# Install gimme-aws-creds with Homebrew CLI to retrieve AWS credentials from Okta. Version 2.8.2 via Homebrew; verified 2026-06-16. ## Install ```sh sudo av install brew:gimme-aws-creds ``` Additional install commands: ### macOS - Homebrew (100%): ```sh brew install gimme-aws-creds ``` Evidence: provider-native install command ## Package facts - **Package key:** brew:gimme-aws-creds - **Package manager:** Homebrew - **Version:** 2.8.2 - **Source summary:** CLI to retrieve AWS credentials from Okta - **Homepage:** - **Repository:** - **Last updated:** 2026-06-16T11:20:52Z - **Generated:** 2026-08-03T00:40:33+00:00 ## Executables - gimme-aws-creds (alias) - gimme-aws-creds-autocomplete.sh (alias) - gimme-aws-creds.cmd (alias) ## Install behavior - Bottle: not available ## Freshness - Page generated: 2026-08-03 - Package-manager version: 2.8.2 ## Project history and usage gimme-aws-creds is a command-line tool from Nike for obtaining short-lived cloud credentials through Okta-backed SAML authentication. ### Project history The official README describes gimme-aws-creds as a CLI that uses an Okta identity provider via SAML to acquire short-lived credentials for AWS and Alibaba Cloud. Its 1.0.0 release notes describe support for a Lambda proxy to avoid sharing an Okta API key widely, plus Okta MFA support for multiple factors. Over time the tool expanded from an Okta-to-AWS credential helper into a broader cloud credential bridge. Its documentation covers Okta Identity Engine, browser-based device authorization, MFA factor handling, configurable profiles, optional gimme-creds-lambda proxying, and Alibaba Cloud RAM credentials using the same Okta authentication flow. ### Adoption history The package fits the enterprise CLI niche created by federated AWS access: engineers need temporary AWS profiles, but organizations often require Okta MFA and SAML rather than long-lived IAM user keys. Distribution through PyPI, Homebrew, and Nix made it accessible to Python and macOS-oriented workstation setups. ### How it is used Practitioners install the tool, run its configuration action to store Okta organization, application, role, and profile preferences, then run gimme-aws-creds to write temporary credentials to the AWS shared credentials file or to stdout. Teams use named profiles and environment overrides to switch accounts, roles, durations, MFA behavior, and cloud-provider mode. ### Why package nerds care gimme-aws-creds is package-manager-interesting because it lives at the boundary between local developer ergonomics and enterprise identity policy. Small packaging details, Python support, shell completion, optional dependencies, and credential-file paths directly affect whether engineers can enter cloud shells without manual SAML copy-and-paste work. ### Timeline - 2017: Version 1.0.0 released with Lambda proxy and MFA support notes. - 2018: 1.0 and 1.1 series releases continued on PyPI. - 2019: 2.0 series appeared on PyPI. - 2023: 2.7 series releases added Identity Engine and authentication-policy work. - 2024: 2.8.2 released with config and Windows dependency fixes. ### Related projects - The README points to gimme-creds-lambda for proxying Okta API interaction. It also sits near Okta's AWS client, AWS STS AssumeRoleWithSAML workflows, Alibaba Cloud STS, and other Okta-to-cloud credential helper CLIs. ### Sources - - - - ## Security Notes No matching local secret-handling manifest was found for gimme-aws-creds. Nucleus package metadata is still published here so future coverage has a stable package URL. ## Configuration and credential file locations These source-backed paths show where this package keeps local settings or durable credentials. Automic Vault can use them as review targets for secret scanning, migration, and command approval. ## Configuration files - Unix: ~/.okta_aws_login_config ## Credential files - Unix: ~/.aws/credentials, ~/.aliyun/config.json ## Combined YAML source View the package source record on GitHub. [combined/gimme-aws-creds.yml](https://github.com/automic-vault/db/blob/main/combined/gimme-aws-creds.yml) ## Sources - Nucleus package database - Geiger risk classifier - curated configuration and credential file locations - curated package history - pkgdb category and tag curation