Vibe coding is how we ship now
You're not reading every line Claude generates. Neither are we. That's not lazy - it's realistic.
AI writes fast
Cursor, Copilot, Claude - they generate hundreds of lines in seconds. You review the shape, not every semicolon.
Deadlines don't wait
The feature needs to ship. The demo is tomorrow. You trust the AI and move on.
But mistakes sneak in
Hardcoded secrets. Outdated dependencies. Logic that looks right but isn't. It happens.
This isn't about blaming AI. It's about having a safety net when you move fast.
The VibeGuard workflow
Build. Scan. Fix if needed. That's it.
Build with AI
Use Cursor, Copilot, Claude, ChatGPT - whatever gets you shipping. Accept the code. Iterate. Move fast.
// Just build. We'll check it.Run the scan
One command. 11 scanners run locally on your machine. Takes about 30 seconds for most repos.
vibeguard scan .Review the diff
If it finds something real, generate a fix. You review it. You apply it. You stay in control.
vibeguard patch && vibeguard applyWhat AI tends to get wrong
These aren't edge cases. They're patterns we see constantly in AI-generated code.
Hardcoded secrets
API_KEY = "sk-live-abc123def456..."API_KEY = os.environ["API_KEY"]AI loves to include example credentials. Sometimes they're real keys from training data.
Outdated dependencies
pyyaml==5.3.1pyyaml==6.0.1AI suggests versions it was trained on, which can be years old and have known issues.
Unsafe file operations
zipfile.extractall(path)# Path traversal check addedAI writes the happy path. It doesn't think about malicious zip files with ../ paths.
Weak authentication
jwt.decode(token, options={'verify': False})jwt.decode(token, secret, algorithms=['HS256'])AI copies patterns from tutorials that prioritize simplicity over security.
SQL injection vectors
f"SELECT * FROM users WHERE id = {user_id}"cursor.execute('SELECT * FROM users WHERE id = ?', (user_id,))String interpolation is simpler. AI defaults to simple. Simple can be dangerous.
Command injection
os.system(f'convert {filename}')subprocess.run(['convert', filename], shell=False)AI doesn't anticipate that filename could be '; rm -rf /'.
What gets caught
Plain English. No CVE IDs. No jargon.
Leaked secrets
API keys, tokens, passwords in code
Risky dependencies
Packages with known issues
Code vulnerabilities
Injection, path traversal, etc.
Weak crypto
Outdated algorithms, bad patterns
Shell risks
Command injection vectors
SQL injection
Unsafe database queries
Config issues
Exposed ports, debug flags
License conflicts
Incompatible open source
You're on a deadline. We get it.
VibeGuard is designed to fit into the "ship it now" workflow, not slow it down.
For a typical repo. Larger codebases take longer, but it's still faster than a code review.
Depends on your LLM provider and the finding complexity. Most patches are instant.
Review the diff, run apply. Git checks ensure you don't break anything.
The math
If a scan takes 30 seconds and catches one leaked key that would've taken 2 hours to rotate and audit, you've saved 7,170 seconds. Run it before every deploy. It's worth it.
Everyone makes these mistakes
In 2024, security researchers found 23.8 million secrets leaked on public GitHub repos. That's not 23.8 million bad developers - that's 23.8 million moments where someone shipped faster than they reviewed.
The person who leaked an AWS key in a demo repo? They were probably having a great day building something cool. The person who committed a database password? Probably shipping a feature their users wanted.
VibeGuard isn't here to judge. It's here to catch the obvious stuff before it becomes a problem. Run it, fix what it finds, ship with confidence.
Source: GitGuardian State of Secrets Sprawl 2024
Works with whatever you're using
VibeGuard doesn't care what AI wrote your code. It just scans what's on disk.
No cloud upload. Ever.
Scans run locally
All 11 scanners run on your machine. Your code never touches our servers.
Reports stay on your machine
JSON, HTML, SARIF - all saved locally. Export to GitHub if you want, but that's your choice.
Patching uses YOUR LLM
When you run vibeguard patch, minimal context goes to the model provider you choose. You provide the API key. You pay them directly. We never see your code.