Founder and CTO Alex Rice discusses how HackerOne uses generative AI to automate security workflows and prioritizing accuracy over efficiency to achieve end-to-end outcomes.
Topics Include:
- HackerOne uses ethical hackers and AI to find vulnerabilities before criminals
- White hat hackers stress test systems to identify security weaknesses proactively
- Generative AI plays a huge role in HackerOne's security operations
- Security teams struggle with constant toil of finding and fixing vulnerabilities
- AI helps minimize toil through natural language interfaces and automation
- Both good and bad actors have access to generative AI tools
- Success requires measuring individual task inputs and outputs, not just aggregates
- Breaking down workflows into granular tasks reveals measurable AI improvements
- HackerOne deployed "Hive," their AI security agent to reduce customer toil
- Initial focus was on tasks where AI clearly outperformed humans
- Started with low-hanging fruit before tackling more complex strategic workflows
- Accuracy is the primary success metric, not just efficiency or speed
- Security requires precision; wrong fixes create bigger problems than inefficiency
- Customer acceptance and reduced time to remediation are north star metrics
- Humans remain the source of truth for validation and feedback loops
- Break down human jobs into granular AI tasks using systems thinking
- Build specific agents for individual tasks rather than entire job roles
- Keep humans accountable for end-to-end outcomes to maintain customer trust
- AWS Bedrock chosen for security, confidentiality, and data separation requirements
- Moving from efficiency improvements to entirely new AI-enabled capabilities
Participants:
Further Links:
See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/
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