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Model Evasion Attacks | Episode 32
In this episode of BHIS Presents: AI Security Ops, the panel explores the stealthy world of model evasion attacks, where adversaries manipulate inputs to trick AI classifiers into misclassifying malicious activity as benign. From image classifiers to malware detection and even LLM-based systems, learn how attackers exploit decision boundaries and why this matters for cybersecurity.

We break down:
- What model evasion attacks are and how they differ from data poisoning
- How attackers tweak features to bypass classifiers (images, phishing, malware)
- Real-world tactics like model extraction and trial-and-error evasion
- Why non-determinism in AI models makes evasion harder to predict
- Advanced threats: model theft, ablation, and adversarial AI
- Defensive strategies: adversarial training, API throttling, and realistic expectations
- Future outlook: regulatory trends, transparency, and the ongoing arms race

Whether you’re deploying EDR solutions or fine-tuning AI models, this episode will help you understand why evasion is an enduring challenge, and what you can do to defend against it.


#AISecurity #ModelEvasion #Cybersecurity #BHIS #LLMSecurity #aithreats

Brought to you by Black Hills Information Security 

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Joff Thyer - https://blackhillsinfosec.com/team/joff-thyer/

Derek Banks - https://www.blackhillsinfosec.com/team/derek-banks/

Brian Fehrman - https://www.blackhillsinfosec.com/team/brian-fehrman/

Bronwen Aker - http://blackhillsinfosec.com/team/bronwen-aker/

Ben Bowman - https://www.blackhillsinfosec.com/team/ben-bowman/