin.py
|   |   `-- registrant.py
|   |-- extractors
|   |   |-- __init__.py
|   |   `-- emails.py
|   `-- sources
|       |-- __init__.py
|       |-- google_search.py
|       `-- shodan_search.py
|-- inq
|-- report
|   `-- index.html
|-- setup.py
`-- tests
    |-- __init__.py
    `-- test_inq.py

Retrieves the primary key and asset object for the asset with the provided 
type and identifier.

asset_type: class, required

    The type of the asset to retrieve from the Intelligence Database. You
    will actually have to pass the class object of the asset type you want
    to retrieve.

identifier: any, required

    The identifier of the asset to retrieve. Consider the identifier as the
    unique attribute of an asset object. As for which attribute is to be
    used to identify an asset, it depends on the contents of the OBJECT_ID
    variable in the asset module.

create: bool, optional, default=False

    When no matching asset object is found, a new one will be created and 
    returned if this parameter is set to True. The new asset will not
    necessarily be stored in the Intelligence Database unless specified
    using the "store" parameter. However, I suggest you do not do this as
    adding assets to the Intelligence Database is the responsibility of
    another module.

store: bool, optional, default=False

    When a new asset is created when none is found, the new one will be
    stored in the Intelligence Database. As said previously, I suggest that
    you do not do this as adding assets to the Intelligence Database is the
    responsibility of another module.

A two-element tuple where the first element is the database primary key of 
the element returned, and the second element is the deserialized asset 
object retrieved from the database.

None if the asset was not found.

If the asset was not found and the create flag was set to True, the primary
key member of the tuple will be set to None.

### 资产

要创建新的资产类型，请在 `inquisitor/assets` 目录中创建一个新文件，并将以下骨架代码粘贴到其中：```python
import inquisitor.assets

class ASSET_NAMEValidateException(Exception):
    pass

def canonicalize(ASSET_IDENTIFIER):
    return ASSET_IDENTIFIER

def main_classify_args(parser):
    parser.add_argument(
        '-aASSET_NAME_LETTER', '--accept-ASSET_NAME',
        metavar='ASSET_NAME',
        type=canonicalize,
        nargs='+',
        help='Specifies a ASSET_NAME to classify as accepted.',
        dest='ASSET_NAMEs_accepted',
        default=list(),
    )
    parser.add_argument(
        '-uASSET_NAME_LETTER', '--unmark-ASSET_NAME',
        metavar='ASSET_NAME',
        type=canonicalize,
        nargs='+',
        help='Specifies a ASSET_NAME to classify as unmarked.',
        dest='ASSET_NAMEs_unmarked',
        default=list(),
    )
    parser.add_argument(
        '-rASSET_NAME_LETTER', '--reject-ASSET_NAME',
        metavar='ASSET_NAME',
        type=canonicalize,
        nargs='+',
        help='Specifies a ASSET_NAME to classify as rejected.',
        dest='ASSET_NAME_rejected',
        default=list(),
    )

def main_classify_canonicalize(args):
    accepted = set(args.ASSET_NAMEs_accepted)
    unmarked = set(args.ASSET_NAMEs_unmarked)
    rejected = set(args.ASSET_NAME_rejected)
    redundant = set.intersection(accepted, unmarked, rejected)
    if redundant:
        raise ValueError(
            ('Conflicting classifications for ASSET_NAMEs '
            ': {}').format(list(redundant))
        )
    accepted = set([canonicalize(a) for a in accepted])
    unmarked = set([canonicalize(a) for a in unmarked])
    rejected = set([canonicalize(a) for a in rejected])
    return (accepted, unmarked, rejected)

class ASSET_NAME(inquisitor.assets.Asset):

    def __init__(self, ASSET_IDENTIFIER, owned=None):
        super(self.__class__, self).__init__(owned=owned)
        self.ASSET_IDENTIFIER = canonicalize(ASSET_IDENTIFIER)
        # TODO: Perform other initialization actions here

    def __eq__(self, other):
        if not isinstance(other, self.__class__):
            return False
        return self.ASSET_IDENTIFIER == other.ASSET_IDENTIFIER

    def related(self, repo):
        # Prepare the results
        results = set()
        # TODO: Create related assets here based on the attributes of this asset
        # Return the results
        return results

