Usage

Learn what is secret scanning and why it matters for building secure systems.

Introduction

Monitor and detect exposed secrets across your data sources, including code repositories, with Infisical Secret Scanning.

For additional security, we recommend using our CLI Secret Scanner to check for exposed secrets before pushing your code changes.

Secret Scanning is a paid feature. If you’re using Infisical Cloud, then it is available under the Enterprise Tier. If you’re self-hosting Infisical, then you should contact [e-mail] to purchase an enterprise license to use it.

How Secret Scanning Works

Secret Scanning consists of several components that enable you to quickly respond to secret leaks:

• Scanner Engine: The core component that analyzes your code and detects potential secrets using pattern matching and entropy analysis
• Real-time Monitoring: Provides continuous surveillance of your repositories for immediate detection of exposed secrets
• Alert System: Notifies organization admins via email when secrets are detected
• Risk Management: Allows tracking and managing detected secrets with different status options
• Data Sources: Integrates with various data sources and version control systems
• Customizable Rules: Supports ignore patterns and custom configurations to reduce false positives

These components work together to provide comprehensive secret detection and incident response capabilities.

Data Sources

Data sources are configured integrations with external platforms, such as a GitHub organization or a GitLab group, that establish secure connections for scanning purposes using App Connections.

A data source acts as a secure intermediary between the external system and the scanner engine. It manages a collection of scannable resources (such as repositories) and handles the authentication and communication required for scanning operations.

Resources

Resources are the atomic, scannable units, such as a repository, that can be monitored for secret exposure. Resources are added automatically when a data source is scanned and updated when scanning events are triggered, such as when a user pushes changes to GitHub.

Each resource maintains its own scanning history and status, allowing for granular monitoring and management of secret scanning across your organization.

Scans

Scans can be initiated in two ways:

1. Full Scan - Manually triggered scan that comprehensively checks either all resources associated with a data source or a single selected resource.

2. Diff Scan - Automatically executed when Auto-Scan is enabled on a data source. This scan type specifically focuses on updates to existing resources.

All scan activities can be monitored in real-time through the Infisical UI, which displays:

• Current scan status
• Timestamp of the scan
• Resource(s) being scanned
• Detection results (whether any secrets were found)

Findings

Findings are automatically generated when secret leaks are detected during scanning operations. Each finding contains comprehensive information including:

• The specific scanning rule that identified the leak
• File location and line number where the secret was found
• Resource-specific details (e.g., commit hash and author for Git repositories)

Findings are initially marked as Unresolved and can be updated to one of the following statuses with additional remarks:

• Resolved - The issue has been addressed
• False Positive - The detection was incorrect
• Ignore - The finding can be safely disregarded

These status options help teams effectively track and manage the lifecycle of detected secret leaks.

Configuration

You can configure custom scanning rules and exceptions by updating your project’s scanning configuration via the UI or API.

The configuration options allow you to:

• Define custom scanning patterns and rules
• Set up ignore patterns to reduce false positives
• Specify file path exclusions
• Configure entropy thresholds for secret detection
• Add allowlists for known safe patterns

For detailed configuration options, expand the example configuration below.

Example Configuration

# Title for the configuration file
title = "Some title"

# This configuration is the foundation that can be expanded. If there are any overlapping rules
# between this base and the expanded configuration, the rules in this base will take priority.
# Another aspect of extending configurations is the ability to link multiple files, up to a depth of 2.
# "Allowlist" arrays get appended and may have repeated elements.
# "useDefault" and "path" cannot be used simultaneously. Please choose one.
[extend]
# useDefault will extend the base configuration with the default config:
# https://raw.githubusercontent.com/Infisical/infisical/main/cli/config/infisical-scan.toml
useDefault = true
# or you can supply a path to a configuration. Path is relative to where infisical cli
# was invoked, not the location of the base config.
path = "common_config.toml"

# An array of tables that contain information that define instructions
# on how to detect secrets
[[rules]]

# Unique identifier for this rule
id = "some-identifier-for-rule"

# Short human readable description of the rule.
description = "awesome rule 1"

# Golang regular expression used to detect secrets. Note Golang's regex engine
# does not support lookaheads.
regex = '''one-go-style-regex-for-this-rule'''

