CVE-2025-46570: Potential Timing Side-Channel Vulnerability in vLLM’s Chunk-Based Prefix Caching
This issue arises from the prefix caching mechanism, which may expose the system to a timing side-channel attack. Description When a new prompt is processed, if the PageAttention mechanism finds a matching prefix chunk, the prefill process speeds up, which is reflected in the TTFT (Time to First Token).
Published May 28, 2025 · Updated Jun 27, 2025
Affected packages
vllm
- Ecosystem
- PyPI
- Affected
- < 0.9.0
- Fixed in
- 0.9.0
- Check
pip show vllm
Advisory details
From the GitHub Advisory Database (CC BY 4.0).
This issue arises from the prefix caching mechanism, which may expose the system to a timing side-channel attack.
Description
When a new prompt is processed, if the PageAttention mechanism finds a matching prefix chunk, the prefill process speeds up, which is reflected in the TTFT (Time to First Token). Our tests revealed that the timing differences caused by matching chunks are significant enough to be recognized and exploited.
For instance, if the victim has submitted a sensitive prompt or if a valuable system prompt has been cached, an attacker sharing the same backend could attempt to guess the victim's input. By measuring the TTFT based on prefix matches, the attacker could verify if their guess is correct, leading to potential leakage of private information.
Unlike token-by-token sharing mechanisms, vLLM’s chunk-based approach (PageAttention) processes tokens in larger units (chunks). In our tests, with chunk_size=2, the timing differences became noticeable enough to allow attackers to infer whether portions of their input match the victim's prompt at the chunk level.
Environment
- GPU: NVIDIA A100 (40G)
- CUDA: 11.8
- PyTorch: 2.3.1
- OS: Ubuntu 18.04
- vLLM: v0.5.1
Configuration: We launched vLLM using the default settings and adjusted chunk_size=2 to evaluate the TTFT.
Leakage
We conducted our tests using LLaMA2-70B-GPTQ on a single device. We analyzed the timing differences when prompts shared prefixes of 2 chunks, and plotted the corresponding ROC curves. Our results suggest that timing differences can be reliably used to distinguish prefix matches, demonstrating a potential side-channel vulnerability.
Results
In our experiment, we analyzed the response time differences between cache hits and misses in vLLM's PageAttention mechanism. Using ROC curve analysis to assess the distinguishability of these timing differences, we observed the following results:
- With a 1-token prefix, the ROC curve yielded an AUC value of 0.571, indicating that even with a short prefix, an attacker can reasonably distinguish between cache hits and misses based on response times.
- When the prefix length increases to 8 tokens, the AUC value rises significantly to 0.99, showing that the attacker can almost perfectly identify cache hits with a longer prefix.
Fixes
- https://github.com/vllm-project/vllm/pull/17045
Credited to russellb, dr75, DarkLight1337.
References
- https://github.com/vllm-project/vllm/security/advisories/GHSA-4qjh-9fv9-r85r
- https://github.com/vllm-project/vllm/pull/17045
- https://github.com/vllm-project/vllm/commit/77073c77bc2006eb80ea6d5128f076f5e6c6f54f
- https://nvd.nist.gov/vuln/detail/CVE-2025-46570
- https://github.com/pypa/advisory-database/tree/main/vulns/vllm/PYSEC-2025-53.yaml
- https://github.com/advisories/GHSA-4qjh-9fv9-r85r
How this page is made: the data panel comes from the GitHub Advisory Database, CISA’s KEV catalog, the NVD and FIRST EPSS, and updates twice a day. No analysis has been written for this entry yet. Methodology
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