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AI Security

The Hidden Vulnerabilities in Large Language Models: A Deep Dive into Prompt Injection Attacks

schedule 12 min read calendar_today November 15, 2025

Large Language Models (LLMs) have revolutionized AI applications, but they've also introduced critical security vulnerabilities that many organizations overlook. This comprehensive analysis explores prompt injection attacks, jailbreaking techniques, and data extraction methods that can compromise even the most sophisticated AI systems.

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ML Vulnerabilities

Model Poisoning: How Adversaries Corrupt Machine Learning Training Data

schedule 10 min read calendar_today November 10, 2025

Data poisoning attacks represent one of the most insidious threats to machine learning systems. By injecting malicious samples into training datasets, attackers can fundamentally compromise model behavior without direct access to the algorithm.

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Adversarial AI

Adversarial Examples: The Invisible Threat to Computer Vision Systems

schedule 8 min read calendar_today November 5, 2025

Adversarial examples—imperceptibly modified inputs that cause catastrophic misclassifications—pose an existential threat to AI safety in critical applications. From autonomous vehicles misidentifying stop signs to medical imaging systems missing cancer diagnoses.

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Privacy & Compliance

Model Inversion and Membership Inference: Privacy Risks in Machine Learning

schedule 9 min read calendar_today October 30, 2025

Your trained models may be leaking far more information than you realize. Model inversion attacks can reconstruct sensitive training data from API access alone, while membership inference determines whether specific individuals were in your training set.

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Infrastructure Security

Securing AI/ML Pipelines: From Data Ingestion to Model Deployment

schedule 11 min read calendar_today October 25, 2025

The ML pipeline itself represents a vast attack surface that extends far beyond model vulnerabilities. From compromised data lakes to poisoned package repositories, infrastructure security failures can invalidate even the most robust model defenses.

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Security Research & Insights

The Hidden Vulnerabilities in Large Language Models: A Deep Dive into Prompt Injection Attacks

Model Poisoning: How Adversaries Corrupt Machine Learning Training Data

Adversarial Examples: The Invisible Threat to Computer Vision Systems

Model Inversion and Membership Inference: Privacy Risks in Machine Learning

Securing AI/ML Pipelines: From Data Ingestion to Model Deployment

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