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INFRAVOX AI
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Infravox automatically scans every pull request for vulnerabilities, secrets, quality issues, and compliance violations with inline AI explanations and one-click auto-fixes.

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pull request #482 api/auth/session.py
@@ -14,7 +14,7 @@ def create_session(user): token = generate_token(user.id)- query = f"INSERT INTO sessions VALUES ('{token}', {user.id})"+ query = "INSERT INTO sessions VALUES (%s, %s)"+ cursor.execute(query, (token, user.id)) db.commit()
Infravox AICritical

SQL injection: user-controlled values are interpolated directly into the query string. Use parameterized queries via cursor.execute(query, params). Auto-fix available one click applies the patch above.

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< 90sAverage scan time per PR
73%Reduction in security incidents
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Scan Coverage

Comprehensive security coverage

One platform covers every attack surface in your codebase.

Security Vulnerabilities

OWASP Top 10, CVE database, dependency audit, secret detection in code.

Code Quality

Complexity, duplication, naming conventions, dead code, anti-patterns.

Dependency Scanning

Outdated packages, known CVEs in npm/pip/maven/go.mod dependencies.

Secret Detection

API keys, tokens, private keys, passwords accidentally committed.

SAST / DAST

Static + dynamic analysis for injection, XSS, SSRF, and more.

Compliance Checks

SOC2, HIPAA, PCI-DSS, GDPR policy enforcement in infrastructure-as-code.

How it works

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01

PR / MR Opened

Developer opens a pull request on GitHub, GitLab, Bitbucket, or Azure Repos.

02

AI Scan Triggered

Infravox automatically triggers a full scan SAST, secrets, dependencies, quality.

03

Findings Annotated

Inline comments posted directly on the PR with severity, explanation, and fix.

04

Risk Score Assigned

A composite risk score (0–100) blocks merge if score exceeds your policy threshold.

05

Auto-Fix Applied

One-click auto-fix for common issues AI pushes a commit with the correction.

06

Metrics Updated

Review cycle time, issue trends, and team velocity updated in your dashboard.

AI Intelligence

Not just lint actual AI intelligence

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AI Inline Comments

Contextual, line-level suggestions with explanations not just lint warnings.

Risk Scoring

Each PR gets a risk score (0–100) based on blast radius and vulnerability severity.

Auto-Fix Suggestions

AI generates ready-to-apply patches for common security and quality issues.

PR Summary Generation

Auto-generated PR descriptions, changelogs, and test coverage summaries.

Review Time Estimates

Tells reviewers exactly how long a PR will take to review before they open it.

Team Velocity Insights

Track review cycle time, bottlenecks, repeat issues, and author patterns.

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