Results for “python-cryptography”

Comprehensive cryptography guidance covering encryption algorithms, password hashing, TLS configuration, key management, and post-quantum considerations. Use when implementing encryption, choosing hashing algorithms, configuring TLS/SSL, managing cryptographic keys, or reviewing cryptographic implementations.

The central pattern.

Execute Python code in a safe sandboxed environment with 100+ pre-installed libraries for data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, and automation.

Write, review, debug, or test Python Xarray workflows for labeled N-dimensional DataArray and Dataset operations, including coordinates, alignment, indexing, groupby, resample, rolling, weighted reduction, Dask-backed execution, and NetCDF/Zarr I/O.

Write, review, debug, test, or optimize pandas Series, DataFrame, Index, groupby, merge, reshape, dtype, missing-value, and time-series code.

Provides guidance for using python-xxhash to implement fast non-cryptographic hashing, including algorithm selection, byte encoding, streaming updates, digest representation, and collision-aware identity for checksums, bucketing, and sampling.

Applies senior Python rules for typing, async, APIs, persistence, tests, packaging, and architecture.

Apply image blur effects and privacy masks using Python PIL processing. Use when you need to blur, redact faces, or mask sensitive regions in images.

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Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements.

Queries Certificate Transparency logs via crt.sh and pycrtsh to detect phishing domains, unauthorized certificate issuance, and shadow IT. Monitors newly issued certificates for typosquatting and brand impersonation using Levenshtein distance.

Generates type-safe, async-first Python 3.11+ code with full type annotations, mypy strict mode, pytest test suites, and validation via black and ruff.

Implements a simplified version of the Signal Protocol's Double Ratchet algorithm using X25519, HKDF, and AES-256-GCM for end-to-end encrypted messaging.

Design, review, debug, and test Python static types including Protocol, generics, variance, overloads, TypedDict, ParamSpec, TypeGuard, and narrowing.

Python code-quality anti-patterns and review checks: exception-hierarchy correctness, singleton identity comparison, narrow exception handling, wildcard-import avoidance, magic-number naming, and dead-local removal. Use when reviewing or self-reviewing Python code for correctness and readability defects that linters and reviewers should catch.

Python development best practices including PEP 8 style guidelines, type hints, docstring conventions, and common patterns. Use when writing or modifying Python code.

Apply comprehensive Python testing strategies using pytest, including TDD methodology, fixtures, mocking, parametrization, and coverage requirements.

Analyzes encryption algorithms, key management, and file encryption routines used by ransomware families to assess decryption feasibility, identify implementation weaknesses, and support recovery efforts.

Monitor Certificate Transparency logs using crt.sh and Certstream to detect phishing domains, lookalike certificates, and unauthorized certificate issuance targeting your organization.

Use when implementing python functionality with production-grade patterns and safeguards.

Create distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to PyPI. Use when packaging Python libraries, creating CLI tools, or distributing Python code.

Generate, store, rotate, and manage RSA key pairs following NIST SP 800-57 guidelines, including key serialization, passphrase protection, and key strength validation.

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Provides Python testing strategies using pytest, covering TDD methodology, fixtures, mocking, parametrization, and coverage requirements.

Configure and maintain Python projects, dependencies, packaging, environments, linting, formatting, type checking, testing, builds, and publishing. Use for pyproject.toml, an existing repository toolchain, or repository-level Python tooling work, not for a standalone script.

Python programming patterns and best practices

Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements.

Use this when designing Python scripts for automation, batch processing, file operations, data transformation, or internal workflows that need deterministic structure and safe environment handling.

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Implement secure JWT signing and verification with HMAC-SHA256, RSA-PSS, and EdDSA, including token expiration, claims validation, and defense against common JWT attacks.

Uses mutation testing to systematically identify gaps in test vector coverage for cryptographic algorithms, then generates new test vectors that close those gaps. Measures effectiveness by comparing mutation kill rates before and after.