py-ocsf-models
This is a Python implementation of the OCSF models. The models are used to represent the data of the OCSF Schema defined in https://schema.ocsf.io/.
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has low install friction, carries a permissive license, and fills a specific need for OCSF schema compliance in Python. It has no known vulnerabilities and is already in use by established security tools. Install it if you need to work with OCSF-formatted cybersecurity data or integrate with platforms that expect OCSF compliance.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later (supports up to but not including 3.15)
- Low friction: pure Python wheel with only two runtime dependencies (pydantic and email-validator).
- Last release 32 days ago; repository is active with recent commits and no archived status.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions; you must include a copy of the license and state significant changes, but derivative works are permitted.
last release 2026-07-13 (32 days) · last repo commit 2026-08-01 · 38 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 137,951 downloads/mo, #11,349 on PyPI
Alternatives
Verify before relying
pip install py-ocsf-models
import py_ocsf_models
# Create and work with OCSF model instances for detection findings, compliance findings, or application security posture findings- Whether the package's OCSF coverage extends beyond the three finding types explicitly listed (Detection, Compliance, Application Security Posture)
- Performance characteristics when handling large volumes of cybersecurity events or findings
- Whether custom model extensions remain compatible with OCSF schema validation across updates
What it is and what it does
py-ocsf-models is a Python library that implements the Open Cybersecurity Schema Framework (OCSF) as a set of Pydantic-based data models. It lets you work with structured cybersecurity data—events, findings, and objects—in a standardized format that can be serialized to and from JSON. The package is built to support tools like Prowler in generating OCSF-compliant security findings that can be shared across different security platforms and tools.
The library depends on Pydantic for model validation and email-validator for email field handling. It covers Detection Findings, Compliance Findings, and Application Security Posture Findings as defined by the OCSF schema. You can create, modify, and serialize cybersecurity data structures while staying compliant with the OCSF specification, making it useful for security platforms, compliance reporting, and interoperability between tools.
Use it for
- Generate standardized OCSF-formatted security findings from custom security tools or scanners
- Consume and validate OCSF detection or compliance findings from external security platforms
- Build compliance reporting pipelines that output findings in OCSF format for regulatory or audit purposes
- Integrate security data from multiple sources into a unified OCSF-compliant data model
- Serialize and store cybersecurity events in a standardized, widely-accepted schema for long-term analysis
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has low install friction, carries a permissive license, and fills a specific need for OCSF schema compliance in Python. It has no known vulnerabilities and is already in use by established security tools. Install it if you need to work with OCSF-formatted cybersecurity data or integrate with platforms that expect OCSF compliance.
Install
py-ocsf-models on PyPI
Before you install
Low friction: pure Python wheel with only two runtime dependencies (pydantic and email-validator). Last release 32 days ago; repository is active with recent commits and no archived status.
Requires Python 3.10 or later (supports up to but not including 3.15)
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions; you must include a copy of the license and state significant changes, but derivative works are permitted.
Quickstart
pip install py-ocsf-models
import py_ocsf_models
# Create and work with OCSF model instances for detection findings, compliance findings, or application security posture findingsVerify before relying
- Whether the package's OCSF coverage extends beyond the three finding types explicitly listed (Detection, Compliance, Application Security Posture)
- Performance characteristics when handling large volumes of cybersecurity events or findings
- Whether custom model extensions remain compatible with OCSF schema validation across updates
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release <3.15,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesemail-validatorpydantic |
| Maintenance | Actively maintained 32 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 137,951 / month, #11,349 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3 |
Evidence: py_ocsf_models-0.10.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “ocsf schema python models”
- py-ocsf-modelsProvides Python models for the Open Cybersecurity Schema Framework…
- ocsf-libProvides Python tools to compile, validate, compare, and work with…
- json-schema-to-pydanticAutomatically generates Pydantic v2 models from JSON Schema…
Give your agent the search over MCP, or paste the wish link into any chat.
More Security packages
Provides Python bindings to the FreeDesktop.org Secret Service API for securely storing and retrieving passwords and secrets through GNOME Keyring, KWallet, or KeePassXC.
MSAL for Python handles OAuth2 and OpenID Connect authentication with Microsoft identity services, managing token acquisition, caching, and refresh for applications integrating with Microsoft Entra ID, Microsoft Accounts, and Azure AD B2C.
joserfc implements JOSE standards (JWS, JWE, JWK, JWT, and related RFCs) for signing, encrypting, and managing JSON-based cryptographic tokens in Python.
Authlib provides a complete implementation of OAuth 1.0, OAuth 2.0, and OpenID Connect 1.0 for building both authentication clients and servers, with built-in support for JWS, JWK, JWA, and JWT standards.
Provides low-level CFFI bindings to the official Argon2 password hashing algorithm for use by libraries and applications that need direct access to Argon2 without higher-level abstractions.
ADAL for Python authenticates applications with Azure Active Directory to obtain tokens for accessing Azure AD-protected resources.
Install only if maintaining existing code that already depends on it, and plan a migration.
See also ocsf-lib · mixbox · cloudsec-audit · pydantic-scim · cisco-ai-mcp-scanner · google-cloud-securitycenter · pqcrypto · socketsecurity · domaintools-api · kingfisher-bin