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AI Risk

Network Devices

"The training of LLMs often relies on distributed network systems [171], [172]. During the transmission of gradients through the links between GPU server nodes, significant volumetric traffic is generated. This traffic can be susceptible to disruption by burst traffic, such as pulsating attacks [161]. Furthermore, distributed training frameworks may encounter congestion issues [173]."

AI Risk2. Privacy & Security2.2 > AI system security vulnerabilities and attacks1 - Pre-deployment

Record summary

A quick snapshot of what this page covers.

Techniques3Attack methods connected to this risk.
Mitigations0Defenses that may help with related attacks.
Domain2. Privacy & SecurityThe broad risk area this belongs to.

Risk profile

How this risk is described and categorized.

Domain2. Privacy & Security
Subdomain2.2 > AI system security vulnerabilities and attacks
Entity3 - Other
Intent2 - Unintentional
Timing1 - Pre-deployment
CategoryHardware Vulnerabilities
SubcategoryNetwork Devices

Suggested mitigations

Defenses that may help with related attacks.

No propagated mitigations. No defense is available through the connected attack methods.

Source

Research source for this risk, when available.