Results for “python-cryptography”

Implement AES-256-GCM encryption for files and data at rest, including key derivation, IV management, and authenticated encryption.

Secure Python services against secret leakage, injection, unsafe subprocess calls, and dependency drift. Use when handling env vars, tokens, SQL, file paths, shell commands, auth flows, or Python security gates.

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.

Analyzes cryptographic code to detect operations that leak secret data through execution timing variations, supporting multiple languages.

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.

Use when writing or editing typed Python scripts, parsing untyped input, choosing lightweight data shapes, or resolving common checker errors without project-scale type-system research.

Systematically reviews an application's use of cryptographic primitives, protocols, and key management to identify vulnerabilities such as weak algorithms, insecure modes, hardcoded keys, insufficient entropy, and protocol misconfigurations.

Security Practices — Cryptographic Safety, Memory Zeroization & Hardened I/O

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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.

Core Python 3.11+ language standards for typing, dataclasses, imports, pathlib, and stdlib-first code. Use for idiomatic language constructs in Python modules or stubs; defer pytest fixtures, database/client configuration, subprocess security, and other specialized concerns.

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

Mine, stake, and manage LITCOIN tokens on Base blockchain using the Python SDK, with options for comprehension mining or LLM-powered research mining.

Implements security-sensitive changes with conservative trust boundaries, secret protection, tests, and verification.

Assess SSL/TLS server configurations using the sslyze Python library to evaluate cipher suites, certificate chains, protocol versions, HSTS headers, and known vulnerabilities like Heartbleed and ROBOT.

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

利用python，指定某个arxiv_id/url， 基于 LLM Agent 对这篇arxiv论文进行分类与深度阅读，直接print打印阅读笔记

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.