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A Practitioner’s Guide to Consuming AI
An overview of current applications of AI/ML to cybersecurity with relevant links and a vision of where things are headed.
2 Days | 4 Rooms | ~32 Hours of Talks
A threat-informed roadmap for securing Kubernetes clusters
A collection of interesting AI tools, products, resources, papers, and more I’ve come across.
A breakdown of what constitutes the software supply chain and how to secure each stage
Big list of q's, how to build a team of security builders, reviewing all PRs with an LLM
Measuring LLM's ability to find vulnerabilities, massive collection of APT reports, how to get started in memory corruption & exploitation
Interview resources, >55 talks on AI and more, a GitHub Action to limit data exfiltration
>40 awesome CloudSec talks, finding vulns with LLMs, how to use Burp like a pro
AppSec and Threat Detection interview q's, tools and tips to secure your Snowflake environment, tools to test LLMs
Queries to look for attackers in your Snowflake, AWS queries to use during incidents, how OpenAI and Apple secure AI workloads
Practical resources for offensive CI/CD research, AI threat modeling tool, bypassing CloudTrail through non-prod endpoints
Repo of detection engineering resources, Jason Haddix's security GPTs, 3 successful founders on building a security company
Subtly tamper with GHA builds, repo with offense-focused Rust PoCs, how to prioritize a detection backlog