CVE-2025-50461VulnerabilityPublished 19 Aug 2025

CVE-2025-50461: n/a

Source CVE Database V5

Not known to be exploited · CVSS 6.5 Medium.

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: 0.5% chance of exploitation in 30 days – higher than 43% 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:L/I:L/A:N

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

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: Low: There is some loss of confidentiality. Access to some restricted information is obtained, but the attacker does not have control over what information is obtained, or the amount or kind of loss is limited. The information disclosure does not cause a direct, serious loss to the impacted component.
Integrity: Low: Modification of data is possible, but the attacker does not have control over the consequence of a modification, or the amount of modification is limited. The data modification does not have a direct, serious impact on the impacted component.
Availability: None: There is no impact to availability within the impacted component.

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 19 Aug 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

AI-suggested

To mitigate this vulnerability, European organizations should take several specific actions beyond generic patching advice: 1) Immediately audit and restrict write permissions on directories where model files are stored or loaded, ensuring only trusted users can place files there. 2) Implement strict validation and integrity checks on all model files before loading, such as cryptographic signatures or hashes, to prevent unauthorized or tampered files from being processed. 3) Modify or patch the model_merger.py script to use torch.load() with weights_only=True if feasible, or employ safer deserialization methods that avoid executing arbitrary code embedded in model files. 4) Educate users and developers about the risks of loading untrusted model files and enforce policies that prohibit downloading models from unverified sources. 5) Monitor systems for unusual file placement activities and anomalous script executions that could indicate exploitation attempts. 6) Engage with Volcengine or the community to obtain patches or updates addressing this vulnerability as soon as they become available. 7) Consider isolating the environment where model merging occurs, using containerization or sandboxing to limit the impact of potential code execution.

Description

A deserialization vulnerability exists in Volcengine's verl 3.0.0, specifically in the scripts/model_merger.py script when using the "fsdp" backend. The script calls torch.load() with weights_only=False on user-supplied .pt files, allowing attackers to execute arbitrary code if a maliciously crafted model file is loaded. An attacker can exploit this by convincing a victim to download and place a malicious model file in a local directory with a specific filename pattern. This vulnerability may lead to arbitrary code execution with the privileges of the user running the script.

Impact

For European organizations, this vulnerability poses a significant risk, particularly for entities involved in AI research, machine learning development, and data science operations that rely on Volcengine's verl 3.0.0 or similar workflows. Exploitation could lead to arbitrary code execution, resulting in unauthorized access to sensitive data, disruption of AI model training or deployment pipelines, and potential compromise of broader IT infrastructure. Given the increasing adoption of AI and machine learning in sectors such as finance, healthcare, manufacturing, and government within Europe, the impact could extend to critical services and intellectual property theft. Additionally, organizations subject to strict data protection regulations like GDPR may face compliance violations and reputational damage if this vulnerability leads to data breaches. The requirement for user interaction to place the malicious file somewhat limits the attack surface but does not eliminate the risk, especially in environments where users have write access to directories used by the script. The absence of known exploits in the wild provides a window for proactive mitigation but should not lead to complacency.

CWE-77Improper Neutralization of Special Elements used in a Command ('Command Injection') (opens in a new tab)
Class weaknessLikelihood of exploit: HighCWE Top 25 (2025): #23OWASP Top 10 A05:2025: Injection (opens in a new tab)
The product constructs all or part of a command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended command when it is sent to a downstream component.
Architecture and Design
If at all possible, use library calls rather than external processes to recreate the desired functionality.
Implementation
If possible, ensure that all external commands called from the program are statically created.
Implementation · Input Validation
Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.
OWASP Cheat Sheets
Abuse Case (opens in a new tab)
Deserialization (opens in a new tab)
Injection Prevention (opens in a new tab)
SQL Injection Prevention (opens in a new tab)
Injection Prevention in Java (opens in a new tab)
OWASP ASVS 4.0.3
V1.5.1 (opens in a new tab)
Attack patterns
LDAP Injection (opens in a new tab)
Command Delimiters (opens in a new tab)
IMAP/SMTP Command Injection (opens in a new tab)
Manipulating Writeable Terminal Devices (opens in a new tab)
Exploiting Multiple Input Interpretation Layers (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 19 Aug 2025, 14:04 UTC

WeaknessesCWE-77

Technical details

References

Community reviews

Related threats