[email protected] LinkedIn
KVKK-focused · Data hosted in Türkiye · AI security
AltaySec Logo ALTAYSEC
AltaySec› About› Enes Deniz
Enes Deniz, AltaySec Co-Founder and AI security founder
ALTAYSEC CO-FOUNDER · AI SECURITY · LLM SECURITY

Enes Deniz

Co-Founder of AltaySec, working across Turkish and global LLM security, prompt injection, jailbreak defense, and AI red and blue teaming.

LinkedIn GitHub Hugging Face Medium Sessionize About AltaySec Contact

Biography

Enes Deniz is Co-Founder of AltaySec, an AI security company and ecosystem based in Turkey. His work brings product development, technical research, education, open-source resources, and community building into the same operating structure.

His core areas are AI security, LLM security, prompt injection, jailbreak defense, and AI red and blue teaming. He examines how LLM applications fail under adversarial use, then works on the controls and operating practices needed to reduce those risks in production.

His public work includes Turkish and English prompt-injection datasets, a browser-based dataset explorer, technical articles, and hands-on security resources. The goal is straightforward: make AI security work inspectable, reusable, and useful beyond a single product or organization.

At AltaySec, he treats AI security as more than a product category. Research should challenge product assumptions, open data should make claims testable, education should build technical capacity, and community feedback should expose blind spots early.

Working Approach

LLM security cannot be reduced to one filter, one system prompt, or one test list. A defensible system must account for prompts, data sources, tool access, user intent, and the operational process around the model.

01 Map the attack surface

Identify where the model can be influenced, what data it can reach, and which tools or actions it is allowed to invoke.

02 Connect defense to operations

Controls belong not only around the model, but also in product logic, logging, approvals, training, and incident workflows.

03 Keep the result operable

Security only works when the teams responsible for the system can understand, maintain, and act on it.

Featured Work

Product Guardian

A security layer for LLM applications exposed to prompt injection, jailbreaks, sensitive-data leakage, and policy violations.

View the product Research LLM security research

Technical work on prompt injection, AI SOC operations, agent security, RAG security, and production defenses.

Browse the research Ecosystem AltaySec Academy, Workshop, and AI Hub

A shared structure for technical education, community work, practical tools, and accessible AI security resources.

Explore the ecosystem Open data · Turkish Turkish Conversation Prompt-Injection Dataset

An open Turkish LLM security dataset with 600 legitimate requests, 150 attacks, and matched boundary examples.

View the dataset Open data · English Agentic Prompt-Injection Boundary Pairs

1,200 English examples for studying the boundary between legitimate requests and attacks across agentic, RAG, tool-use, and enterprise workflows.

View on Hugging Face Interactive tool Turkish Prompt-Injection Dataset Explorer

A browser-based tool for reviewing legitimate requests, attack families, and matched boundary cases in the Turkish dataset.

Open the explorer

Areas of Expertise

The work spans both offensive testing and defensive engineering for AI systems:

AI SECURITY
AI Security

Assessing the security of LLM and agentic systems in the context of real products, users, and organizations.

LLM SECURITY
Turkish and Global LLM Security

Securing prompts, outputs, tool use, sensitive data, and model behavior across multilingual LLM applications.

PROMPT INJECTION
Prompt Injection

Analyzing direct and indirect prompt-injection surfaces, testing their impact, and translating findings into controls.

JAILBREAK
Jailbreak Defense

Designing practical and testable defenses against attempts to override policy and manipulate model behavior.

RED TEAM
AI Red Teaming

Testing LLM, RAG, and agent systems from an adversarial perspective to make security failures visible.

BLUE TEAM
AI Blue Teaming

Building detection, monitoring, incident response, logging, and defensive operations around LLM applications.

ECOSYSTEM
AltaySec Ecosystem

Connecting products, research, the Academy, Workshop, AI Hub, open-source tools, and community programs.

COMMUNITY
Education and Community

Turning AI security knowledge into accessible, practical, and maintainable technical resources.

