VulnerabilityPublished 21 Nov 2025

CVE-2025-62608: ml-explore mlx · Heap-based Buffer Overflow

Affects ml-explore mlxSource CVE Database V5

Not known to be exploited · CVSS 5.5 Medium : upgrade to 0.29.4 when convenient.

Data as of 26 Oct 2026, 09:15 UTC

CVSS 4.0 base score

5.5Medium

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

EPSS: 0.5% chance of exploitation in 30 days – higher than 46% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch: Available – fixed in 0.29.4

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:N/VA:L/SC:N/SI:N/SA:N/E:P

Base metrics

Attack Vector: Network
Attack Complexity: Low
Attack Requirements: None
Privileges Required: None
User Interaction: None
Vulnerable system confidentiality: Low
Vulnerable system integrity: None
Vulnerable system availability: Low
Subsequent system confidentiality: None
Subsequent system integrity: None
Subsequent system availability: None

Threat metrics

Exploit Maturity: POC

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

Attack Vector: Network: The vulnerable system is bound to the network stack and the set of possible attackers extends beyond the other options listed below, 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: The attacker must take no measurable action to exploit the vulnerability. The attack requires no target-specific circumvention to exploit the vulnerability. An attacker can expect repeatable success against the vulnerable system.
Attack Requirements: None: The successful attack does not depend on the deployment and execution conditions of the vulnerable system. The attacker can expect to be able to reach the vulnerability and execute the exploit under all or most instances of the vulnerability.
Privileges Required: None: The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files of the vulnerable system to carry out an attack.
User Interaction: None: The vulnerable system can be exploited without interaction from any human user, other than the attacker.
Vulnerable system 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 Vulnerable System.
Vulnerable system integrity: None: There is no loss of integrity within the Vulnerable System.
Vulnerable system availability: Low: Performance is reduced or there are interruptions in resource availability. Even if repeated exploitation of the vulnerability is possible, the attacker does not have the ability to completely deny service to legitimate users. The resources in the Vulnerable System are either partially available all of the time, or fully available only some of the time, but overall there is no direct, serious consequence to the Vulnerable System.
Subsequent system confidentiality: None: There is no loss of confidentiality within the Subsequent System or all confidentiality impact is constrained to the Vulnerable System.
Subsequent system integrity: None: There is no loss of integrity within the Subsequent System or all integrity impact is constrained to the Vulnerable System.
Subsequent system availability: None: There is no impact to availability within the Subsequent System or all availability impact is constrained to the Vulnerable System.
Exploit Maturity: POC: Based on threat intelligence sources each of the following must apply: · Proof-of-concept is publicly available · No knowledge of reported attempts to exploit this vulnerability · No knowledge of publicly available solutions used to simplify attempts to exploit the vulnerability

Definitions: FIRST CVSS v4.0 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 21 Nov 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 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 ml-explore/mlx to 0.29.4.

Affected software

Product	Affected	Fixed in
GitHubml-explore/mlx`pkg:github/ml-explore/mlx`Other threats	Affected <0.29.4	Fixed in 0.29.4

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 update the mlx framework to version 0.29.4 or later to remediate this vulnerability. Additionally, organizations should implement strict validation and sanitization of all external NumPy .npy files before processing, including scanning for malformed or suspicious files. Employing application-level sandboxing or containerization for ML workloads can limit the blast radius of potential crashes or leaks. Monitoring ML pipeline logs for unexpected crashes or anomalies can help detect exploitation attempts. Restricting file input sources to trusted origins and enforcing strict access controls on ML data ingestion points will reduce exposure. For organizations unable to upgrade immediately, disabling automatic loading of untrusted .npy files or using alternative parsing libraries without this vulnerability can be considered. Finally, maintain up-to-date asset inventories to identify Apple silicon devices running vulnerable mlx versions to prioritize patching efforts.

Description

MLX is an array framework for machine learning on Apple silicon. Prior to version 0.29.4, there is a heap buffer overflow in mlx::core::load() when parsing malicious NumPy .npy files. Attacker-controlled file causes 13-byte out-of-bounds read, leading to crash or information disclosure. This issue has been patched in version 0.29.4.

Impact

For European organizations, the primary impact of CVE-2025-62608 lies in potential denial of service and limited information disclosure within machine learning environments running on Apple silicon devices. Organizations relying on mlx for ML data processing could face application crashes disrupting workflows, leading to operational downtime or degraded service availability. The information disclosure risk, while limited to small memory leaks, could expose sensitive ML model parameters or proprietary data if exploited in a targeted manner. This could undermine intellectual property confidentiality or leak sensitive training data. The vulnerability is particularly relevant for sectors with advanced ML adoption such as finance, healthcare, and research institutions across Europe. Since exploitation requires supplying a malicious .npy file, environments that ingest external or user-generated ML data are at higher risk. However, the lack of privilege requirements and user interaction lowers the attack complexity. Prompt patching is essential to prevent exploitation and maintain the integrity and availability of ML workflows.

CWE-122Heap-based Buffer Overflow (opens in a new tab)
Variant weaknessLikelihood of exploit: HighCWE Top 25 (2025): #16
A heap overflow condition is a buffer overflow, where the buffer that can be overwritten is allocated in the heap portion of memory, generally meaning that the buffer was allocated using a routine such as malloc().
Pre-design: Use a language or compiler that performs automatic bounds checking.
Architecture and Design
Use an abstraction library to abstract away risky APIs. Not a complete solution.
Operation · Build and Compilation · Environment Hardening
Use automatic buffer overflow detection mechanisms that are offered by certain compilers or compiler extensions. Examples include: the Microsoft Visual Studio /GS flag, Fedora/Red Hat FORTIFY_SOURCE GCC flag, StackGuard, and ProPolice, which provide various mechanisms including canary-based detection and range/index…
OWASP Cheat Sheets
XML Security (opens in a new tab)
Mass Assignment (opens in a new tab)
OWASP ASVS 4.0.3
V13.3.1 (opens in a new tab)
V5.1.4 (opens in a new tab)
V5.1.3 (opens in a new tab)
Attack patterns
Forced Integer Overflow (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

Community reviews

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 21 Nov 2025, 19:20 UTC

WeaknessesCWE-122

Technical details

References

Community reviews

Related threats