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GHSA-4qjh-9fv9-r85r

LowCVSS 2.6 / 10
Published May 28, 2025·Last modified Feb 4, 2026
Affected Components(0)

No affected components available

Description

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. <img src="https://github.com/user-attachments/assets/db3491e9-02b7-424c-9b6d-56f553b39f2f" alt="roc_curves_combined_block_2" width="400"/>

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
Risk Scores
Base Score
2.6

The vulnerability can be exploited over the network without needing physical access. It is difficult for an attacker to exploit this vulnerability and may require special conditions. An attacker needs basic access or low-level privileges. The attacker needs the user to perform some action, like clicking a link. The impact is confined to the system where the vulnerability exists. There is a low impact on the confidentiality of the information.

Threat Intelligence
2.4

Limited exploitation activity has been observed. Close monitoring and planned remediation are recommended.

EPSS
0.26%

The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.

Exploit
Not available

We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.

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