Framework-Zusammenfassung, 2 Min. Lesezeit
ISO/IEC 42001 makes AI governance auditable
ISO/IEC 42001 does not prescribe seven named documents; it requires controlled evidence that AI risks, responsibilities, and decisions are managed.
AI security
Thema „ai“
13 Beiträge zu diesem Thema.
Artikel und Videos erscheinen auf Englisch.
Framework-Zusammenfassung, 2 Min. Lesezeit
Secure AI agents by their traits, not their labels
The Cloud Security Alliance's trait-based approach maps agent behavior and architectural choices to concrete security risks and controls.
AI security
Essay, 4 Min. Lesezeit
Why AI-assisted compliance review still needs a human signature
AI can read a marketing document against MiFID II requirements faster than any human. It still shouldn't be the one who approves it. That's a design principle, not a limitation.
Building CompylotAI
Framework-Zusammenfassung, 2 Min. Lesezeit
The OWASP AI Exchange connects AI threats to controls
The OWASP AI Exchange provides a lifecycle map for moving from AI governance and threat analysis to testing, operations, and residual-risk decisions.
AI security
Framework-Zusammenfassung, 2 Min. Lesezeit
Adversarial machine learning needs a common language
NIST's attack taxonomy helps security teams connect adversary goals, access, lifecycle stages, and mitigations across predictive and generative AI.
AI security
Framework-Zusammenfassung, 2 Min. Lesezeit
Red teaming generative AI is a lifecycle discipline
Microsoft's experience across 100 generative-AI products shows why testing must follow real system risks, not a generic attack checklist.
AI security
Framework-Zusammenfassung, 2 Min. Lesezeit
The OWASP LLM Top 10 is an application-security list
OWASP's 2025 list shows that securing an LLM application requires architecture, testing, and development controls around the model.
AI security
Framework-Zusammenfassung, 2 Min. Lesezeit
The EU AI Act turns AI governance into an operating obligation
The EU AI Act is not only a legal classification scheme; it requires organizations to connect AI risk, data governance, oversight, and evidence.
EU security and compliance
Framework-Zusammenfassung, 2 Min. Lesezeit
Managing generative-AI risk with the NIST profile
NIST's Generative AI Profile extends the AI RMF with concrete actions for governance, data provenance, testing, and incident disclosure.
AI security
Framework-Zusammenfassung, 2 Min. Lesezeit
AI security is governance in action
BaFin's central point is simple: AI security has to cover the whole decision process, not just the model.
AI security
Framework-Zusammenfassung, 2 Min. Lesezeit
Putting Google's Secure AI Framework into practice
Google's SAIF implementation guide turns six security principles into an organizational process for designing, deploying, and operating AI safely.
AI security
Framework-Zusammenfassung, 2 Min. Lesezeit
Google SAIF: six elements for secure AI
Google's one-page SAIF summary provides a useful executive test for whether AI security covers architecture, operations, and business risk.
AI security
Framework-Zusammenfassung, 2 Min. Lesezeit
NIST AI RMF: govern, map, measure, and manage
The NIST AI RMF gives organizations a lifecycle structure for connecting AI governance, assets, architecture, measurement, and risk treatment.
AI security
Neue Beiträge direkt erhalten
Folgen Sie uns dort, wo Sie lesen. Keine Newsletter-Anmeldung nötig.