S9009: TruffleHog
TruffleHog is an open-source secrets-discovery tool that is used to search for credentials, API keys, and encryption keys across a variety of data sources and environments.[1][2] TruffleHog has the ability to discover credentials and secrets stored in code repositories, git history, CI/CD pipelines, among other common storage locations to include filesystems and cloud storage buckets.[1][3][2] TruffleHog was first released by its author in 2016.[2]
Analyst context for executives and security teams
TruffleHog is a legitimate open-source secrets-discovery tool that can search for credentials, API keys, encryption keys, and other secrets across local systems, code repositories, CI/CD pipelines, cloud storage, and SaaS data sources. For defenders, its presence is material because the same capability used for security hygiene can also expose the credentials that enable cloud account abuse, token theft, and follow-on access to repositories, collaboration platforms, and cloud infrastructure.
Executive priority
Treat this behavior as an identity and cloud-risk signal, not just a tool sighting. Leaders should ask whether the organization can prove where secrets are stored, who can scan or access them, how exposed secrets are rotated, and whether cloud, repository, CI/CD, SharePoint, Confluence, messaging, and storage access is logged well enough for investigation. Budget and control priorities should focus on reducing hardcoded secrets, improving secrets-management adoption, enforcing least privilege, and ensuring incident response can rapidly revoke or rotate exposed credentials.
Technical view
SOC, detection, and IR teams should validate visibility across the supported environments: IaaS, Linux, SaaS, and Windows. The relationship context maps this tool to local data collection, file and directory discovery, code repository collection, SaaS repository mining, cloud service and infrastructure discovery, cloud storage object discovery, credential material in files, application token theft, cloud metadata access, and cloud secrets-management stores. Because ATT&CK provides no official detection text for this object, teams should build detections around observed execution, repository and SaaS access patterns, cloud API enumeration, unusual bulk reads of storage objects, and access to secrets or metadata services by identities or hosts that do not normally perform scanning.
Likely telemetry
- Endpoint process execution and command-line telemetry on Linux and Windows hosts where security or developer tooling may run
- File system access events for bulk reads of configuration files, source trees, build artifacts, and other sensitive paths
- Code repository audit logs for clone, fetch, search, and history access activity
- CI/CD platform logs showing pipeline execution, repository access, and secret-scanning activity
- Cloud audit logs for API calls related to service discovery, infrastructure discovery, storage listing, object reads, and secrets-management access
Detection direction
- Separate authorized security scanning from suspicious use by maintaining an inventory of approved scanners, service accounts, hosts, repositories, schedules, and expected data sources.
- Correlate tool execution or secret-scanning behavior with identity activity: new cloud sessions, unusual API calls, access to secrets stores, token use, or repository access outside normal patterns.
- Prioritize detections where scanning is followed by credential use, cloud account activity, application token access, or data access from cloud storage and SaaS repositories.
- Tune for likely false positives from developer workflows, CI/CD jobs, approved secret-scanning programs, and security assessments; require context such as caller identity, location, scope, and change ticket where possible.
- Watch for blind spots in SaaS audit logging, repository history access, cloud object-level logging, metadata service visibility, and unmanaged developer workstations.
Mitigation priorities
- Reduce exposed secrets first: remove credentials from code, files, documentation, messaging, and build artifacts where feasible.
- Use centralized secrets-management stores and restrict read/list permissions to the minimum required identities and workloads.
- Rotate or revoke exposed credentials, API keys, encryption keys, and application tokens when discovery or access is confirmed.
- Harden cloud identities with least privilege, conditional access where applicable, and monitoring of cloud account and token activity.
- Enable and retain audit logs for repositories, CI/CD systems, SaaS collaboration platforms, cloud APIs, cloud storage, and secrets managers so incidents can be scoped.
Analyst notes and limits
This is a dual-use software object. The ATT&CK record describes TruffleHog’s capability to discover secrets across repositories, git history, CI/CD pipelines, filesystems, cloud storage, and other common locations. The strongest defensive value comes from combining this tool context with the related ATT&CK techniques for credential access, discovery, collection, cloud accounts, cloud APIs, SaaS repositories, and cloud storage.
ATT&CK provides no official detection guidance, no aliases, and no specified tactics directly on the tool object. Local detections require environment-specific baselines for approved scanning, developer behavior, repository access, CI/CD activity, SaaS audit coverage, and cloud logging. This summary does not assert active exploitation, attribution, or guaranteed detection coverage.
TruffleHog
TruffleHog is an open-source secrets-discovery tool that is used to search for credentials, API keys, and encryption keys across a variety of data sources and environments.[1][2] TruffleHog has the ability to discover credentials and secrets stored in code repositories, git history, CI/CD pipelines, among other common storage locations to include filesystems and cloud storage buckets.[1][3][2] TruffleHog was first released by its author in 2016.[2]
How security teams should use this page
Treat this object as behavior context, not an attribution claim. Validate the related groups, software, data sources, and mitigations against official ATT&CK relationships and your own telemetry before making control-coverage decisions.
