Sourcegraph Cody Security Scanner
Building with Cody? Make sure your AI-assisted code is secure before deployment.
Our automated security scanner analyzes your Cody application for vulnerabilities, misconfigurations, and exposed secrets. Get a comprehensive security report in minutes, not days.
AI Assistant Security Considerations
Sourcegraph Cody makes development fast, but AI-generated code often skips security best practices:
- !AI suggestions may include insecure patterns
- !Code context shared with AI service
- !Generated code needs security validation
- !Dependencies suggested may have vulnerabilities
Where Security Breaks in Sourcegraph Cody Apps
Built on Supabase (Postgres + RLS), Sourcegraph Cody applications share a recognizable fingerprint — which means attackers and automated scanners find them the same way every time. Based on real vulnerability patterns in Sourcegraph Cody deployments, the breakdown is 0 critical-impact issues, 2 high-impact, and 2 medium-or-lower.
AI suggestions may include insecure patterns
A common failure mode in Sourcegraph Cody applications: ai suggestions may include insecure patterns. Left unchecked, this can lead to data exposure, unauthorized access, or service abuse.
Fix: Scan your deployed application with a security tool that understands this stack. Address the specific findings — generic best practices don't catch platform-specific misconfigurations.
Code context shared with AI service
A common failure mode in Sourcegraph Cody applications: code context shared with ai service. Left unchecked, this can lead to data exposure, unauthorized access, or service abuse.
Fix: Scan your deployed application with a security tool that understands this stack. Address the specific findings — generic best practices don't catch platform-specific misconfigurations.
Generated code needs security validation
A common failure mode in Sourcegraph Cody applications: generated code needs security validation. Left unchecked, this can lead to data exposure, unauthorized access, or service abuse.
Fix: Require human review for security-sensitive code (auth, data access, secrets). Run automated security scanning on every AI-generated change before merging.
Dependencies suggested may have vulnerabilities
A common failure mode in Sourcegraph Cody applications: dependencies suggested may have vulnerabilities. Left unchecked, this can lead to data exposure, unauthorized access, or service abuse.
Fix: Run `npm audit` on every install. Verify suggested packages exist and have an established reputation before installing. Pin versions for reproducible builds.
What We Check
Secret Scanning
Detect exposed API keys and credentials.
Code Analysis
Review AI-generated code for vulnerabilities.
Dependency Check
Analyze suggested dependencies for security.
Database Security
Verify database access patterns.
What You'll Get
Why Sourcegraph Cody Apps Need Security Scanning
Sourcegraph Cody provides AI-powered code assistance with deep codebase understanding. This powerful context awareness speeds development but requires security awareness.
Review all AI suggestions for security implications and scan your deployed application to catch any issues before they become vulnerabilities.
How Sourcegraph Cody Security Scanning Works
Submit Your URL
Enter your Cody application URL. Our scanner automatically detects your tech stack and configures the appropriate security checks for Sourcegraph Cody.
Automated Analysis
We scan for exposed secrets, security headers, authentication issues, database misconfigurations, and Sourcegraph Cody-specific vulnerabilities. The scan typically completes in 15-20 minutes.
Get Actionable Results
Receive a detailed report with prioritized vulnerabilities, severity ratings, and step-by-step remediation guidance with code examples specific to Sourcegraph Cody.
Common Questions About Sourcegraph Cody Security
What vulnerabilities are most common in Sourcegraph Cody apps?
The top finding classes in Sourcegraph Cody apps: ai suggestions may include insecure patterns; code context shared with ai service; generated code needs security validation.
What does a VAS scan of a Sourcegraph Cody app check?
The scan probes your deployed app for the specific findings above: secret scanning, code analysis, dependency check, database security. It actually attempts each vulnerability class (not just header inspection) and reports results with severity + fix for each.
Is running a scan safe for production?
Yes. The scanner uses read-only probes against public endpoints — no data modification, no destructive tests. Scans typically finish in 15–20 minutes and will not impact application availability.
Remediation Playbook for Sourcegraph Cody
Priority-ordered fixes for the specific findings we see in Sourcegraph Cody apps. Critical items close data-exposure gaps; high items prevent compromise; medium items reduce attack surface. Applies to apps using Supabase (Postgres + RLS) — the dominant Sourcegraph Cody stack.
1. AI suggestions may include insecure patterns
Why it matters: A common failure mode in Sourcegraph Cody applications: ai suggestions may include insecure patterns. Left unchecked, this can lead to data exposure, unauthorized access, or service abuse.
How to close it: Scan your deployed application with a security tool that understands this stack. Address the specific findings — generic best practices don't catch platform-specific misconfigurations.
2. Code context shared with AI service
Why it matters: A common failure mode in Sourcegraph Cody applications: code context shared with ai service. Left unchecked, this can lead to data exposure, unauthorized access, or service abuse.
How to close it: Scan your deployed application with a security tool that understands this stack. Address the specific findings — generic best practices don't catch platform-specific misconfigurations.
3. Generated code needs security validation
Why it matters: A common failure mode in Sourcegraph Cody applications: generated code needs security validation. Left unchecked, this can lead to data exposure, unauthorized access, or service abuse.
How to close it: Require human review for security-sensitive code (auth, data access, secrets). Run automated security scanning on every AI-generated change before merging.
4. Dependencies suggested may have vulnerabilities
Why it matters: A common failure mode in Sourcegraph Cody applications: dependencies suggested may have vulnerabilities. Left unchecked, this can lead to data exposure, unauthorized access, or service abuse.
How to close it: Run `npm audit` on every install. Verify suggested packages exist and have an established reputation before installing. Pin versions for reproducible builds.
Verify the fixes stuck
Run a VAS scan after applying each fix to confirm the gap is actually closed. "I applied the fix" is not evidence — the fix may have been partial, reverted, or not deployed. Re-scanning gives you proof, and a record for compliance if you ever need it.
Secure Your Sourcegraph Cody App
Don't let vulnerabilities compromise your hard work. Security issues in Sourcegraph Cody applications can lead to data breaches, unauthorized access, and damaged user trust. The average data breach costs startups between $120,000 and $1.24 million.
Run a Starter Scan in minutes — just $9. Scan before you launch and deploy with confidence knowing your application meets security best practices.
Get Starter ScanMore on Sourcegraph Cody Security
Every angle of Cody security — from the specific findings we detect to step-by-step fixes.
Sourcegraph Cody Security Risks
Specific risks we find in Cody apps, with real-world examples.
Sourcegraph Cody Security Issues
Issues grouped by severity with detection and fix steps.
Sourcegraph Cody Best Practices
Remediation playbook derived from Cody's actual failure modes.
Is Sourcegraph Cody Safe?
Honest assessment of Cody's production readiness.
Sourcegraph Cody Security Checklist
Pre-launch checklist covering every finding class for Cody.
How to Secure Sourcegraph Cody Apps
Step-by-step hardening guide for Cody deployments.