# Kingfisher

Kingfisher Logo [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) Kingfisher is a blazingly fast secret‑scanning and validation tool built in Rust. It combines Intel’s hardware‑accelerated Hyperscan regex engine with language‑aware parsing via Tree‑Sitter, and **ships with hundreds of built‑in rules** to detect, validate, and triage secrets before they ever reach production

Kingfisher originated as a fork of [Nosey Parker](https://github.com/praetorian-inc/noseyparker) by Praetorian Security, Inc, and is built atop their incredible work and the work contributed by the Nosey Parker community. Kingfisher extends Nosey Parker with live secret validation via cloud-provider APIs, augments regex detection with tree-sitter for code parsing, adds GitLab support, and builds a Windows x64 binary. **MongoDB Blog**: [Introducing Kingfisher: Real-Time Secret Detection and Validation](https://www.mongodb.com/blog/post/product-release-announcements/introducing-kingfisher-real-time-secret-detection-validation) ## Key Features - **Performance**: Multi‑threaded, Hyperscan‑powered scanning for massive codebases - **Language‑Aware Accuracy**: AST parsing in 20+ languages via Tree‑Sitter reduces contextless regex matches. see [docs/PARSING.md](/docs/PARSING.md) - **Built-In Validation**: Hundreds of built-in detection rules, many with live-credential validators that call the relevant service APIs (AWS, Azure, GCP, Stripe, etc.) to confirm a secret is active. You can extend or override the library by adding YAML-defined rules on the command line—see [docs/RULES.md](/docs/RULES.md) for details - **Git History Scanning**: Scan local repos, remote GitHub/GitLab orgs/users, or arbitrary GitHub/GitLab repos ## Getting Started ### Installation On macOS, you can simply ```bash brew install kingfisher ``` Pre-built binaries are also available on the [Releases](https://github.com/mongodb/kingfisher/releases) section of this page. Or you may compile for your platform via `make`: ```bash # NOTE: Requires Docker make linux ``` ```bash # macOS make darwin ``` ```bash # Windows x64 --- requires building from a Windows host with Visual Studio installed ./buildwin.bat -force ``` ```bash # Build all targets make linux-all # builds both x64 and arm64 make darwin-all # builds both x64 and arm64 make all # builds for every OS and architecture supported ``` # Write Custom Rules! Kingfisher ships with hundreds of rules with HTTP and service‑specific validation checks (AWS, Azure, GCP, etc.) to confirm if a detected string is a live credential. However, you may want to add your own custom rules, or modify a detection to better suit your needs / environment. First, review [docs/RULES.md](/docs/RULES.md) to learn how to create custom Kingfisher rules. Once you've done that, you can provide your custom rules (defined in a YAML file) and provide it to Kingfisher at runtime --- no recompiling required! # Usage ## Basic Examples > **Note**  `kingfisher scan` detects whether the input is a Git repository or a plain directory—no extra flags required. ### Scan with secret validation ```bash kingfisher scan /path/to/code ## NOTE: This path can refer to: # 1. a local git repo # 2. a directory with many git repos # 3. or just a folder with files and subdirectories ## To explicitly prevent scanning git commit history add: # `--git-history=none` ``` ### Scan a directory containing multiple Git repositories ```bash kingfisher scan /projects/mono‑repo‑dir ``` ### Scan a Git repository without validation ```bash kingfisher scan ~/src/myrepo --no-validate ``` ### Display only secrets confirmed active by third‑party APIs ```bash kingfisher scan /path/to/repo --only-valid ``` ### Output JSON and capture to a file ```bash kingfisher scan . --format json | tee kingfisher.json ``` ### Output SARIF directly to disk ```bash kingfisher scan /path/to/repo --format sarif --output findings.sarif ``` ### Pipe any text directly into Kingfisher by passing `-` ```bash cat /path/to/file.py | kingfisher scan - ``` ### Scan using a rule _family_ with one flag _(prefix matching: `--rule kingfisher.aws` loads `kingfisher.aws._`)\* ```bash # Only apply AWS-related rules (kingfisher.aws.1 + kingfisher.aws.2) kingfisher scan /path/to/repo --rule kingfisher.aws ``` ### Display rule performance statistics ```bash kingfisher scan /path/to/repo --rule-stats ``` ### Scan while ignoring likely test files `--exclude` skips any file or directory whose