🚨How Hackers Poison AI Models | APT-Style Attacks on Phishing Detection Explained | Mohammad Ahmad🔍🧠

⚠️ Disclaimer: This video is for educational and awareness purposes only. We do not encourage or promote any unethical activities. All demonstrations and discussions are done in a controlled lab environment to spread knowledge and security best practices.
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🎙️ Podcast Episode Overview:
🚨 AI Dataset Poisoning in Cybersecurity | How Hackers Attack Machine Learning Models | Featuring SOC IR Expert Mohammad Ahmad | MITRE ATLAS AML.T0020

In this explosive episode of Cyber Mind Space, we uncover one of the most dangerous and underexplored threats in cybersecurity and artificial intelligence — AI dataset poisoning.

Joined by Mohammad Ahmad, a leading SOC & Incident Response expert at Trustwave, we expose how attackers manipulate training datasets to poison machine learning models and bypass modern AI-driven phishing detection systems.

📉 Poisoned data = compromised AI.
🧠 Corrupt inputs = broken trust in ML systems.

🎯 In this episode, you'll learn:

What is dataset poisoning in machine learning and how it impacts AI security

How attackers inject backdoors, model bias, and undetectable vulnerabilities

Step-by-step analysis of a real Kaggle phishing detection dataset

Tactics used in adversarial machine learning, model evasion, and data manipulation

Direct mapping with MITRE ATLAS technique AML.T0020 (Poison Training Data)

💡 This episode is ideal for:

Cybersecurity professionals

AI/ML engineers & researchers

Threat hunters & red teamers

SOC analysts & blue teams

Ethical hackers & penetration testers

🧠 Stay ahead of the curve in:
AI in cybersecurity, data poisoning attacks, machine learning model security, adversarial AI, SOC operations, phishing protection, AI threat modeling, and AI dataset poisoning, machine learning security, adversarial machine learning, data poisoning attacks, phishing detection bypass, MITRE ATLAS AML.T0020, poisoned datasets, SOC expert, cybersecurity podcast, red teaming AI, Kaggle phishing dataset, artificial intelligence in cybersecurity, training data attacks, model evasion, AI security risks

🔔 Subscribe now for expert-led breakdowns on AI, threat intelligence, red teaming, and the dark side of machine learning.
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📚 Study Material & Dataset Used:
We used the Web Page Phishing Detection Dataset from Kaggle to demonstrate how even public datasets can be potential attack vectors in ML pipelines.
📂 Dataset URL:
🔗 www.kaggle.com/datasets/shash...
🔍 MITRE ATLAS Technique Referenced:
AML.T0020 – Poison Training Data
Learn more: atlas.mitre.org/techniques/AM...
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👨‍💻 About the Guest – Mohammad Ahmad:
🎓 Master's in Cybersecurity
🛡️ SOC & IR Expert at Trustwave
🌐 LinkedIn: / m-ahmad95
💬 He actively drives security operations excellence and threat detection across enterprises globally.
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