Techniques used
This mirrors the MITRE pattern of making group, software, campaign, and technique relationships scannable. Relationship notes come from mirrored ATT&CK relationship text when available.
| Domain | ID | Name | Relationship / procedure |
|---|---|---|---|
| Enterprise | T1213.002 | Sharepoint Sub-technique | TruffleHog has searched SharePoint for data and credentials.CitationGithub TruffleSecurity Trufflehog April 2025 |
| Enterprise | T1213.005 | Messaging Applications Sub-technique | TruffleHog has obtained data and credentials associated with messaging applications to include Slack.CitationGithub TruffleSecurity Trufflehog April 2025 |
| Enterprise | T1619 | Cloud Storage Object Discovery | TruffleHog can enumerate cloud storage environments including Amazon Web Service (AWS) S3 buckets and Google Cloud Storage buckets.CitationBlack Hills Information Security TruffleHog January 2024CitationGithub TruffleSecurity Trufflehog April 2025 |
| Enterprise | T1059.009 | Cloud API Sub-technique | TruffleHog has leveraged Cloud CLI in order to enumerate and gather credentials.CitationGithub TruffleSecurity Trufflehog April 2025 |
| Enterprise | T1526 | Cloud Service Discovery | TruffleHog has the ability to scan code repositories and CI/CD platforms.CitationBlack Hills Information Security TruffleHog January 2024CitationGithub TruffleSecurity Trufflehog April 2025 |
| Enterprise | T1555.006 | Cloud Secrets Management Stores Sub-technique | TruffleHog can obtain secrets from AWS Secrets and GCP Secret Manager.CitationBlack Hills Information Security TruffleHog January 2024CitationGithub TruffleSecurity Trufflehog April 2025 TruffleHog has also gathered passwords, secrets and API keys from source repositories, .env files, and git history.CitationNetskope Shai-Hulud November 2025 |
| Enterprise | T1580 | Cloud Infrastructure Discovery | TruffleHog can enumerate AWS Infrastructure to include EC2 instances.CitationGithub TruffleSecurity Trufflehog April 2025 |
| Enterprise | T1552.005 | Cloud Instance Metadata API Sub-technique | TruffleHog can query the AWS and GCP metadata endpoints for instances and service credentials.CitationBlack Hills Information Security TruffleHog January 2024CitationGithub TruffleSecurity Trufflehog April 2025 |
| Enterprise | T1528 | Steal Application Access Token | TruffleHog has gathered access tokens and API tokens from CI/CD pipeline solutions and repositories.CitationBlack Hills Information Security TruffleHog January 2024 |
| Enterprise | T1083 | File and Directory Discovery | TruffleHog has can browse and scan individual files and directories.CitationBlack Hills Information Security TruffleHog January 2024CitationNetskope Shai-Hulud November 2025CitationGithub TruffleSecurity Trufflehog April 2025 |
| Enterprise | T1005 | Data from Local System | TruffleHog has gathered data from home directories of the victim environment.CitationNetskope Shai-Hulud November 2025 |
| Enterprise | T1078.004 | Cloud Accounts Sub-technique | TruffleHog has used stolen credentials to log into cloud services to access cloud hosted repositories and other cloud storage solutions to discover sensitive data to include API Keys, tokens and credentials.CitationGithub TruffleSecurity Trufflehog April 2025 |
| Enterprise | T1552.001 | Credentials In Files Sub-technique | TruffleHog has obtained credentials stored in config files and credential files in victim environments.CitationBlack Hills Information Security TruffleHog January 2024CitationNetskope Shai-Hulud November 2025 |
| Enterprise | T1530 | Data from Cloud Storage | TruffleHog has the ability to scan cloud storage services for credentials to include Amazon (AWS) S3 and Google Cloud Storage.CitationBlack Hills Information Security TruffleHog January 2024CitationGithub TruffleSecurity Trufflehog April 2025 |
| Enterprise | T1213.001 | Confluence Sub-technique | TruffleHog has collected credentials and data associated with Confluence.CitationGithub TruffleSecurity Trufflehog April 2025 |
| Enterprise | T1213.003 | Code Repositories Sub-technique | TruffleHog has gathered data and credentials from code repositories.CitationGithub TruffleSecurity Trufflehog April 2025 |
All related ATT&CK context
Object version and sync metadata
The fields below describe the current mirrored snapshot. When Glexia retains multiple ATT&CK source imports, you can open the table to compare the same object across releases (hashes and MITRE timestamps). For MITRE’s own release notes and roadmap, see ATT&CK resources — Updates .
Imported snapshots across ATT&CK releases (1)
| Release | Bundle imported | Object version | Modified | Status | Raw hash |
|---|---|---|---|---|---|
| 19.1 | 1.0 | Current bundle | d7d1b1890c6b… |
Mirrored ATT&CK source object
The raw object is retained through the mirrored ATT&CK source bundle and object hash. The raw endpoint returns the exact object from the mirrored bundle when available.
External references and citations
MITRE external references are preserved separately from Glexia analysis so citations remain traceable to their original source records.
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[1]
Black Hills Information Security TruffleHog January 2024
Chris Traynor. (2024, January 18). Rooting For Secrets with TruffleHog. Retrieved April 15, 2026.
Open source URL -
[2]
Github TruffleSecurity Trufflehog April 2025
Trufflesecurity. (2026, April 8). TruffleHog Enterprise. Retrieved April 15, 2026.
Open source URL -
[3]
Netskope Shai-Hulud November 2025
Gianpietro Cutolo. (2025, November 26). Shai-Hulud 2.0: Aggressive, Automated, and Fast Spreading. Retrieved April 9, 2026.
Open source URL -
[4]
mitre-attack S9009Open source URL
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