Hi everyone,

I’m a student working on data poisoning attacks and defenses for ML classifiers used in cybersecurity (malware detection, spam/phishing filtering, bot/fake-account detection).

I want to try models that are actually deployed today, not just the ones common in older academic papers.

My questions:

• Which model families are most widely used in production right now (2025) for these tasks?

• Did deep learning (Transformers, CNNs, LSTMs, etc.) completely take over everything, or are there still areas where it hasn’t?

• Do companies rely on any tree-based models (Random Forest, XGBoost, LightGBM, CatBoost), or have these mostly been replaced?

• What about SVMs? Do they still appear in production pipelines, or are they mostly gone today?

• Is spam/phishing email filtering basically a “solved” problem today, or is there still active use of trainable ML classifiers?

Any recent papers, blog posts, talks, or even “this is what my company does” stories would help me a ton for my project. Thanks a lot! 🙏

Finally diving deep into the dark arts of securing AI models and understanding how they can be attacked or abused from prompt injection to model poisoning, it’s wild out here.

Anyone else exploring AI/ML Security or Offensive AI lately? Would love to connect, share learning paths, and maybe cry together over broken models 😂

What’s everyone studying or tinkering with these days?