The LMVD-ID is an internal research identifier, not an official CVE identifier.
Cross-user data isolation in shared GPU serving
A compromised serving framework can violate user-data isolation through shared GPU state. GIFT evaluates per-user information-flow enforcement in vLLM and DistServe.
Paper-evaluated models(6)
Qwen 2.5 14B, Qwen 2.5 32B, Qwen 2.5 72B +3 more
- Qwen 2.5 14B
- Qwen 2.5 32B
- Qwen 2.5 72B
- OPT 13B
- OPT 30B
- OPT 66B
Description
A compromised serving framework can violate user-data isolation through shared GPU state. GIFT evaluates per-user information-flow enforcement in vLLM and DistServe.
Examples
See the primary study (opens in a new tab).
Impact
The authors demonstrate cross-user context exposure and analyze a protected monitor intended to block such flows. Their ordinary GIFT evaluation reports up to 5% request-rate overhead at matched latency. Security depends on monitor, kernel-rule and CPU-data-handling assumptions; side channels and denial of service are excluded.
Affected Systems
- Evaluated vLLM/DistServe integrations; the largest models are excluded from the single-H100 confidential-computing evaluation.
Mitigation Steps
- Patch serving software and restrict administrative access.
- Enforce per-user GPU-data ownership across kernels and cache movement.
- Revalidate isolation when kernels or serving paths change.
Evidence
Research context and confidence
- Evidence and verification
- Paper-reported; independent reproduction is not documented.
- Primary source plus a dedicated evidence section.
- Severity
- Not rated by this catalog.
- Source and publication type
- arXiv · Research preprint.
- Peer-review status is not provided by this source.
- Author and publication status
- Author metadata is not stored; see the primary paper.
- Threat model and attacker access
- Not explicitly classified; consult the primary paper..
- Related deployment categories
- No related deployment category is classified.
- Taxonomy labels only; paper-specific deployment prerequisites are not inferred.
- Affected systems
- Evaluated vLLM/DistServe integrations; the largest models are excluded from the single-H100 confidential-computing evaluation.
Research Paper
Here is a GIFT: Enforcing User Data Isolation in LLM Serving via GPU Information Flow Tracking
Primary source: arXiv. Findings are reported by the cited research and have not been independently verified.
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