Technical Product Management Course · by Stanislav Belyaev
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AI Security Vuln Rate

3 outgoing · 1 incoming · 4 total connections

Map Detail
AI Tools

AI Security Vuln Rate

AI Security Vulnerability Rate compares the frequency of security issues found in AI-generated code versus human-written code. It helps teams assess whether AI tools are introducing additional security risk into the codebase. Tracking this metric is essential for maintaining security standards as AI adoption grows, informing decisions about where AI-generated code requires additional scrutiny or automated scanning.

Frequency of security flaws in AI code. Critical Risk: 45-51% of AI code can contain security flaws (Veracode study).

Scale Impact
👤 Solo / Pair (1–3)
0.5
👥 Team (4–15)
0.6
🏢 Department (15–100)
0.7
🏛️ Organization (100+)
0.8

45-51% of AI code has security flaws. At scale, more AI code means more attack surface. Automated scanning becomes essential but can't catch all AI-specific patterns.

3
Influences
1
Influenced by

→ Influences

Change Failure Rate (CFR)

45-51% of AI code has security flaws. Directly increases production failures and security incidents.

45-51% vulnerability rate
Veracode 2025 GenAI Code Security Report - Already Validated
Incident Frequency

AI-generated security vulnerabilities lead to production incidents.

Veracode: 45% AI code has OWASP Top 10 vulns; Georgetown CSET: 68-73% contain vulnerabilities
Veracode 2025 & Georgetown CSET
AI Trust Level

Repeated security issues erode developer trust in AI-generated code.

Trust declining 40%→29%
Stack Overflow Developer Survey 2025 - Already Validated

← Influenced by

Code Coverage

Strong test coverage catches AI security flaws before production. DORA #1 success factor.

Safety net for AI code
Security Research Best Practices
Metrics map by Stanislav Belyaev · Analysis powered by Anthropic Claude Opus 4.6 · All data validated by human experts