USE CASE: AI CODE ASSISTANTS

SECURE AI-POWERED
CODE GENERATION

Prevent code injection, block malicious suggestions, and ensure AI coding tools can't access sensitive repos or execute harmful commands.

Key Capabilities

Code Injection Prevention

Detect and block attempts to inject malicious code through AI suggestions. Analyze generated code for security vulnerabilities before it reaches developers.

Repository Access Control

Enforce least-privilege access to codebases. Prevent AI from accessing sensitive repositories or leaking proprietary code.

Command Execution Validation

Validate shell commands and scripts before execution. Block dangerous operations like rm -rf, privilege escalation, or network exfiltration.

Secret Detection

Automatically detect and redact API keys, tokens, passwords, and other secrets in code before they're exposed to AI systems.

Dependency Analysis

Flag suggestions that include vulnerable or malicious dependencies. Integrate with vulnerability databases for real-time checks.

Developer Activity Audit

Complete logging of AI-assisted code generation. Track which suggestions were accepted and identify potential security issues.

How It Works for Code Assistants

1

Integrate

Deploy PromptGuard as a gateway for your AI coding tools. Works with Copilot, Cursor, and custom code assistants.

2

Analyze

Every code suggestion is analyzed for security issues. Malicious patterns are blocked before reaching developers.

3

Audit

Track all AI-assisted code changes. Identify security issues and demonstrate compliance.

Securing AI Code Assistants

python
from promptguard import PromptGuard

pg = PromptGuard(
    api_key="your-api-key",
    project_id="code-assistant"
)

# Configure code-specific protections
pg.configure({
    "code_mode": True,
    "code_security": {
        "detect_injection": True,
        "scan_for_vulnerabilities": True,
        "block_dangerous_patterns": True,
        "allowed_languages": ["python", "javascript", "typescript"]
    },
    "secret_detection": {
        "enabled": True,
        "types": ["api_key", "password", "token", "private_key"],
        "action": "redact"
    },
    "command_validation": {
        "enabled": True,
        "block_dangerous_commands": True,
        "require_approval_for": ["rm", "sudo", "curl", "wget"]
    },
    "repository_access": {
        "enforce_boundaries": True,
        "blocked_paths": [".env", "secrets/", "credentials/"]
    }
})

# AI code suggestions are now protected
response = pg.guard(
    prompt=code_context,
    context={
        "developer_id": developer.id,
        "repository": repo.name,
        "language": "python"
    }
)

Why PromptGuard for Code Assistants?

✓ PROMPTGUARD

  • Purpose-built code security
  • Injection pattern detection
  • Repository access controls
  • Secret detection built-in
  • Developer activity auditing

✗ OTHER SOLUTIONS

  • Generic text analysis only
  • No code-specific scanning
  • No repository awareness
  • Basic secret detection
  • Limited audit capabilities

Secure Your AI Code Assistant

Enable AI-powered development without compromising security.