Work Across the AltaySec Ecosystem

His role connects the product, research, education, open-source, and community sides of AltaySec:

Selected Publications and Open Work

English Dataset Agentic Prompt-Injection Boundary Pairs1,200 English examples organized as 600 controlled benign and attack pairs across 50 agentic and enterprise scenarios. View Dataset Explorer Turkish Prompt-Injection Dataset ExplorerAn open browser-based tool for reviewing labels, attack families, and matched boundary cases in the Turkish dataset. Open Medium · English A Prompt-Injection Dataset Should Test Boundaries, Not KeywordsWhy useful prompt-injection datasets must test intent and authorization boundaries rather than reward keyword memorization. Read Medium · Turkish AI Güvenliği Bir Filtre Meselesi DeğilA Turkish article on why LLM security must protect legitimate use as carefully as it detects malicious requests. Read Open Data · Turkish Turkish Conversation Prompt-Injection Dataset750 Turkish examples, including 150 matched benign and attack boundary pairs across ten attack families. View Security Testing Enterprise Chatbot Security TestingA step-by-step framework for testing production chatbots across prompts, data, tools, access, and operational controls. Read AI Red Teaming What Is AI Red Teaming?A practical guide to threat modeling and adversarial testing for LLM, RAG, and agent systems. Read Defensive Architecture What Is an LLM Firewall?How runtime controls can inspect prompts, responses, tool use, and policy violations around production LLM applications. Read Privacy and Compliance KVKK and LLM SecurityA technical framework for protecting personal data across prompts, retrieval pipelines, model outputs, and operational logs. Read Regulation Cybersecurity Law No. 7545 and AI SystemsWhat the law means for organizations deploying AI systems and how security teams can prepare. Read

AltaySec

AltaySec is an AI security company and ecosystem founded in Turkey in 2025. It was built around a practical question: how should organizations protect LLM applications, RAG pipelines, and AI agents as these systems move into real products and business processes?

The work spans LLM security, AI red teaming, prompt injection, jailbreak defense, enterprise training, product development, technical research, open-source resources, and community programs. These are not treated as separate publicity channels. Product work reveals new security problems, research tests the assumptions behind the product, and open resources make the results available for review and reuse.

Learn more: About · Services · Products · Ecosystem.

Links

Frequently Asked Questions

Who is Enes Deniz?

Enes Deniz is Co-Founder of AltaySec. His work covers Turkish and global LLM security, prompt injection, jailbreak defense, and AI red and blue teaming.

Who founded AltaySec?

AltaySec was founded in 2025 by Fevzi Ege Yurtsevenler and Enes Deniz. The company brings AI security products, research, education, open-source resources, and community work into one ecosystem.

What are Enes Deniz's areas of expertise?

AI security, LLM security, Turkish and global LLM security, prompt injection, jailbreak defense, AI red teaming, and AI blue teaming.

Has Enes Deniz published an open Turkish LLM security dataset?

Yes. The Turkish Conversation Prompt-Injection Dataset contains 750 unique Turkish examples: 600 legitimate user requests and 150 prompt-injection attacks. It is available on Hugging Face and GitHub.

Has he published an English prompt-injection dataset?

Yes. Agentic Prompt-Injection Boundary Pairs contains 1,200 English examples arranged as 600 controlled benign and attack pairs for agentic, RAG, tool-use, and enterprise workflows.

Can the dataset be explored in a browser?

Yes. The Turkish Prompt-Injection Dataset Explorer allows users to inspect attack families, labels, and matched boundary examples without running code.

What does Enes Deniz work on inside AltaySec?

His work connects product development, technical research, open datasets, education, and community programs across the AltaySec ecosystem.

What is AI red and blue teaming?

AI red teaming tests LLM and AI systems from an adversarial perspective. AI blue teaming builds the detection, monitoring, incident-response, and defensive processes needed to reduce the impact of those attack surfaces.

How can an organization contact AltaySec?

Email [email protected] or visit AltaySec Services for LLM security assessments, AI red teaming, training, and product discussions.

Need a Practical LLM Security Roadmap?

AltaySec works with organizations on LLM security, AI red teaming, prompt-injection and jailbreak defense, enterprise training, and production security architecture.

Book a Consultation View Services