CVE-2025-48943VulnerabilityPublished 30 May 2025

CVE-2025-48943: vllm · Uncaught Exception

Affects vllmSource CVE Database V5

Mentioned vulnerabilities

CVE-2025-48942

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

Data as of 25 Oct 2026, 19:02 UTC

CVSS 3.1 base score

6.5Medium

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

EPSS: 0.4% chance of exploitation in 30 days – higher than 41% 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 2026-10-25.

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-project/vllm to 0.9.0.

Affected software

Product	Affected	Fixed in
GitHubvllm-project/vllm`pkg:github/vllm-project/vllm`Other threats	Affected <0.9.0 >=0.8.0	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 prioritize upgrading vLLM to version 0.9.0 or later, where the vulnerability is patched. Until an upgrade is possible, organizations should implement input validation and sanitization controls to detect and reject malformed or suspicious regex patterns before they reach the vLLM server. Network segmentation and strict access controls should be enforced to limit who can send structured output requests to the vLLM service, reducing the risk of unauthorized or malicious inputs. Monitoring and alerting on server crashes or unusual regex processing errors can help detect attempted exploitation. Additionally, employing Web Application Firewalls (WAFs) or API gateways with regex pattern filtering capabilities can provide an additional layer of defense. Regular security assessments and code reviews focusing on exception handling and input validation in AI inference services are recommended to prevent similar issues. Finally, organizations should maintain an incident response plan tailored to availability-impacting attacks on AI infrastructure.

Description

vLLM is an inference and serving engine for large language models (LLMs). Version 0.8.0 up to but excluding 0.9.0 have a Denial of Service (ReDoS) that causes the vLLM server to crash if an invalid regex was provided while using structured output. This vulnerability is similar to GHSA-6qc9-v4r8-22xg/CVE-2025-48942, but for regex instead of a JSON schema. Version 0.9.0 fixes the issue.

Impact

For European organizations utilizing vLLM versions 0.8.0 to 0.8.x in production or research environments, this vulnerability poses a risk of service disruption due to server crashes triggered by maliciously crafted regex inputs. This can lead to denial of service conditions affecting AI-driven applications, potentially impacting business continuity, especially in sectors relying on real-time or large-scale AI inference such as finance, healthcare, and telecommunications. The disruption could degrade user experience, delay critical decision-making processes, and cause operational downtime. Since the vulnerability does not affect confidentiality or integrity, data breaches are unlikely; however, availability impacts can still have significant operational and reputational consequences. The requirement for some level of privilege to exploit may limit exposure but does not eliminate risk, especially in multi-tenant or shared environments where attackers might gain limited access. The lack of known exploits suggests a window of opportunity for proactive mitigation before active exploitation occurs.

References

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 8 Jul 2025, 14:25 UTC

WeaknessesCWE-248

Technical details

References

Community reviews

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