ZafiyetAI
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About
ZafiyetAI is a specialized AI Security Atlas designed to catalog and analyze vulnerabilities within machine learning and artificial intelligence ecosystems. It acts as a comprehensive repository for cybersecurity professionals, providing detailed insights into how AI systems are targeted, exploited, and compromised. By mapping out the entire attack lifecycle—from initial information gathering and research to the final operational impact—the platform helps organizations understand the unique threat landscape that comes with deploying large language models and other complex ML architectures. It serves as a foundational resource for anyone looking to bridge the gap between traditional information security and the specialized world of neural network defense. The platform categorizes threats into several key domains, including data poisoning, prompt injection, and model evasion. It explores sophisticated techniques such as "white-box" attacks, where an attacker has full knowledge of the model's internal workings, and "black-box" scenarios involving physical manipulation or adversarial data input. Users can access structured documentation and a dedicated CVE blog that tracks specific vulnerabilities, allowing for a methodical approach to red teaming and defensive hardening. The site specifically addresses modern AI-specific risks such as plugin vulnerabilities, malicious script execution within model interpreters, and meta-prompt attacks. This tool is primarily built for cybersecurity researchers, penetration testers, and AI engineers who need to secure their training pipelines and inference endpoints. It serves as a critical resource for developers integrating LLMs into their enterprise products, helping them identify potential "backdoors" or unauthorized access points that could lead to data exfiltration or total system takeover. Organizations in highly regulated industries such as finance, healthcare, and infrastructure, which are rapidly adopting AI solutions, would find this security atlas indispensable for conducting thorough risk assessments and audits. What sets ZafiyetAI apart is its structured focus on the "AI Security Atlas" concept, which mirrors frameworks like MITRE ATT&CK but is tailored specifically for the nuances of machine learning. Unlike general security blogs, it provides a rigorous taxonomy of AI-specific tactics, techniques, and procedures. By documenting real-world attack strategies—such as how attackers exploit open research data or develop specialized AI-targeting tools—it offers a proactive roadmap for defense. This focus on the intersection of data science and cybersecurity makes it an essential bookmark for the next generation of security operations.
Pros & Cons
Provides a highly specialized taxonomy for AI-specific security threats.
Covers the entire attack lifecycle from reconnaissance to final impact.
Includes a dedicated CVE blog for tracking documented vulnerabilities.
Offers deep dives into niche topics like proxy models and meta-prompt attacks.
Free access to extensive documentation on adversarial machine learning.
The primary interface and detailed documentation are currently in Turkish.
Focuses on research and educational content rather than automated scanning tools.
Does not offer a direct community forum or live support for users.
Requires significant existing cybersecurity knowledge to fully utilize the insights.
Use Cases
Security researchers can use the atlas to study emerging attack vectors like prompt injection and develop new defensive benchmarks.
AI developers can review the documentation to identify and patch potential backdoors in their training data or model inference pipelines.
Red teamers can utilize the categorized TTPs to simulate realistic attacks against corporate LLM deployments.
Compliance officers can refer to the security atlas to conduct risk assessments for AI-integrated software products.
Platform
Task
Features
• ai supply chain security mapping
• data poisoning attack insights
• plugin vulnerability documentation
• model evasion strategy database
• adversarial data research
• cve tracking for ai models
• detailed prompt injection analysis
• ai security atlas taxonomy
FAQs
What is the main purpose of the ZafiyetAI Security Atlas?
It serves as a comprehensive knowledge base for understanding and mitigating security threats specific to AI and machine learning systems. It documents various attack vectors like prompt injection and data poisoning to help researchers build more resilient models.
Does the platform provide information on specific vulnerabilities?
Yes, ZafiyetAI includes a dedicated CVE Blog and documentation that covers specific security flaws and research findings. This allows users to stay updated on the latest threats affecting different AI architectures and software.
Who can benefit from using this security resource?
The platform is designed for cybersecurity professionals, red teamers, and AI developers who need to evaluate the security posture of their ML models. It provides the tactical knowledge required to perform risk assessments and implement defensive strategies.
What types of AI attacks are covered in the atlas?
The atlas covers a wide range of tactics including initial access methods, privilege escalation via prompt injection, and evasion techniques. It also details more complex scenarios like supply chain attacks and adversarial data manipulation.
Pricing Plans
Free Resource
Free Plan• Full access to Security Atlas
• CVE Blog updates
• Prompt injection documentation
• Data poisoning research
• Attack strategy guides
• Adversarial data examples
• Model evasion techniques
• Open research data
Job Opportunities
There are currently no job postings for this AI tool.
Ratings & Reviews
No ratings available yet. Be the first to rate this tool!
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