EUVD-2022-39946

Malicious code in bioql PyPI...

EUVD-2022-52126

Malicious code in bioql PyPI...

EUVD-2025-6307

Malicious code in bioql PyPI...

EUVD-2021-34647

Malicious code in bioql PyPI...

EUVD-2023-3122

Malicious code in bioql PyPI...

EUVD-2025-20924

Malicious code in bioql PyPI...

EUVD-2022-28325

Malicious code in bioql PyPI...

EUVD-2024-46265

Malicious code in bioql PyPI...

EUVD-2023-48622

Malicious code in bioql PyPI...

EUVD-2022-0602

Malicious code in bioql PyPI...

EUVD-2022-6406

Malicious code in bioql PyPI...

EUVD-2025-19463

Malicious code in bioql PyPI...

EUVD-2025-2154

Malicious code in bioql PyPI...

EUVD-2023-12373

Malicious code in bioql PyPI...

EUVD-2022-4671

Malicious code in bioql PyPI...

RLSA-2025:8915 Moderate: grafana-pcp security update

The Grafana plugin for Performance Co-Pilot includes datasources for scalable time series from pmseries and Redis, live PCP metrics and bpftrace scripts from pmdabpftrace, as well as several dashboards. Security Fixes: net/http: Request smuggling due to acceptance of invalid chunked data in...

CST-AFNet: A Dual Attention-Based Deep Learning Framework for Intrusion Detection in IoT Networks

The rapid expansion of the Internet of Things IoT has revolutionized modern industries by enabling smart automation and real time connectivity. However, this evolution has also introduced complex cybersecurity challenges due to the heterogeneous, resource constrained, and distributed nature of...

Adaptive Deception Framework with Behavioral Analysis for Enhanced Cybersecurity Defense

This paper presents CADL Cognitive-Adaptive Deception Layer, an adaptive deception framework achieving 99.88% detection rate with 0.13% false positive rate on the CICIDS2017 dataset. The framework employs ensemble machine learning Random Forest, XGBoost, Neural Networks combined with behavioral...

Heap-based buffer overflow in the linetoken function in afmparse.c in t1lib, as used in teTeX 3.0.x, GNOME evince, and possibly other products, allows remote attackers to cause a denial of service (crash) and possibly execute arbitrary code via a DVI file containing a crafted Adobe Font Metrics (AFM) file, a different vulnerability than CVE-2010-2642.

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BIT-MONGODB-2024-3374 MongoDB Server (mongod) may crash when generating ftdc

An unauthenticated user can trigger a fatal assertion in the server while generating ftdc diagnostic metrics due to attempting to build a BSON object that exceeds certain memory sizes. This issue affects MongoDB Server v5.0 versions prior to and including 5.0.16 and MongoDB Server v6.0 versions...