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- “AI-Generated Code: A Productivity Boost or Backdoor?”
“AI-Generated Code: A Productivity Boost or Backdoor?”
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Devs Are Shipping AI-Written Code Without Review
From GitHub Copilot to ChatGPT prompts, developers integrate suggested code straight into production. Most never audit or fully understand what’s being deployed.
AI Often Repeats Insecure Patterns
LLMs learn from public code — including vulnerable examples. This means they generate outdated encryption, poor input validation, and insecure defaults.
Copyright and Licensing Are Legal Time Bombs
AI can unknowingly pull from GPL, MIT, or proprietary sources. Using generated code may introduce license conflicts that carry real legal risk.
AI-native CRM
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AI Can Accidentally Leak Secrets
If trained on internal repos, AI may surface hardcoded keys, internal endpoints, or sensitive logic. Prompting without redaction opens new paths for leaks.
Attackers Are Using AI Too
Prompt engineering helps create polymorphic malware, phishing emails, and even exploit scripts. The defensive AI arms race has a criminal side too.
Secure Use of AI Requires Policy, Not Panic
Don’t block AI tools — govern them. Define usage policies, mandate code reviews, scan outputs for risk, and educate developers. AI is here — secure it.
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