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תוכן מסופק על ידי Anton Chuvakin. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Anton Chuvakin או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
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EP251 Beyond Fancy Scripts: Can AI Red Teaming Find Truly Novel Attacks?
MP3•בית הפרקים
Manage episode 518728690 series 2892548
תוכן מסופק על ידי Anton Chuvakin. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Anton Chuvakin או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
Guest:
- Ari Herbert-Voss, CEO at RunSybil
Topics:
- The market already has Breach and Attack Simulation (BAS), for testing known TTPs. You're calling this 'AI-powered' red teaming. Is this just a fancy LLM stringing together known attacks, or is there a genuine agent here that can discover a truly novel attack path that a human hasn't scripted for it?
- Let's talk about the 'so what?' problem. Pentest reports are famous for becoming shelf-ware. How do you turn a complex AI finding into an actionable ticket for a developer, and more importantly, how do you help a CISO decide which of the thousand 'criticals' to actually fix first?
- You're asking customers to unleash a 'hacker AI' in their production environment. That's terrifying. What are the 'do no harm' guardrails? How do you guarantee your AI won't accidentally rm -rf a critical server or cause a denial of service while it's 'exploring'?
- You mentioned the AI is particularly good at finding authentication bugs. Why that specific category? What's the secret sauce there, and what's the reaction from customers when you show them those types of flaws?
- Is this AI meant to replace a human red teamer, or make them better? Does it automate the boring stuff so experts can focus on creative business logic attacks, or is the ultimate goal to automate the entire red team function away?
- So, is this just about finding holes, or are you closing the loop for the blue team? Can the attack paths your AI finds be automatically translated into high-fidelity detection rules? Is the end goal a continuous purple team engine that's constantly training our defenses?
- Also, what about fixing? What makes your findings more fixable?
- What will happen to red team testing in 2-3 years if this technology gets better?
Resource:
- Kim Zetter Zero Day blog
- EP230 AI Red Teaming: Surprises, Strategies, and Lessons from Google
- EP217 Red Teaming AI: Uncovering Surprises, Facing New Threats, and the Same Old Mistakes?
- EP68 How We Attack AI? Learn More at Our RSA Panel!
- EP71 Attacking Google to Defend Google: How Google Does Red Team
254 פרקים
MP3•בית הפרקים
Manage episode 518728690 series 2892548
תוכן מסופק על ידי Anton Chuvakin. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Anton Chuvakin או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
Guest:
- Ari Herbert-Voss, CEO at RunSybil
Topics:
- The market already has Breach and Attack Simulation (BAS), for testing known TTPs. You're calling this 'AI-powered' red teaming. Is this just a fancy LLM stringing together known attacks, or is there a genuine agent here that can discover a truly novel attack path that a human hasn't scripted for it?
- Let's talk about the 'so what?' problem. Pentest reports are famous for becoming shelf-ware. How do you turn a complex AI finding into an actionable ticket for a developer, and more importantly, how do you help a CISO decide which of the thousand 'criticals' to actually fix first?
- You're asking customers to unleash a 'hacker AI' in their production environment. That's terrifying. What are the 'do no harm' guardrails? How do you guarantee your AI won't accidentally rm -rf a critical server or cause a denial of service while it's 'exploring'?
- You mentioned the AI is particularly good at finding authentication bugs. Why that specific category? What's the secret sauce there, and what's the reaction from customers when you show them those types of flaws?
- Is this AI meant to replace a human red teamer, or make them better? Does it automate the boring stuff so experts can focus on creative business logic attacks, or is the ultimate goal to automate the entire red team function away?
- So, is this just about finding holes, or are you closing the loop for the blue team? Can the attack paths your AI finds be automatically translated into high-fidelity detection rules? Is the end goal a continuous purple team engine that's constantly training our defenses?
- Also, what about fixing? What makes your findings more fixable?
- What will happen to red team testing in 2-3 years if this technology gets better?
Resource:
- Kim Zetter Zero Day blog
- EP230 AI Red Teaming: Surprises, Strategies, and Lessons from Google
- EP217 Red Teaming AI: Uncovering Surprises, Facing New Threats, and the Same Old Mistakes?
- EP68 How We Attack AI? Learn More at Our RSA Panel!
- EP71 Attacking Google to Defend Google: How Google Does Red Team
254 פרקים
כל הפרקים
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