Why Current AI Security Frameworks Aren't Good Enough:
Early this week, we released a video discussing why governance and AI security frameworks are the most important first step when securing AI.
In this week's newsletter, we take a look at why current AI security frameworks are falling short in protecting against the unique risks of modern AI systems. Traditional frameworks, built for static systems, can't keep up with AI's dynamic, adaptive nature. Imagine an attacker embedding hidden instructions in an email that tricks an AI like Microsoft 365 Copilot into leaking sensitive data, without ever bypassing network defenses.
Or consider the real-world consequences from fatal autonomous vehicle accidents to manipulative chatbots leading to romance scams and emotional harm.
These risks are not hypothetical—they're happening now.
Here’s what you need to know to stay ahead:
1/ Intent-Based Attacks: Unlike traditional malware, modern AI attacks use language and context, like the EchoLeak vulnerability in Microsoft 365 Copilot, to manipulate systems without code.
2/ Human-Centric Risks: AI decisions now impact financial, health, and emotional outcomes, with documented cases of harm, including fatalities and psychological distress.
3/ Framework Shortcomings: Standards like ISO/IEC 27001 and NIST lack the operational depth to address AI’s unique risks, leaving 74% of organizations reporting AI-related breaches in 2024.
4/ Business-First Approach: Effective AI security must integrate seamlessly with development, prioritizing speed, automation, and adaptability to keep pace with innovation.
PurpleSec
Why Current AI Security Frameworks Aren't Good Enough:
Early this week, we released a video discussing why governance and AI security frameworks are the most important first step when securing AI.
In this week's newsletter, we take a look at why current AI security frameworks are falling short in protecting against the unique risks of modern AI systems. Traditional frameworks, built for static systems, can't keep up with AI's dynamic, adaptive nature. Imagine an attacker embedding hidden instructions in an email that tricks an AI like Microsoft 365 Copilot into leaking sensitive data, without ever bypassing network defenses.
Or consider the real-world consequences from fatal autonomous vehicle accidents to manipulative chatbots leading to romance scams and emotional harm.
These risks are not hypothetical—they're happening now.
Here’s what you need to know to stay ahead:
1/ Intent-Based Attacks: Unlike traditional malware, modern AI attacks use language and context, like the EchoLeak vulnerability in Microsoft 365 Copilot, to manipulate systems without code.
2/ Human-Centric Risks: AI decisions now impact financial, health, and emotional outcomes, with documented cases of harm, including fatalities and psychological distress.
3/ Framework Shortcomings: Standards like ISO/IEC 27001 and NIST lack the operational depth to address AI’s unique risks, leaving 74% of organizations reporting AI-related breaches in 2024.
4/ Business-First Approach: Effective AI security must integrate seamlessly with development, prioritizing speed, automation, and adaptability to keep pace with innovation.
Read the full story: purplesec.us/newsletter/current-ai-security-framew…
2 months ago | [YT] | 1