Summary
A recent review identified several regular expressions in the vllm codebase that are susceptible to Regular Expression Denial of Service (ReDoS) attacks. These patterns, if fed with crafted or malicious input, may cause severe performance degradation due to catastrophic backtracking.
1. vllm/lora/utils.py Line 173
|
match = re.search(r"\((.*?)\)\$?$", load_modules) |
Risk Description:
- The regex
r"\((.*?)\)\$?$"
matches content inside parentheses. If input such as ((((a|)+)+)+)
is passed in, it can cause catastrophic backtracking, leading to a ReDoS vulnerability.
- Using
.*?
(non-greedy match) inside group parentheses can be highly sensitive to input length and nesting complexity.
Remediation Suggestions:
- Limit the input string length.
- Use a non-recursive matching approach, or write a regex with stricter content constraints.
- Consider using possessive quantifiers or atomic groups (not supported in Python yet), or split and process before regex matching.
2. vllm/entrypoints/openai/tool_parsers/phi4mini_tool_parser.py Line 52
|
pattern = r'functools\[(.*?)\]' |
Risk Description:
- The regex
r'functools\[(.*?)\]'
uses .*?
to match content inside brackets, together with re.DOTALL
. If the input contains a large number of nested or crafted brackets, it can cause backtracking and ReDoS.
Remediation Suggestions:
- Limit the length of
model_output
.
- Use a stricter, non-greedy pattern (avoid matching across extraneous nesting).
- Prefer
re.finditer()
and enforce a length constraint on each match.
3. vllm/entrypoints/openai/serving_chat.py Line 351
|
param_match = re.search(r'.*"parameters":\s*(.*)', |
Risk Description:
- The regex
r'.*"parameters":\s*(.*)'
can trigger backtracking if current_text
is very long and contains repeated structures.
- Especially when processing strings from unknown sources,
.*
matching any content is high risk.
Remediation Suggestions:
- Use a more specific pattern (e.g., via JSON parsing).
- Impose limits on
current_text
length.
- Avoid using
.*
to capture large blocks of text; prefer structured parsing when possible.
4. benchmarks/benchmark_serving_structured_output.py Line 650
|
actual = re.search(r'\{.*\}', actual).group() |
Risk Description:
- The regex
r'\{.*\}'
is used to extract JSON inside curly braces. If the actual
string is very long with unbalanced braces, it can cause backtracking, leading to a ReDoS vulnerability.
- Although this is used for benchmark correctness checking, it should still handle abnormal inputs carefully.
Remediation Suggestions:
- Limit the length of
actual
.
- Prefer stepwise search for
{
and }
or use a robust JSON extraction tool.
- Recommend first locating the range with simple string search, then applying regex.
Fix
Summary
A recent review identified several regular expressions in the vllm codebase that are susceptible to Regular Expression Denial of Service (ReDoS) attacks. These patterns, if fed with crafted or malicious input, may cause severe performance degradation due to catastrophic backtracking.
1. vllm/lora/utils.py Line 173
vllm/vllm/lora/utils.py
Line 173 in 2858830
Risk Description:
r"\((.*?)\)\$?$"
matches content inside parentheses. If input such as((((a|)+)+)+)
is passed in, it can cause catastrophic backtracking, leading to a ReDoS vulnerability..*?
(non-greedy match) inside group parentheses can be highly sensitive to input length and nesting complexity.Remediation Suggestions:
2. vllm/entrypoints/openai/tool_parsers/phi4mini_tool_parser.py Line 52
vllm/vllm/entrypoints/openai/tool_parsers/phi4mini_tool_parser.py
Line 52 in 2858830
Risk Description:
r'functools\[(.*?)\]'
uses.*?
to match content inside brackets, together withre.DOTALL
. If the input contains a large number of nested or crafted brackets, it can cause backtracking and ReDoS.Remediation Suggestions:
model_output
.re.finditer()
and enforce a length constraint on each match.3. vllm/entrypoints/openai/serving_chat.py Line 351
vllm/vllm/entrypoints/openai/serving_chat.py
Line 351 in 2858830
Risk Description:
r'.*"parameters":\s*(.*)'
can trigger backtracking ifcurrent_text
is very long and contains repeated structures..*
matching any content is high risk.Remediation Suggestions:
current_text
length..*
to capture large blocks of text; prefer structured parsing when possible.4. benchmarks/benchmark_serving_structured_output.py Line 650
vllm/benchmarks/benchmark_serving_structured_output.py
Line 650 in 2858830
Risk Description:
r'\{.*\}'
is used to extract JSON inside curly braces. If theactual
string is very long with unbalanced braces, it can cause backtracking, leading to a ReDoS vulnerability.Remediation Suggestions:
actual
.{
and}
or use a robust JSON extraction tool.Fix