Links submitted by the Threat Radar community and AI curated for defenders.

Community Curated

CVE Database V5

Real-world exploitation and exposure telemetry from the OffSeq Mirage honeypot fleet and Sonar internet scans — which CVEs attackers are actually exploiting and which are exposed in the wild, plus attacker IoCs. All IPs are masked; no raw victim or sensor identity is ever published.

OffSeq Mirage

AlienVault OTX General

SANS ISC Handlers Diary

SecurityWeek

Threatpost

Reddit ExploitDev

Latest exploits, shellcode, and vulnerability proofs-of-concept from Exploit-DB

Exploit-DB RSS Feed

Reddit BlueTeam

Reddit ThreatIntel

Reddit Reverse Engineering

Reddit Malware

Reddit NetSec

Reddit Cybersecurity

ThreatFox MISP Feed

CIRCL OSINT Feed

NCSC UK

JVN Japan

GCP Compute Engine Security

GCP Kubernetes Security

AWS Security Bulletins

CERT/CC

Tenable Research

Google Project Zero

Microsoft Security Blog

Cisco Talos

Zero Day Initiative

Palo Alto Unit 42

Krebs on Security

Kaspersky Security Blog

Check Point Research

GCVE Database

Bleeping Computer

Reddit InfoSec News

The Hacker News

Dark Reading

AlienVault OTX Vulnerabilities

AlienVault OTX Malware

MLX is an array framework for machine learning on Apple silicon. Prior to version 0.29.4, there is a segmentation fault in mlx::core::load_gguf() when loading malicious GGUF files. Untrusted pointer from external gguflib library is dereferenced without validation, causing application crash. This issue has been patched in version 0.29.4.

CVE-2025-62609 is a vulnerability identified in the ml-explore mlx framework, an array processing library designed for machine learning workloads on Apple silicon platforms. The vulnerability stems from a NULL pointer dereference (CWE-476) in the mlx::core::load_gguf() function, which is responsible for loading GGUF files—a data format used within the framework. Specifically, when mlx versions prior to 0.29.4 load a maliciously crafted GGUF file, an untrusted pointer originating from the external gguflib library is dereferenced without proper validation or null checks. This leads to a segmentation fault, causing the application to crash. The vulnerability is remotely exploitable without any authentication or user interaction, as the attack vector involves supplying a malicious GGUF file to the vulnerable function. The CVSS v4.0 base score is 5.5 (medium severity), reflecting the limited impact confined to denial of service rather than code execution or data compromise. No known exploits are currently reported in the wild. The issue was reserved in October 2025 and published in November 2025, with a patch available in mlx version 0.29.4 that adds necessary pointer validation to prevent the crash. This vulnerability primarily affects applications and services that utilize the mlx framework for machine learning tasks on Apple silicon hardware and load GGUF files from untrusted sources.

Detailed information about CVE-2025-62609: CWE-476: NULL Pointer Dereference in ml-explore mlx affecting ml-explore mlx. Get real-time updates, technical detail

CVE-2025-62609: CWE-476: NULL Pointer Dereference in ml-explore mlx - Live Threat Intelligence - Threat Radar | OffSeq.com

CVE-2025-62609: CWE-476: NULL Pointer Dereference in ml-explore mlx

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.

CVE-2025-62608 is a heap-based buffer overflow vulnerability identified in the mlx array framework, a machine learning library optimized for Apple silicon platforms. The vulnerability resides in the mlx::core::load() function responsible for parsing NumPy .npy files, a common data format in scientific computing and ML workflows. Specifically, when processing a maliciously crafted .npy file, mlx performs an out-of-bounds read of 13 bytes beyond the allocated heap buffer. This flaw is classified under CWE-122 (Heap-based Buffer Overflow). The consequence of this out-of-bounds read is twofold: it can cause the application to crash (denial of service) or leak sensitive memory contents (information disclosure). The vulnerability does not require any privileges, user interaction, or authentication, making it remotely exploitable by simply supplying a crafted file to the vulnerable mlx library. The affected versions are all mlx releases prior to 0.29.4, with the issue resolved in version 0.29.4. The CVSS v4.0 base score is 5.5 (medium severity), reflecting the limited impact scope and lack of integrity or availability compromise beyond crash and information leak. No known exploits have been reported in the wild, but the vulnerability poses a risk to systems that automatically load or process untrusted NumPy files using vulnerable mlx versions on Apple silicon hardware. Given the growing use of Apple silicon in ML environments, this vulnerability could be leveraged in targeted attacks against data science workflows or ML model pipelines.

Detailed information about CVE-2025-62608: CWE-122: Heap-based Buffer Overflow in ml-explore mlx affecting ml-explore mlx. Get real-time updates, technical deta

CVE-2025-62608: CWE-122: Heap-based Buffer Overflow in ml-explore mlx - Live Threat Intelligence - Threat Radar | OffSeq.com

CVE-2025-62608: CWE-122: Heap-based Buffer Overflow in ml-explore mlx


CVE-2025-62609: CWE-476: NULL Pointer Dereference in ml-explore mlxCVE-2025-62609 0 MLX is an array framework for machine learning on Apple silicon. Prior to version 0.29.4, there is a segmentation fault in mlx::core::load_gguf() when loading malicious GGUF files. Untrusted pointer from external gguflib library is dereferenced without validation, causing application crash. This issue has been patched in version 0.29.4. MediumVulnerabilityGermanyFranceUnited Kingdom+5#cve #cve-2025-62609 #cwe-476 Join the discussion	CVE Database V5	11/21/2025, 18:57:45 UTC Added: 11/21/2025, 19:13:14 UTC
CVE-2025-62608: CWE-122: Heap-based Buffer Overflow in ml-explore mlxCVE-2025-62608 0 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. MediumVulnerabilityGermanyFranceUnited Kingdom+7#cve #cve-2025-62608 #cwe-122 Join the discussion	CVE Database V5	11/21/2025, 18:56:03 UTC Added: 11/21/2025, 19:13:14 UTC

Threat Intelligence Database

Stop chasing alerts. Route them.

Check if your credentials are on the dark web

Filter Threats

Threat Intelligence

Lead Pen Test Professional