Daniel Miessler

Daniel Miessler, a cybersecurity veteran and creator of the Personal AI Infrastructure (PAI) framework, dives into a transformative vision for AI. He introduces the TELOS system, which helps individuals define purpose and set goals, facilitating a new relationship with AI agents. Miessler discusses how scaffolding can turn AI models into practical assistants, the potential for AI to reshape labor and ownership, and the looming challenges of cybersecurity in an AI-driven world. He also explores the implications of activating human agency and the need for universal basic income as technology evolves.

In this discussion, Jason Haddix, an offensive security expert from Arcanum, and Daniel Miessler, founder of Unsupervised Learning, dive into the 2025 landscape of AI security. They reveal how LLMs are leaking into broader ecosystems, becoming tools for malicious prompts and exploiting vulnerabilities. The duo highlights the critical yet unsolved problem of prompt injection and the challenges posed by privacy laws on incident response. They emphasize the need for innovative threat modeling and proactive security measures to navigate this evolving danger.

Daniel Miessler, a cybersecurity expert and the creator of Unsupervised Learning, discusses the future of work in an AI-dominated world. He explores the unsettling possibility of a 'zero-employee' ideal and its implications for society and security. The conversation digs into the emotional turmoil CEOs face during layoffs and the urgent need for new economic structures like Universal Basic Income. Additionally, Miessler emphasizes the importance of curiosity and critical thinking for future workers to navigate the challenges posed by AI.

In this conversation, Daniel Miessler, a cybersecurity and AI expert and founder of Unsupervised Learning, explores the evolving landscape of work in an AI-dominated era. He argues that human labor itself may be an economic bubble, highlighting how businesses are thriving with fewer workers. Daniel discusses his experiences at Apple and the importance of building careers around problem-solving. He emphasizes context management in AI's potential and shares inspiring stories of youthful innovation, pointing toward a future where adaptation is key.

Episode 24: In this episode of Critical Thinking - Bug Bounty Podcast, we chat with Daniel Miessler and Rez0 about the emergence and potential of AI in hacking. We cover AI shortcuts and command line tools, AI in code analysis and the use of AI agents, and even brainstorm about the possible opportunities that integrating AI into hacking tools like Caido and Burp might present. Don't miss this episode packed with valuable insights and cutting-edge strategies for both beginners and seasoned bug bounty hunters alike.Follow us on twitter at: @ctbbpodcastWe're new to this podcasting thing, so feel free to send us any feedback here: info@criticalthinkingpodcast.ioShoutout to YTCracker for the awesome intro music!------ Links ------Follow your hosts Rhynorater & Teknogeek on twitter:https://twitter.com/0xteknogeekhttps://twitter.com/rhynoraterToday’s Guests:https://twitter.com/rez0__https://twitter.com/DanielMiesslerDaniel Miessler’s Unsupervised Learninghttps://danielmiessler.com/Simon Willison's Python Function Search Toolhttps://simonwillison.net/2023/Jun/18/symbex/oobabooga - web interface for modelshttps://github.com/oobabooga/text-generation-webuiState of GPThttps://karpathy.ai/stateofgpt.pdf AI Canarieshttps://danielmiessler.com/p/ai-agents-canaries GPT3.5https://community.openai.com/t/gpt-3-5-turbo-0613-function-calling-16k-context-window-and-lower-prices/263263 GPT Engineerhttps://github.com/AntonOsika/gpt-engineerTimestamps:(00:00:00) Introduction(00:05:40) Using AI for hacking: Developing hacking tools and workflow shortcuts(00:11:40) GPT Engineer and Small Developer for Security Vulnerability Mapping(00:22:40) The potential dangers of centralized vs. decentralized finance(00:24:10) Ethical hacking and circumventing ChatGPT restrictions(00:26:09) AI Agents, Reverse API, and Encoding/Decoding Tools(00:31:45) Limitations of AI in context window and processing large JavaScript files(00:36:50) Meta-prompter: Enhancing prompts for accurate responses from GPT(00:41:00) GPT-35 and the new 616K context model(45:08) Creating a loader for Burp Suite files or Caido instances(00:54:02) Hacking AI Features: Best Practices(01:00:00) AI plugin takeover and the need for verification of third-party plugins and tools