When AI infrastructure becomes the target: Securing gateways and control points

Sicherheitsmeldung mit Schweregrad hoch. Sie wird laut CISA-KEV aktiv ausgenutzt und sollte priorisiert behandelt werden. Betroffene Kennungen: CVE-2025-68700, CVE-2025-69286, CVE-2026-24770, CVE-2026-28797, CVE-2026-42271. Technische Details im Tab „Originaltext“; empfohlene Schritte in der Checkliste.

Originaltext der Quelle (nicht übersetzt) – die deutsche Zusammenfassung findest du im Tab „Kurzfassung".

In this article

AI workloads are becoming high-value control pointsCase study 1: LiteLLM gateway compromiseCase study 2: RAGFlow compromiseCase study 3: Kestra compromiseMitigation and protection guidanceMITRE ATT&CK techniques observedReferencesLearn more

AI is creating a new layer of enterprise infrastructure. Gateways, retrieval platforms, orchestration services, and containerized runtimes now sit between users, applications, data, and models. These systems concentrate credentials, data access, model connectivity, and execution privileges, making them some of the most powerful components in the AI stack.

That concentration of trust is also creating new opportunities for attackers. In recent investigations, Microsoft observed activity targeting three distinct AI workloads: a LiteLLM gateway, a RAGFlow deployment, and a Kestra workflow environment. The intrusion paths varied, but the objectives were strikingly similar. Attackers sought to steal credentials, establish persistence, and monetize compromised compute resources.

The individual techniques matter, but the broader pattern matters more. Across these cases, attackers treated AI infrastructure as a control plane where credential theft, host compromise, and downstream data access can converge. As organizations continue to deploy AI systems, these platforms are becoming high value targets that deserve the same security scrutiny as other critical enterprise infrastructure.

AI workloads are becoming high-value control points

The campaign-level signal extends beyond one product. The targeted …

Vollständiger Originalartikel ↗

• Betroffenheit im eigenen Stack prüfen (CVE-2025-68700, CVE-2025-69286, CVE-2026-24770, CVE-2026-28797, CVE-2026-42271): Versionen/Komponenten abgleichen.
• Originalquelle / Hersteller-Advisory lesen: https://www.microsoft.com/en-us/security/blog/2026/08/26/when-ai-infrastructure-becomes-target-securing-gateways-control-points/
• Priorität HOCH: laut CISA-KEV aktiv ausgenutzt – bevorzugt patchen.
• Verfügbaren Patch oder Workaround einspielen und dokumentieren.
• Erkennung: Logs und Indikatoren (IoCs) auf Ausnutzung prüfen.