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Precogs - AI-native Code Security 🛡️

Proactive Code Quality & Security Analysis. Detect bugs, vulnerabilities, and data leaks in your code before you even run it.

Marketplace Version Installs Discord


Precogs AI brings predictive security intelligence directly into your VS Code workflow. While traditional linters catch syntax errors, Precogs analyzes code semantics and execution paths to identify complex vulnerabilities that others miss.

✨ Key Features

  • 🛡️ Multi-Layer Scanning: Unified SAST, SCA, and Container scanning.
  • 🕵️ Secrets & PII Detection: Automatically catch 500+ secret types (keys, tokens) and sensitive personal data before they are committed.
  • 📦 Binary & SBOM: Generate machine-readable Software Bill of Materials (CycloneDX/SPDX) and analyze compiled binaries.
  • 🤖 AI Fix Suggestions: Use Gemini-powered context-aware fixes to remediate vulnerabilities with one click.
  • 🔗 Hybrid Authentication: Sign in via GitHub or use a project-specific API key for CI/CD and automation.

🚀 Quick Setup

Option 1: GitHub Login (Recommended)

  1. Install the Precogs extension from the Marketplace.
  2. Click the Precogs AI icon in the Activity Bar.
  3. Click Sign In with GitHub to authorize your account.
  4. Open any file and start scanning!

Option 2: API Key (Hybrid Auth)

For air-gapped environments or personalized setups:

  1. Generate an API Key from your Precogs Dashboard.
  2. Open VS Code Settings (Cmd+,).
  3. Search for precogs.apiKey and paste your key (pk_live_...).
  4. (Optional) Set precogs.apiEndpoint if using a self-hosted instance.

🛠️ Commands

Command Action
Precogs AI: Scan Current File Run a focused security scan on the active editor.
Scan Entire Workspace Analyze all files in your current project.
Apply AI Security Fix Preview and apply the recommended remediation.
Show Security Panel Open the summary and findings dashboard.

🌐 Supported Languages

Optimized for Python, JavaScript, TypeScript, Java, Go, C/C++, Rust, Ruby, and PHP.


❓ FAQ

Q: Does Precogs store my code?
A: No. Code is analyzed in transient memory and is never used for training models. We are SOC2 Type II compliant.

Q: How is this better than generic AI assistants?
A: Generic assistants focus on completion. Precogs focused on auditing. We use specialized security models to find race conditions, logic errors, and deep vulnerabilities.


🤝 Support & Resources

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