# Golang regular expression used to match paths. This can be used as a standalone rule or it can be used
# in conjunction with a valid `regex` entry.
path = '''a-file-path-regex'''

# Array of strings used for metadata and reporting purposes.
tags = ["tag","another tag"]

# A regex match may have many groups, this allows you to specify the group that should be used as (which group the secret is contained in)
# its entropy checked if `entropy` is set.
secretGroup = 3

# Float representing the minimum shannon entropy a regex group must have to be considered a secret.
# Shannon entropy measures how random a data is. Since secrets are usually composed of many random characters, they typically have high entropy
entropy = 3.5

# Keywords are used for pre-regex check filtering.
# If rule has keywords but the text fragment being scanned doesn't have at least one of it's keywords, it will be skipped for processing further.
# Ideally these values should either be part of the identifier or unique strings specific to the rule's regex
# (introduced in v8.6.0)
keywords = [
    "auth",
    "password",
    "token",
]

# You can include an allowlist table for a single rule to reduce false positives or ignore commits
# with known/rotated secrets
[rules.allowlist]
description = "ignore commit A"
commits = [ "commit-A", "commit-B"]
paths = [
    '''go\.mod''',
    '''go\.sum'''
]
# note: (rule) regexTarget defaults to check the _Secret_ in the finding.
# if regexTarget is not specified then _Secret_ will be used.
# Acceptable values for regexTarget are "match" and "line"
regexTarget = "match"
regexes = [
    '''process''',
    '''getenv''',
]
# note: stopwords targets the extracted secret, not the entire regex match
# if the extracted secret is found in the stopwords list, the finding will be skipped (i.e not included in report)
stopwords = [
    '''client''',
    '''endpoint''',
]


# This is a global allowlist which has a higher order of precedence than rule-specific allowlists.
# If a commit listed in the `commits` field below is encountered then that commit will be skipped and no
# secrets will be detected for said commit. The same logic applies for regexes and paths.
[allowlist]
description = "global allow list"
commits = [ "commit-A", "commit-B", "commit-C"]
paths = [
    '''gitleaks\.toml''',
    '''(.*?)(jpg|gif|doc)'''
]

# note: (global) regexTarget defaults to check the _Secret_ in the finding.
# if regexTarget is not specified then _Secret_ will be used.
# Acceptable values for regexTarget are "match" and "line"
regexTarget = "match"

regexes = [
    '''219-09-9999''',
    '''078-05-1120''',
    '''(9[0-9]{2}|666)-\d{2}-\d{4}''',
]
# note: stopwords targets the extracted secret, not the entire regex match
# if the extracted secret is found in the stopwords list, the finding will be skipped (i.e not included in report)
stopwords = [
    '''client''',
    '''endpoint''',
]

Ignoring Known Secrets

If you’re intentionally committing a test secret that the secret scanner might flag, you can instruct Infisical to overlook that secret with the methods listed below.

infisical-scan:ignore

To ignore a secret contained in line of code, simply add infisical-scan:ignore at the end of the line as comment in the given programming.

example.js

function helloWorld() {
  console.log("8dyfuiRyq=vVc3RRr_edRk-fK__JItpZ"); // infisical-scan:ignore
}

.infisicalignore

An alternative method to exclude specific findings involves creating a .infisicalignore file at your repository’s root. You can then add the fingerprints of the findings you wish to exclude. The Infisical scan report provides a unique Fingerprint for each secret found. By incorporating these Fingerprints into the .infisicalignore file, Infisical will skip the corresponding secret findings in subsequent scans.

.infisicalignore

bea0ff6e05a4de73a5db625d4ae181a015b50855:frontend/components/utilities/attemptLogin.js:stripe-access-token:147
bea0ff6e05a4de73a5db625d4ae181a015b50855:backend/src/json/integrations.json:generic-api-key:5
1961b92340e5d2613acae528b886c842427ce5d0:frontend/components/utilities/attemptLogin.js:stripe-access-token:148