CVE-2025-65213VulnerabilityPublished 15 Dec 2025

CVE-2025-65213: n/a

Source CVE Database V5

Not known to be exploited · CVSS 9.8 Critical.

Data as of 26 Oct 2026, 06:26 UTC

CVSS 3.1 base score

9.8Critical

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

EPSS: 0.7% chance of exploitation in 30 days – higher than 54% 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:H/I:H/A:H

Attack Vector: Network
Attack Complexity: Low
Privileges Required: None
User Interaction: None
Scope: Unchanged
Confidentiality: High
Integrity: High
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: High: There is total loss of confidentiality, resulting in all resources within the impacted component being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact.
Integrity: High: There is a total loss of integrity, or a complete loss of protection. For example, the attacker is able to modify any/all files protected by the impacted component. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to 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 15 Dec 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

AI-suggested

1. Immediately audit all uses of torch_musa in your environment to identify any instances where pickle.load() is called on user-controllable inputs, especially within compare_for_single_op() and nan_inf_track_for_single_op() functions. 2. Implement strict input validation and sanitization to ensure that only trusted and verified pickle files are processed. 3. Where possible, replace pickle-based deserialization with safer alternatives such as JSON or other secure serialization formats that do not allow code execution. 4. Employ sandboxing or containerization techniques to isolate processes that handle deserialization of external data, limiting the impact of potential exploitation. 5. Monitor network and application logs for unusual file access patterns or execution behaviors that could indicate exploitation attempts. 6. Establish strict access controls and least privilege principles for services running torch_musa to minimize the privileges available to an attacker. 7. Stay alert for official patches or updates from MooreThreads and apply them immediately upon release. 8. Consider deploying runtime application self-protection (RASP) or endpoint detection and response (EDR) solutions capable of detecting anomalous code execution related to deserialization attacks.

Description

CVE-2025-65213 is a critical unsafe deserialization vulnerability in MooreThreads torch_musa library affecting all versions. The vulnerability arises from the use of Python's pickle.load() on user-controlled file paths in the compare_for_single_op() and nan_inf_track_for_single_op() functions without proper validation. This allows attackers to craft malicious pickle files that execute arbitrary Python code upon deserialization, leading to remote code execution with the privileges of the victim process. The vulnerability has a CVSS score of 9.8, indicating a critical severity with network attack vector, no required privileges or user interaction, and full impact on confidentiality, integrity, and availability. No known exploits are currently reported in the wild. European organizations using torch_musa in AI or data processing workflows are at significant risk, especially those in countries with strong AI development sectors. Immediate mitigation involves restricting or validating input sources for pickle files, employing safer serialization methods, and isolating processes handling untrusted data. Given the critical nature and ease of exploitation, this vulnerability demands urgent attention to prevent potential widespread compromise.

Impact

For European organizations, the impact of CVE-2025-65213 is substantial, particularly for those involved in AI research, machine learning, and data analytics where torch_musa may be integrated. Successful exploitation allows attackers to execute arbitrary code remotely with the same privileges as the application, potentially leading to full system compromise, data theft, disruption of services, or lateral movement within corporate networks. Confidentiality breaches could expose sensitive intellectual property or personal data protected under GDPR, leading to regulatory penalties and reputational damage. Integrity and availability impacts could disrupt critical AI workflows or data processing pipelines, causing operational downtime and financial losses. Given the critical CVSS score and the lack of required authentication or user interaction, the threat surface is broad, increasing the likelihood of exploitation if mitigations are not applied promptly. The absence of known exploits in the wild currently provides a window for proactive defense, but the vulnerability’s nature makes it a prime target for attackers once exploit code becomes available.

Summary

CVE-2025-65213 is a critical security vulnerability identified in the MooreThreads torch_musa library, specifically within the torch_musa.utils.compare_tool module. The vulnerability stems from unsafe deserialization practices in the compare_for_single_op() and nan_inf_track_for_single_op() functions, which use Python's pickle.load() function on file paths that can be controlled by an attacker. Since pickle.load() can execute arbitrary code embedded within a serialized object, an attacker who can supply a malicious pickle file can trigger arbitrary code execution within the context of the victim process. This vulnerability does not require any privileges or user interaction and can be exploited remotely if an attacker can influence the file path input. The vulnerability affects all versions of torch_musa as no specific version restrictions are noted. The CVSS v3.1 score of 9.8 reflects its critical severity, with a network attack vector, low attack complexity, no privileges required, and no user interaction needed. The impact includes full compromise of confidentiality, integrity, and availability of the affected system. No patches or fixes are currently published, and no exploits have been reported in the wild yet. The underlying weakness corresponds to CWE-502 (Deserialization of Untrusted Data), a well-known and dangerous class of vulnerabilities. This issue is particularly concerning for environments where torch_musa is used to process untrusted or external data, such as AI model training or inference pipelines, where malicious actors could leverage this flaw to execute arbitrary commands, install malware, or pivot within networks.

CWE-502Deserialization of Untrusted Data (opens in a new tab)
Base weaknessLikelihood of exploit: MediumCWE Top 25 (2025): #15OWASP Top 10 A08:2025: Software or Data Integrity Failures (opens in a new tab)
The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.
Architecture and Design · Implementation
If available, use the signing/sealing features of the programming language to assure that deserialized data has not been tainted. For example, a hash-based message authentication code (HMAC) could be used to ensure that data has not been modified.
Implementation
When deserializing data, populate a new object rather than just deserializing. The result is that the data flows through safe input validation and that the functions are safe.
Implementation
Explicitly define a final object() to prevent deserialization.
OWASP Cheat Sheets
Abuse Case (opens in a new tab)
Deserialization (opens in a new tab)
XML Security (opens in a new tab)
XML External Entity Prevention (opens in a new tab)
Software Supply Chain Security (opens in a new tab)
OWASP ASVS 4.0.3
V1.5.2 (opens in a new tab)
V5.5.3 (opens in a new tab)
V5.5.1 (opens in a new tab)
Attack patterns
Object Injection (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

github.com/MooreThreads/torch_musa/issues/110 (opens in a new tab)

Community reviews

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Exploitation evidence

What to do

Description

AI analysisMachine-generated, updated 22 Dec 2025, 19:29 UTC

WeaknessesCWE-502

Technical details

References

Community reviews

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