CVE-2025-48887

CVE-2025-48887 is a medium-severity inefficient regular expression (ReDoS) vulnerability in vllm (pip), affecting versions >= 0.6.4, < 0.9.0. It is fixed in 0.9.0.

Summary

A Regular Expression Denial of Service (ReDoS) vulnerability exists in the file vllm/entrypoints/openai/tool_parsers/pythonic_tool_parser.py of the vLLM project. The root cause is the use of a highly complex and nested regular expression for tool call detection, which can be exploited by an attacker to cause severe performance degradation or make the service unavailable.

Details

The following regular expression is used to match tool/function call patterns:

r"\[([a-zA-Z]+\w*\(([a-zA-Z]+\w*=.*,\s*)*([a-zA-Z]+\w*=.*\s)?\),\s*)*([a-zA-Z]+\w*\(([a-zA-Z]+\w*=.*,\s*)*([a-zA-Z]+\w*=.*\s*)?\)\s*)+\]"

This pattern contains multiple nested quantifiers (*, +), optional groups, and inner repetitions which make it vulnerable to catastrophic backtracking.

Attack Example:
A malicious input such as

[A(A=	)A(A=,		)A(A=,		)A(A=,		)... (repeated dozens of times) ...]

or

"[A(A=" + "\t)A(A=,\t" * repeat

can cause the regular expression engine to consume CPU exponentially with the input length, effectively freezing or crashing the server (DoS).

Proof of Concept:
A Python script demonstrates that matching such a crafted string with the above regex results in exponential time complexity. Even moderate input lengths can bring the system to a halt.

Length: 22, Time: 0.0000 seconds, Match: False
Length: 38, Time: 0.0010 seconds, Match: False
Length: 54, Time: 0.0250 seconds, Match: False
Length: 70, Time: 0.5185 seconds, Match: False
Length: 86, Time: 13.2703 seconds, Match: False
Length: 102, Time: 319.0717 seconds, Match: False

Impact

  • Denial of Service (DoS): An attacker can trigger a denial of service by sending specially crafted payloads to any API or interface that invokes this regex, causing excessive CPU usage and making the vLLM service unavailable.
  • Resource Exhaustion and Memory Retention: As this regex is invoked during function call parsing, the matching process may hold on to significant CPU and memory resources for extended periods (due to catastrophic backtracking). In the context of vLLM, this also means that the associated KV cache (used for model inference and typically stored in GPU memory) is not released in a timely manner. This can lead to GPU memory exhaustion, degraded throughput, and service instability.
  • Potential for Broader System Instability: Resource exhaustion from stuck or slow requests may cascade into broader system instability or service downtime if not mitigated.

A regular expression with worst-case exponential or polynomial matching time is applied to untrusted input, causing excessive CPU use. Typical impact: denial of service when input is crafted to trigger backtracking.

CVE-2025-48887 has a CVSS score of 6.5 (Medium). The vector is network-reachable, low privileges required, and no user interaction. A CVSS score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether this affects your application depends on whether the vulnerable code is present and reachable in your environment. A fixed version is available (0.9.0); upgrading removes the vulnerable code path.

Affected versions

vllm (>= 0.6.4, < 0.9.0)

Security releases

vllm → 0.9.0 (pip)

Kodem intelligence

Severity tells you how bad this could be in the worst case. It does not tell you whether you are exposed. Exploitability and impact are functions of runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A vulnerable package can sit in your dependency tree and never run.

Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter. Kodem's runtime-powered SCA identifies whether this CVE is reachable in your applications.

See it in your environment

Remediation advice

Frequently Asked Questions

  1. What is CVE-2025-48887? CVE-2025-48887 is a medium-severity inefficient regular expression (ReDoS) vulnerability in vllm (pip), affecting versions >= 0.6.4, < 0.9.0. It is fixed in 0.9.0. A regular expression with worst-case exponential or polynomial matching time is applied to untrusted input, causing excessive CPU use.
  2. How severe is CVE-2025-48887? CVE-2025-48887 has a CVSS score of 6.5 (Medium). This score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether it represents real risk in your environment depends on whether the vulnerable code is present and reachable.
  3. Which versions of vllm are affected by CVE-2025-48887? vllm (pip) versions >= 0.6.4, < 0.9.0 is affected.
  4. Is there a fix for CVE-2025-48887? Yes. CVE-2025-48887 is fixed in 0.9.0. Upgrade to this version or later.
  5. Is CVE-2025-48887 exploitable, and should I be worried? Whether CVE-2025-48887 is exploitable in your environment depends on whether the vulnerable code is present and reachable. A CVSS score is a worst-case rating; it does not account for your specific deployment, configuration, or usage patterns. Kodem, an Intelligent Application Security platform, uses runtime intelligence to show which vulnerabilities actually execute in production, so you can focus on the ones that represent real risk. Get a demo
  6. What actually determines whether CVE-2025-48887 is exploitable, and how bad it is? Exploitability and impact are not fixed properties of a CVE. They depend on runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A high CVSS score on a dependency that never runs is not the same as real risk. Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter.
  7. How do I fix CVE-2025-48887? Upgrade vllm to 0.9.0 or later.

Other vulnerabilities in vllm

CVE-2026-54233CVE-2026-54236CVE-2026-53923CVE-2026-12491CVE-2026-48746

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