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Monitoring your Slack workspaces for sensitive information

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Slack Watchman

Python 2.7 and 3 compatible PyPI version License: MIT

Monitoring your Slack workspaces for sensitive information

About Slack Watchman

Slack Watchman is an application that uses the Slack API to look for potentially sensitive data exposed in your Slack workspaces.

More information about Slack Watchman can be found on my blog.


Slack Watchman looks for:

  • API Keys, Tokens & Service Accounts
    • AWS, Azure, GCP, Google API, Slack (keys & webhooks), Twitter, Facebook, GitHub
    • Generic Private keys
    • Access Tokens, Bearer Tokens, Client Secrets, Private Tokens
  • Files
    • Certificate files
    • Potentially interesting/malicious/sensitive files (.docm, .xlsm, .zip etc.)
    • Executable files
    • Keychain files
    • Config files for popular services (Terraform, Jenkins, OpenVPN and more)
  • Personal Data
    • Leaked passwords
    • Passport numbers, Dates of birth, Social security numbers, National insurance numbers, Drivers licence numbers (UK), Individual Taxpayer Identification Number
  • Financial data
    • Paypal Braintree tokens, Bank card details, IBAN numbers, CUSIP numbers

It also gives the following, which can be used for general auditing: - User data - All users & all admins - Channel data - All channels, including externally shared channels

Time based searching

You can run Slack Watchman to look for results going back as far as: - 24 hours - 7 days - 30 days - All time

This means after one deep scan, you can schedule Slack Watchman to run regularly and only return results from your chosen timeframe.


Slack Watchman uses custom YAML rules to detect matches in Slack.

They follow this format:

enabled: [true|false]
  description: #what the search should find
  severity: #rating out of 100
category: #[files|tokens|financial|pii]
- #[files|messages]
file_types: #optional list for use with file searching
  - #test case that should match the regex*
  - #test case that should not match the regex*
- #search query to use in Slack*
pattern: #Regex pattern to filter out false positives*

There are Python tests to ensure rules are formatted properly and that the Regex patterns work in the


More information about rules, and how you can add your own, is in the file



Slack Watchman gives the following logging options: - CSV - Log file - Stdout - TCP stream

When using CSV logging, searches for rules are returned in separate CSV files, for all other methods of logging, results are output in JSON format, perfect for ingesting into a SIEM or other log analysis platform.

For file and TCP stream logging, configuration options need to be passed via

file or environment variable. See the file
for instructions on how to set it up.

If no logging option is given, Slack Watchman defaults to CSV logging.


Slack API token

To run Slack Watchman, you will need a Slack API OAuth access token. You can do this by creating a simple Slack App.

The app needs to have the following User Token Scopes added:

Note: User tokens act on behalf of the user who authorises them, so I would suggest you create this app and authorise it using a service account, otherwise the app will have access to your private channels and chats.

Providing token

Slack Watchman will first try to get the the Slack token from the environment variable

, if this fails it will load the token from .conf file (see below).

.conf file

Configuration options can be passed in a file named

which must be stored in your home directory. The file should follow the YAML format, and should look like below:
  token: xoxp-xxxxxxxx
Slack Watchman will look for this file at runtime, and use the configuration options from here. If you are not using the advanced logging features, leave them blank.

If you are having issues with your .conf file, run it through a YAML linter.

An example file is in



Install via pip

pip install slack-watchman


Slack Watchman will be installed as a global command, use as follows: ``` usage: slack-watchman [-h] --timeframe {d,w,m,a} [--output {csv,file,stdout,stream}] [--version] [--all] [--users] [--channels] [--pii] [--financial] [--tokens] [--files] [--custom CUSTOM]

Monitoring your Slack workspaces for sensitive information

optional arguments: -h, --help show this help message and exit --output {csv,file,stdout,stream} Where to send results --version show program's version number and exit --all Find everything --users Find all users --channels Find all channels --pii Find personal data: Passwords, DOB, passport details, drivers licence, ITIN, SSN --financial Find financial data: Card details, PayPal Braintree tokens, IBAN numbers, CUSIP numbers --tokens Find tokens: Private keys, AWS, GCP, Google API, Slack, Slack webhooks, Facebook, Twitter, GitHub --files Find files: Certificates, interesting/malicious files --custom Search for user defined custom search queries that you have created rules for

required arguments: --timeframe {d,w,m,a} How far back to search: d = 24 hours w = 7 days, m = 30 days, a = all time ```

You can run Slack Watchman to look for everything, and output to default CSV:

slack-watchman --timeframe a --all

Or arguments can be grouped together to search more granularly. This will look for tokens and files for the last 30 days, and output the results to a TCP stream:

slack-watchman --timeframe m --tokens --files --output stream

Other Watchman apps

You may be interested in some of the other apps in the Watchman family: - GitLab Watchman - GitHub Watchman


The source code for this project is released under the GNU General Public Licence. This project is not associated with Slack.

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