codeshield
Shield against LLM generated insecure code
Decision gist · record as of 2026-08-14
Yes, if you deploy LLM-assisted code generation in production or development workflows. CodeShield fills a real gap: LLMs can generate insecure code even when fine-tuned for safety, and this package provides a lightweight, low-latency filter to catch it. Active maintenance, permissive license, and no known vulnerabilities support adoption. Install only if you actually integrate LLM code output into your pipeline; it's not a general-purpose static analyzer.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.8 or later.
- semgrep must be installed and functional for static analysis to work across the supported programming languages.
- Low install friction with a pure Python wheel and only two runtime dependencies (pyyaml and semgrep).
License · maintenance · safety
permissive license (permissive) — Licensed under MIT (permissive), so you can use, modify, and distribute CodeShield freely in commercial and private projects without restriction.
last release 2024-04-19 (847 days) · last repo commit 2026-08-14 · 4,348 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 110,025 downloads/mo, #12,486 on PyPI
Alternatives
Verify before relying
pip install codeshield
from codeshield import CodeShield
shield = CodeShield()
result = shield.scan(code_snippet)- Exact API surface and configuration options for customizing scan behavior and response modes (warning vs. blocking).
- Whether the package includes pre-built rules for all 50+ CWEs or requires external configuration.
- Performance characteristics on code snippets larger than typical LLM outputs.
- Integration examples with specific IDEs or LLM frameworks beyond the referenced notebook.
What it is and what it does
CodeShield is a runtime security filter designed to intercept insecure code generated by large language models before it enters production. It acts as a guardrail in workflows where LLMs assist with code generation—whether as IDE plugins, chatbot code suggestions, or automated coding assistants—flagging or blocking code that violates secure coding practices.
The package uses static analysis (via semgrep and the Insecure Code Detector library) to scan code across multiple programming languages for patterns matching over 50 CWEs. It employs a two-layer scanning strategy: a fast pattern check flags suspicious code, and only flagged content undergoes comprehensive analysis. According to the documentation, this design keeps 99% of benign requests under 70ms latency, with p90 latency at 450ms for thorough scans, making it suitable for production environments where both security and performance matter.
Use it for
- Block insecure code suggestions in IDE-integrated AI coding assistants before developers see them.
- Add warnings or reject unsafe code snippets returned by LLM chatbots used for coding help.
- Scan code generated by automated LLM pipelines to enforce secure coding hygiene before merge.
- Validate code produced by internal or third-party LLM services in CI/CD workflows.
- Detect common insecure patterns (CWE violations) in bulk-generated code for compliance audits.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you deploy LLM-assisted code generation in production or development workflows.
CodeShield fills a real gap: LLMs can generate insecure code even when fine-tuned for safety, and this package provides a lightweight, low-latency filter to catch it. Active maintenance, permissive license, and no known vulnerabilities support adoption. Install only if you actually integrate LLM code output into your pipeline; it's not a general-purpose static analyzer.
Install
codeshield on PyPI
Before you install
Low install friction with a pure Python wheel and only two runtime dependencies (pyyaml and semgrep). The package is actively maintained with recent commits and has accumulated 4348 repository stars, indicating established community adoption.
Requires Python 3.8 or later. semgrep must be installed and functional for static analysis to work across the supported programming languages.
License in practice
Licensed under MIT (permissive), so you can use, modify, and distribute CodeShield freely in commercial and private projects without restriction.
Quickstart
pip install codeshield
from codeshield import CodeShield
shield = CodeShield()
result = shield.scan(code_snippet)Verify before relying
- Exact API surface and configuration options for customizing scan behavior and response modes (warning vs. blocking).
- Whether the package includes pre-built rules for all 50+ CWEs or requires external configuration.
- Performance characteristics on code snippets larger than typical LLM outputs.
- Integration examples with specific IDEs or LLM frameworks beyond the referenced notebook.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagespyyamlsemgrep |
| Maintenance | Actively maintained 847 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 110,025 / month, #12,486 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3 |
Evidence: codeshield-1.0.1-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 › “llm code security filtering”
- codeshieldCodeShield filters code generated by LLMs to detect and block…
- llm-guardLLM Guard provides input and output scanning for Large Language…
- vannaVanna converts natural language questions into SQL queries and…
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 guardrails-ai · openai-guardrails · pydantic-ai-shields · llm-guard · cisco-ai-mcp-scanner · smg-grpc-servicer · njsscan · cisco-ai-skill-scanner · mobsfscan · guarddog