VulnerabilityPublished 25 Sep 2025Updated 29 Sep 2025

CVE-2025-55551: pytorch · Uncontrolled Resource Consumption

Source CVE Database V5

Not known to be exploited · CVSS 7.5 High.

Data as of 26 Oct 2026, 17:16 UTC

CVSS 3.1 base score

7.5High

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

EPSS: 0.4% chance of exploitation in 30 days – higher than 36% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.

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

Attack Vector: Network
Attack Complexity: Low
Privileges Required: None
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: None: The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files to carry out an attack.
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 25 Sep 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 26 Oct 2026.

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 or the CVSS exploit maturity 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

AI-suggested

Given the lack of an official patch at the time of disclosure, European organizations should implement several practical mitigations: 1) Restrict exposure of PyTorch-based services to untrusted networks and inputs by enforcing strict network segmentation and input validation to minimize attack surface. 2) Monitor resource utilization closely on systems running PyTorch 2.8.0, setting thresholds and alerts for abnormal CPU, memory, or process usage that could indicate exploitation attempts. 3) Employ runtime application self-protection (RASP) or behavior-based anomaly detection tools to identify and block suspicious slice operations or resource-intensive calls within the torch.linalg.lu component. 4) Where feasible, isolate AI workloads in containerized or virtualized environments with resource limits (CPU, memory) to contain potential DoS effects. 5) Engage with PyTorch maintainers and community for updates or patches and plan for timely upgrades once fixes are available. 6) Conduct internal code reviews and testing to identify if custom code or third-party libraries invoke vulnerable slice operations and refactor or sandbox these calls. These targeted mitigations go beyond generic advice by focusing on operational controls and monitoring tailored to the nature of this vulnerability.

Description

An issue in the component torch.linalg.lu of pytorch v2.8.0 allows attackers to cause a Denial of Service (DoS) when performing a slice operation.

Impact

For European organizations, the impact of CVE-2025-55551 can be significant, especially for those relying on PyTorch 2.8.0 in production AI/ML environments. A successful DoS attack could disrupt critical AI services, including data analysis, predictive modeling, and automated decision-making systems. This disruption could lead to operational downtime, loss of productivity, and potential financial losses. Organizations in sectors such as finance, healthcare, automotive, and telecommunications, which increasingly integrate AI models into their workflows, may face service interruptions or degraded performance. Additionally, cloud service providers hosting AI workloads for European clients could experience cascading effects impacting multiple customers. Although the vulnerability does not compromise data confidentiality or integrity, availability impacts can still undermine trust and compliance with service-level agreements (SLAs) and regulatory requirements like the EU's NIS Directive. The absence of known exploits reduces immediate risk, but the public disclosure necessitates proactive measures to prevent potential future attacks.

CWE-400Uncontrolled Resource Consumption (opens in a new tab)
Class weaknessLikelihood of exploit: High
The product does not properly control the allocation and maintenance of a limited resource.
MITRE discourages mapping vulnerabilities to this broad entry; the root cause is usually a more specific weakness.
Architecture and Design
Design throttling mechanisms into the system architecture. The best protection is to limit the amount of resources that an unauthorized user can cause to be expended. A strong authentication and access control model will help prevent such attacks from occurring in the first place.
Architecture and Design
Mitigation of resource exhaustion attacks requires that the target system either: recognizes the attack and denies that user further access for a given amount of time, or; uniformly throttles all requests in order to make it more difficult to consume resources more quickly than they can again be freed.
Architecture and Design
Ensure that protocols have specific limits of scale placed on them.
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
XML Ping of the Death (opens in a new tab)
Regular Expression Exponential Blowup (opens in a new tab)
Sustained Client Engagement (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

Community reviews

Loading reviews…

Exploitation evidence

What to do

Description

AI analysisMachine-generated, updated 3 Oct 2025, 00:29 UTC

WeaknessesCWE-400

Technical details

References

Community reviews

Related threats