path matches this glob pattern (repeatable, uses gitignore-style syntax, case sensitive) ```bash # Scan source but skip likely unit / integration tests kingfisher scan ./my-project \ --exclude='[Tt]est' \ --exclude='spec' \ --exclude='[Ff]ixture' \ --exclude='example' \ --exclude='sample' ``` ### Exclude specific paths ```bash # Skip all Python files and any directory named tests kingfisher scan ./my-project \ --exclude '*.py' \ --exclude '[Tt]ests' ``` If you want to know which files are being skipped, enable verbose debugging (-v) when scanning, which will report any files being skipped by the baseline file (or via --exclude): ```bash # Skip all Python files and any directory named tests, and report to stderr any skipped files kingfisher scan ./my-project \ --exclude '*.py' \ --exclude tests \ -v ``` --- ## Scanning GitHub ### Scan GitHub organisation (requires `KF_GITHUB_TOKEN`) ```bash kingfisher scan --github-organization my-org ``` ### Scan remote GitHub repository ```bash kingfisher scan --git-url https://github.com/org/repo.git # Optionally provide a GitHub Token KF_GITHUB_TOKEN="ghp_…" kingfisher scan --git-url https://github.com/org/private_repo.git ``` --- ## Scanning GitLab ### Scan GitLab group (requires `KF_GITLAB_TOKEN`) ```bash kingfisher scan --gitlab-group my-group ``` ### Scan GitLab user ```bash kingfisher scan --gitlab-user johndoe ``` ### Scan remote GitLab repository by URL ```bash kingfisher scan --git-url https://gitlab.com/group/project.git ``` ### List GitLab repositories ```bash kingfisher gitlab repos list --group my-group ``` --- ## Environment Variables for Tokens | Variable | Purpose | | ----------------- | ---------------------------- | | `KF_GITHUB_TOKEN` | GitHub Personal Access Token | | `KF_GITLAB_TOKEN` | GitLab Personal Access Token | Set them temporarily per command: ```bash KF_GITLAB_TOKEN="glpat-…" kingfisher scan --gitlab-group my-group ``` Or export for the session: ```bash export KF_GITLAB_TOKEN="glpat-…" ``` _If no token is provided Kingfisher still works for public repositories._ --- ## Exit Codes | Code | Meaning | | ---- | ----------------------------- | | 0 | No findings | | 200 | Findings discovered | | 205 | Validated findings discovered | --- ### Update Checks Kingfisher automatically queries GitHub for a newer release when it starts and tells you whether an update is available. - **Hands-free updates** – Add `--self-update` to any Kingfisher command * If a newer version exists, Kingfisher will download it, replace the running binary, and re-launch itself with the **exact same arguments**. * If the update fails or no newer release is found, the current run proceeds as normal - **Disable version checks** – Pass `--no-update-check` to skip both the startup and shutdown checks entirely --- ### List Builtin Rules ```bash kingfisher rules list ``` ### To scan using **only** your own `my_rules.yaml` you could run: ```bash kingfisher scan \ --load-builtins=false \ --rules-path path/to/my_rules.yaml \ ./src/ ``` ### To add your rules alongside the built‑ins: ```bash kingfisher scan \ --rules-path ./custom-rules/ \ --rules-path my_rules.yml \ ~/path/to/project-dir/ ``` ## Other Examples ```bash # Check custom rules - this ensures all regular expressions compile, and can match the rule's `examples` in the YML file kingfisher rules check --rules-path ./my_rules.yml # List GitHub repos kingfisher github repos list --user my-user kingfisher github repos list --organization my-org ``` ## Notable Scan Options - `--no-dedup`: Report every occurrence of a finding (disable the default de-duplicate behavior) - `--confidence `: (low|medium|high) - `--min-entropy `: Override default threshold - `--no-binary`: Skip binary files - `--no-extract-archives`: Do not scan inside archives - `--extraction-depth `: Specifies how deep nested archives should be extracted and scanned (default: 2) - `--redact`: Replaces discovered secrets with a one-way hash for secure output - `--exclude `: Skip any file or directory whose path matches this glob pattern (repeatable, uses gitignore-style syntax, case sensitive) - `--baseline-file `: Ignore matches listed in a baseline YAML file - `--manage-baseline`: Create or update the baseline file with current findings ## Build a Baseline / Detect New Secrets There are situations where a repository already contains checked‑in secrets, but you want to ensure no **new** secrets are introduced. A baseline file lets you document