Mind the Machine

In this episode we talk about AI Pentesting. We talk about the difference with traditional cybersecurity pentesting. We also talk about benefits and drawbacks of manual and AI automatic pentesting. In the case of AI automatic pentesting, we mention some open source tools to perform it. These are some URLs related to topic mentioned in the episode: Breaking Down Adversarial Machine Learning Attacks Through Red Team Challenges https://boschko.ca/adversarial-ml/ Dreadnode’s Crucible CTF platform https://crucible.dreadnode.io/ PyRIT https://github.com/Azure/PyRIT Garak https://github.com/NVIDIA/garak Project Moonshot https://github.com/aiverify-foundation/moonshot

In this episode, we talk about ten very important security architecture patterns to protect LLM applications. Open source guardrails software mentioned during the episode: TrustyAI Llama Guard Nemo Guardrails Open source model evaluation frameworks mentioned: lm-evaluation-harness Project Moonshot Giskard

In today's podcast, we will talk about what is prompt injection. We will talk about techniques to exploit it and security controls to reduce the risk of it happening.

In this first episode of Mind the Machine I introduce the podcast and myself, Florencio Cano. The podcast will be about AI security and safety. We will talk about security for AI and also about AI for security. I hope you enjoy it! Please, don't hesitate on contacting me directly by sending me an email to florencio.cano@gmail.com or by contacting me at LinkedIn or Mastodon.