fevziegeyurtsevenler

fevziegeyurtsevenler / LLM-Security-Nedir

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Fevzi Ege Yurtsevenler tarafından hazırlanan, Türkiye'nin ilk kapsamlı LLM Güvenliği giriş rehberi. Yapay zeka güvenliğinin temellerini ve yeni saldırı yüzeylerini keşfedin.

altaysec.com.tr ai ai-security-turkey artificial-intelligence cyber-security llm
10
0
100% credibility
Found May 05, 2026 at 10 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
AI Summary

This GitHub repository hosts a Turkish educational article introducing LLM Security, explaining threats to large language models, differences from traditional cybersecurity, and defense strategies.

How It Works

1
🔍 Discover the Guide

You stumble upon this friendly guide while searching for info on keeping AI chatbots safe.

2
📖 Start Reading the Intro

You dive into the opening story about how new tech like AI brings fresh safety challenges, just like the web did years ago.

3
💡 Grasp What LLM Security Means

The lightbulb moment hits: this is all about protecting smart AI language tools from tricks and hacks that could spill secrets or cause trouble.

4
📋 Explore Attacks and Fixes

You scan the handy lists of sneaky attacks like prompt tricks and strong defenses like input checks and watchdogs.

5
🔗 Check Trusted Sources

You note the links to big names like OWASP for deeper dives into real-world safety tips.

🎉 Feel Empowered on AI Safety

Now you understand why AI security matters for banks, hospitals, and more, ready to spot risks in everyday AI tools.

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AI-Generated Review

What is LLM-Security-Nedir?

LLM-Security-Nedir is Turkey's first comprehensive intro guide to LLM security, written by Fevzi Ege Yurtsevenler, covering yapay zeka security temellerini and yeni saldırı yüzeyleri like prompt injection, jailbreak, and data poisoning. It breaks down what LLM security nedir for developers building AI systems, explaining attacks, defenses like guardrails and output filtering, and why it differs from classic cybersecurity. Users get a clear Turkish-language rehberi with OWASP references, attack tables, and a roadmap to deeper topics—no code, just practical knowledge to secure LLM apps.

Why is it gaining traction?

It stands out as the ilk Turkish resource on LLM security, filling a gap for Ege-region devs and beyond who need accessible explanations without English barriers. The hook is its structured overview of real-world threats like RAG poisoning and agentic attacks, plus Turkey-specific context on finance and public sector adoption. Developers notice the concise tables, stats from 2025 reports, and forward links to series on OWASP LLM Top 10.

Who should use this?

AI engineers in Turkey integrating LLMs into customer support or code assistants, seeking to grasp security basics before production. Security analysts transitioning to yapay zeka threats, especially those handling prompt-based systems in e-commerce or healthcare. Newcomers like Fevzi Ege Yurtsevenler fans wanting a quick ramp-up on LLM vs. ML security distinctions.

Verdict

With 10 stars and 1.0% credibility score, it's an early-stage doc-only repo lacking code or tools, but a solid, constructive starting point for Turkish LLM security education—bookmark if you're local, skip for advanced implementations.

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