the known findings so future scans only report anything that is not already in that list. The easiest way to create a baseline is to run a normal scan with the `--manage-baseline` flag (typically at a low confidence level to capture all potential matches): ```bash kingfisher scan /path/to/code \ --confidence low \ --manage-baseline \ --baseline-file ./baseline-file.yml ``` Use the same YAML file with the `--baseline-file` option on future scans to hide all recorded findings: ```bash kingfisher scan /path/to/code \ --baseline-file /path/to/baseline-file.yaml ``` See ([docs/BASELINE.md](docs/BASELINE.md)) for full detail. ## Finding Fingerprint The document below details the four-field formula (rule SHA-1, origin label, start & end offsets) hashed with XXH3-64 to create Kingfisher’s 64-bit finding fingerprint, and explains how this ID powers safe deduplication; plus how `--no-dedup` can be used shows every raw match. See ([docs/FINGERPRINT.md](docs/FINGERPRINT.md)) ## Rule Performance Profiling Use `--rule-stats` to collect timing information for every rule. After scanning, the summary prints a **Rule Performance Stats** section showing how many matches each rule produced along with its slowest and average match times. Useful when creating rules or debugging rules. ## CLI Options ```bash kingfisher scan --help ``` ## Business Value By integrating Kingfisher into your development lifecycle, you can: - **Prevent Costly Breaches** Early detection of embedded credentials avoids expensive incident response, legal fees, and reputation damage - **Automate Compliance** Enforce secret‑scanning policies across GitOps, CI/CD, and pull requests to help satisfy SOC 2, PCI‑DSS, GDPR, and other standards - **Reduce Noise, Focus on Real Threats** Validation logic filters out false positives and highlights only active, valid secrets (`--only-valid`) - **Accelerate Dev Workflows** Run in parallel across dozens of languages, integrate with GitHub Actions or any pipeline, and shift security left to minimize delays ## The Risk of Leaked Secrets Embedding credentials in code repositories is a pervasive, ever‑present risk that leads directly to data breaches: 1. **Uber (2016)** - _Incident_: Attackers stole GitHub credentials, retrieved an AWS key from a developer’s private repo, and accessed data on 57 million riders and 600 000 drivers. - _Sources_: [BBC News](https://www.bbc.com/news/technology-42075306), [Ars Technica](https://arstechnica.com/tech-policy/2017/11/report-uber-paid-hackers-100000-to-keep-2016-data-breach-quiet/) 2. **AWS** - _Incident_: An AWS engineer accidentally published log files and CloudFormation templates containing AWS key pairs (including “rootkey.csv”) to a public GitHub repo. - _Sources_: [The Register](https://www.theregister.com/2020/01/23/aws_engineer_credentials_github/), [UpGuard](https://www.upguard.com/breaches/identity-and-access-misstep-how-an-amazon-engineer-exposed-credentials-and-more) 3. **Infosys** - _Incident_: Infosys published an internal PyPI package embedding a FullAdminAccess AWS key for a Johns Hopkins data bucket; the key remained active for over a year. - _Sources_: [The Stack](https://www.thestack.technology/infosys-leak-aws-key-exposed-on-pypi/), [Tom Forbes Blog](https://tomforb.es/blog/infosys-leak/) 4. **Microsoft** - _Incident_: Microsoft’s AI research GitHub repo included an overly permissive Azure SAS token, exposing 38 TB of private data (workstation backups, 30,000+ Teams messages). - _Sources_: [Wiz Blog](https://www.wiz.io/blog/38-terabytes-of-private-data-accidentally-exposed-by-microsoft-ai-researchers), [TechCrunch](https://techcrunch.com/2023/09/18/microsoft-ai-researchers-accidentally-exposed-terabytes-of-internal-sensitive-data/) 5. **GitHub** - _Incident_: GitHub discovered its RSA SSH host private key was briefly exposed in a public repository and rotated it out of caution. - _Sources_: [GitHub Blog](https://github.blog/news-insights/company-news/we-updated-our-rsa-ssh-host-key/) Left unchecked, leaked secrets can lead to unauthorized access, pivoting within your environment, regulatory fines, and brand‑damaging incident response costs. # Benchmark Results See ([docs/COMPARISON.md](docs/COMPARISON.md)) # Roadmap - More rules - Auto-updater - Packages for Linux (deb, rpm) - Please file a [feature request](https://github.com/mongodb/kingfisher/issues) if you have specific features you'd like added # License [Apache2 License](LICENSE)