CVE-2025-48887VulnerabilityPublished 30 May 2025

CVE-2025-48887: vllm · ReDoS

Affects vllmSource CVE Database V5

Not known to be exploited · CVSS 6.5 Medium : upgrade to 0.9.0 when convenient.

Data as of 26 Oct 2026, 07:57 UTC

CVSS 3.1 base score

6.5Medium

How severe the flaw is on the 0–10 CVSS scale.

EPSS: 0.5% chance of exploitation in 30 days – higher than 43% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch: Available – fixed in 0.9.0

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Attack Vector: Network
Attack Complexity: Low
Privileges Required: Low
User Interaction: None
Scope: Unchanged
Confidentiality: None
Integrity: None
Availability: High

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Network: The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed, up to and including the entire Internet. Such a vulnerability is often termed 'remotely exploitable' and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).
Attack Complexity: Low: Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success against the vulnerable component.
Privileges Required: Low: The attacker is authorized with (i.e., requires) privileges that provide basic user capabilities that could normally affect only settings and files owned by a user. Alternatively, an attacker with Low privileges may have the ability to cause an impact only to non-sensitive resources.
User Interaction: None: The vulnerable system can be exploited without any interaction from any user.
Scope: Unchanged: An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.
Confidentiality: None: There is no loss of confidentiality within the impacted component.
Integrity: None: There is no loss of integrity within the impacted component.
Availability: High: There is total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable).

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 30 May 2025
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-26.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponised: Public exploit code exists in Metasploit or Exploit-DB, or CISA SSVC reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Upgrade vllm to 0.9.0.

Affected software

Product	Affected	Fixed in
PyPIvllm`pkg:pypi/vllm`Other threats	Affected <0.9.0 >=0.6.4	Fixed in 0.9.0

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

European organizations should immediately assess their deployments of vLLM and identify any instances running versions between 0.6.4 and 0.9.0. The primary mitigation is to upgrade to vLLM version 0.9.0 or later, which contains the patch addressing the ReDoS vulnerability. If immediate upgrading is not feasible, organizations should implement input validation and sanitization to detect and block maliciously crafted inputs that could trigger catastrophic backtracking. Rate limiting and request throttling can reduce the impact of potential attacks by limiting the number of regex evaluations per client or IP address. Monitoring CPU usage and response times on vLLM services can help detect ongoing exploitation attempts. Network-level protections such as Web Application Firewalls (WAFs) with custom rules to identify suspicious payloads targeting the vulnerable regex pattern may also be effective. Finally, organizations should incorporate this vulnerability into their incident response and vulnerability management workflows to ensure timely patching and detection.

Description

vLLM, an inference and serving engine for large language models (LLMs), has a Regular Expression Denial of Service (ReDoS) vulnerability in the file `vllm/entrypoints/openai/tool_parsers/pythonic_tool_parser.py` of versions 0.6.4 up to but excluding 0.9.0. 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. The pattern contains multiple nested quantifiers, optional groups, and inner repetitions which make it vulnerable to catastrophic backtracking. Version 0.9.0 contains a patch for the issue.

Impact

For European organizations utilizing vLLM versions prior to 0.9.0, this vulnerability could lead to significant service disruptions. Since vLLM is used for serving large language models, which are often integrated into customer-facing applications, research platforms, or internal AI tools, a successful ReDoS attack could degrade response times or cause complete outages. This impacts business continuity, user experience, and operational efficiency. In sectors such as finance, healthcare, and critical infrastructure where AI-driven decision-making or automation is increasingly common, availability interruptions could have cascading effects. Additionally, organizations relying on vLLM for AI services may face reputational damage if services become unreliable. The vulnerability does not expose sensitive data or allow unauthorized access, but the denial of service potential can be exploited by malicious actors to disrupt AI services, potentially as part of larger multi-vector attacks. Given the growing adoption of AI technologies in Europe, the threat is relevant to enterprises, research institutions, and cloud service providers hosting vLLM-based solutions.

CWE-1333Inefficient Regular Expression Complexity (opens in a new tab)
Base weaknessLikelihood of exploit: High
The product uses a regular expression with a worst-case computational complexity that is inefficient and possibly exponential.
Architecture and Design
Use regular expressions that do not support backtracking, e.g. by removing nested quantifiers.
System Configuration
Set backtracking limits in the configuration of the regular expression implementation, such as PHP's pcre.backtrack_limit. Also consider limits on execution time for the process.
Implementation
Do not use regular expressions with untrusted input. If regular expressions must be used, avoid using backtracking in the expression.
OWASP Cheat Sheets
File Upload (opens in a new tab)
OWASP ASVS 4.0.3
V12.1.1 (opens in a new tab)
Attack patterns
Regular Expression Exponential Blowup (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 8 Jul 2025, 14:28 UTC

WeaknessesCWE-1333

Technical details

References

Community reviews

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