    def transform(self, repo, sources):
        # Prepare the results
        assets = set()
        # Google Transforms
        if sources.get('google'):
            subassets = self.cache_transform_get('google', repo)
            if not subassets:
                # Acquire API
                google = sources['google']
                # TODO: Perform Google queries here and the results to 'subassets'
                # Cache The Transform
                self.cache_transform_store('google', subassets)
            assets.update(subassets)
        # Shodan Transforms
        if sources.get('shodan'):
            subassets = self.cache_transform_get('shodan', repo)
            if not subassets:
                # Acquire API
                shodan = sources['shodan']
                # TODO: Perform Google queries here and the results to 'subassets'
                # Cache The Transform
                self.cache_transform_store('shodan', subassets)
            assets.update(subassets)
        # Return the results
        return assets

    def is_owned(self, repo):
        if self.owned:
            return True
        # TODO: Automatically determine ownership based on repo contents
        return False

    def parent_asset(self, repo):
        # TODO: Return parent asset based on repo contents
        return None

REPOSITORY = 'ASSET_REPOSITORY'
ASSET_CLASS = ASSET_NAME
OBJECT_ID = 'ASSET_IDENTIFIER'

related

  Returns the set of assets directly related to the asset in question (i.e.
  those that can be derived without querying a search engine).

  When creating asset objects, make sure you use the 
  IntelligenceRepository.get_asset_string method instead of instatiating a 
  new one your self so the asset can be returned from the repository if it 
  exists.

  Set the create flag to True when calling the method in question in order
  to return a new object when one isn't found.

  Set the store flag to False as appending assets is the job of another
  module.

repo: IntelligenceRepository

    The Intelligence Repository that is being used in the current context.

Set of assets directly related to the asset in question. 

为此，我们需要使用一个支持OpenAI格式的统一API。

然后，我们可以使用一个小型模型进行分析，因为问题非常简单。

所以，我创建了一个代理来运行。

我们可以使用一个简单的'if else'语句。

对于结果，我们需要输出一个字符串。

注意：代理只运行一次，然后停止。

所以，我创建了一个代理。此，我们需要使用一个支持OpenAI格式的统一API。

然后，我们可以使用一个小型模型进行分析，因为问题非常简单。

所以，我创建了一个代理来运行。

我们可以使用一个简单的'if else'语句。

对于结果，我们需要输出一个字符串。

注意：代理只运行一次，然后停止。```
Function

    transform

Description
  
      Returns the set of assets potentially related to the asset in question
      (i.e. those that can be derived by querying a search engine).

      You may access search engine objects through the provided sources
      parameter.

      Each search engine object has a transform method which automatically
      creates asset objects for you. You just need to provide it the repository
      and your query string, and then append the objects it returns to the set
      of assets to be returned by your asset's transform method.

Parameters

    repo: IntelligenceRepository

        The Intelligence Repository that is being used in the current context.

    sources: dict

        The list of search engine objects that are available for use.

Returns

    Set of assets potentially related to the asset in question.
    

is_owned

 Determines if there is high confidence that this asset does indeed belong
 to the target. Usually checks for any "strong" classification tag first by
 looking at the contents of the "owned" variable, before performing
 automatic evaluation.

 Automatic evaluation depends on what type of asset you're writing. For
 example, for a Host asset, the secondary sources of determining ownership
 would include looking if its registrant is owned by the target, if it's
 parent domain is owned by the target. etc.

repo: IntelligenceRepository

    The Intelligence Repository that is being used in the current context.

True it is determined with high confidence that this asset does indeed 
belong to the target.

该工具可以通过将每个内核版本标记为易受攻击或修补后，快速识别Linux x86_64内核中的漏洞。

**特性**

- **操作系统**：与操作系统无关
- **架构**：与内核级别的操作系统架构无关

**感谢等**

我们想感谢所有对这个项目做出贡献的人。```
Function

    parent_asset

Description
  
     Returns the asset object that is considered the parent of this asset
     object.

Parameters

    repo: IntelligenceRepository

Returns

    The asset object that this asset falls under (e.g. a Block is under a 
    Registrant, a Host is under a Block, a Host is under another Host, an Email
    is under a Host, etc. This is primarily used for visualization.