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Threat modeling LLM apps

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Manage episode 435570456 series 2385063
Contenido proporcionado por Changelog Media. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Changelog Media o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

If you have questions at the intersection of Cybersecurity and AI, you need to know Donato at WithSecure! Donato has been threat modeling AI applications and seriously applying those models in his day-to-day work. He joins us in this episode to discuss his LLM application security canvas, prompt injections, alignment, and more.

Leave us a comment

Changelog++ members save 9 minutes on this episode because they made the ads disappear. Join today!

Sponsors:

  • Assembly AI – Turn voice data into summaries with AssemblyAI’s leading Speech AI models. Built by AI experts, their Speech AI models include accurate speech-to-text for voice data (such as calls, virtual meetings, and podcasts), speaker detection, sentiment analysis, chapter detection, PII redaction, and more.
  • Porkbun – Go to porkbun.com to get .app, .dev, or .foo domain names at Porkbun for only $1 for the first year!
  • Changelog News – A podcast+newsletter combo that’s brief, entertaining & always on-point. Subscribe today.

Featuring:

Show Notes:

Something missing or broken? PRs welcome!

  continue reading

Capíttulos

1. Welcome to Practical AI (00:00:00)

2. Sponsor: Assembly AI (00:00:35)

3. Donato's journey in gen AI (00:04:10)

Chapter image

4. The most secure LLM (00:07:11)

5. What is a threat model? (00:08:58)

6. Commonplace AI security (00:10:38)

7. Setting up guard rails (00:14:20)

8. Sponsor: Porkbun (00:22:34)

9. Model checking (00:24:48)

10. Closed LLM endpoints (00:34:17)

11. input & output validation (00:37:17)

12. Sponsor: Changelog News (00:41:32)

13. RLHF in alignment (00:43:19)

14. Jailbreakers vs aligners (00:46:37)

15. Exciting things to explore (00:50:25)

16. Thanks for listening! (00:53:24)

17. Outro (00:53:51)

288 episodios

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iconCompartir
 
Manage episode 435570456 series 2385063
Contenido proporcionado por Changelog Media. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Changelog Media o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

If you have questions at the intersection of Cybersecurity and AI, you need to know Donato at WithSecure! Donato has been threat modeling AI applications and seriously applying those models in his day-to-day work. He joins us in this episode to discuss his LLM application security canvas, prompt injections, alignment, and more.

Leave us a comment

Changelog++ members save 9 minutes on this episode because they made the ads disappear. Join today!

Sponsors:

  • Assembly AI – Turn voice data into summaries with AssemblyAI’s leading Speech AI models. Built by AI experts, their Speech AI models include accurate speech-to-text for voice data (such as calls, virtual meetings, and podcasts), speaker detection, sentiment analysis, chapter detection, PII redaction, and more.
  • Porkbun – Go to porkbun.com to get .app, .dev, or .foo domain names at Porkbun for only $1 for the first year!
  • Changelog News – A podcast+newsletter combo that’s brief, entertaining & always on-point. Subscribe today.

Featuring:

Show Notes:

Something missing or broken? PRs welcome!

  continue reading

Capíttulos

1. Welcome to Practical AI (00:00:00)

2. Sponsor: Assembly AI (00:00:35)

3. Donato's journey in gen AI (00:04:10)

Chapter image

4. The most secure LLM (00:07:11)

5. What is a threat model? (00:08:58)

6. Commonplace AI security (00:10:38)

7. Setting up guard rails (00:14:20)

8. Sponsor: Porkbun (00:22:34)

9. Model checking (00:24:48)

10. Closed LLM endpoints (00:34:17)

11. input & output validation (00:37:17)

12. Sponsor: Changelog News (00:41:32)

13. RLHF in alignment (00:43:19)

14. Jailbreakers vs aligners (00:46:37)

15. Exciting things to explore (00:50:25)

16. Thanks for listening! (00:53:24)

17. Outro (00:53:51)

288 episodios

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