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Secure Your LLM Against Common Vulnerabilities (Guest: Steve Wilson)

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Manage episode 378635955 series 3437240
Content provided by Andreas Welsch. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Andreas Welsch or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In this episode, Steve Wilson (Project Leader, OWASP Foundation) and Andreas Welsch discuss securing your Large Language Model against common vulnerabilities. Steve shares his findings from co-authoring the OWASP Top 10 on LLMs report and provides valuable advice for listeners looking to improve the security of their Generative AI enabled applications.
Key topics:
- What are the most important vulnerabilities of LLMs?
- What are developers underestimating about these security risks?
- How will these vulnerabilities be exploited?
- How can AI leaders and developers mitigate or prevent it?
Listen to the full episode and hear how you can:
- Balance innovation and security risks of new technologies like generative AI
- Understand the difference between direct and indirect prompt injections
- Prevent over-assigning agency to LLMs
- Establish trust boundaries and treat LLM-generated output as untrusted
Watch this episode on YouTube:
https://youtu.be/TpIowNnAcj4

Questions or suggestions? Send me a Text Message.

Support the Show.

***********
Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.

More details:
https://www.intelligence-briefing.com
All episodes:
https://www.intelligence-briefing.com/podcast
Get a weekly thought-provoking post in your inbox:
https://www.intelligence-briefing.com/newsletter

  continue reading

56 episodes

Artwork
iconShare
 
Manage episode 378635955 series 3437240
Content provided by Andreas Welsch. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Andreas Welsch or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In this episode, Steve Wilson (Project Leader, OWASP Foundation) and Andreas Welsch discuss securing your Large Language Model against common vulnerabilities. Steve shares his findings from co-authoring the OWASP Top 10 on LLMs report and provides valuable advice for listeners looking to improve the security of their Generative AI enabled applications.
Key topics:
- What are the most important vulnerabilities of LLMs?
- What are developers underestimating about these security risks?
- How will these vulnerabilities be exploited?
- How can AI leaders and developers mitigate or prevent it?
Listen to the full episode and hear how you can:
- Balance innovation and security risks of new technologies like generative AI
- Understand the difference between direct and indirect prompt injections
- Prevent over-assigning agency to LLMs
- Establish trust boundaries and treat LLM-generated output as untrusted
Watch this episode on YouTube:
https://youtu.be/TpIowNnAcj4

Questions or suggestions? Send me a Text Message.

Support the Show.

***********
Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.

More details:
https://www.intelligence-briefing.com
All episodes:
https://www.intelligence-briefing.com/podcast
Get a weekly thought-provoking post in your inbox:
https://www.intelligence-briefing.com/newsletter

  continue reading

56 episodes

All episodes

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