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Authors: Rami Elron
2021-09-24

tldr - powered by Generative AI

The presentation discusses the importance of better software security through auto remediation and the challenges associated with it. It emphasizes the need for trustworthiness, accuracy, and insightfulness in auto remediation.
  • Auto remediation is about facilitating the process of remediation and reducing the number of unattended issues.
  • Standardized fixed approach helps with triaging and prioritization.
  • Auto remediation can combat the security knowledge gap and better allocate resources.
  • Trust is important in auto remediation and it must be designed to accommodate the developer's concerns.
  • Auto remediation should be proactive, accurate, and reduce noise and ambiguity.
  • Insightfulness is important in auto remediation to provide suggestions that garner more trust from the end user.
  • Auto remediation must drive results and be developer-centric.
  • The challenges associated with auto remediation include the proper placement and annotation of sanitization and the potential for inadvertent changes to the logic of the application.
  • Traditional remediation approaches can be confounding and irrelevant to developers.
  • Auto remediation should embrace a developer's standpoint and provide confirmation that the solution will work.