apidriver (>=0.6.5, <=0.9.1), classification-model (0.0.1) +27 more potentially affected by CVE-2026-59890 via setuptools (56.0.0)

setuptools PYPI version 56.0.0 is affected by a known vulnerability. The following packages have a transitive dependency on setuptools and may be impacted: - apidriver =0.6.5, =3.33.0, =0.41.1, =10.0.0, =0.0.3.6, =1.2.3, =1.0.0, =0.0.18, =1.0.0, =1.4.13, =1.4.29 and more Source cves: CVE-2026-598...

MIT to Become Hotbed of AI Video Surveillance

It's a lot: According to information obtained by The Tech , MIT is spending over $3 million on more than 500 AI surveillance cameras in academic buildings, residence halls, and outdoor areas along Memorial Drive. Installation of the new cameras, along with the wiring and infrastructure that will...

CVE-2026-15422 SCTP needs to better-check INIT ACK chunk parameters

The illumos SCTP inbound path performs association lookup for INIT ACK chunks without adequately validating the address parameters carried in the chunk. Since this lookup runs during packet classification i.e. before SCTP integrity checks or IPsec policy are applied a remote, unauthenticated...

On the Impact of Entropy-Based Features

Network anomaly detection is increasingly challenging due to the growing diversity and variability of traffic patterns, which are not always well captured by traditional statistical features. In this work, we explore the use of entropy as an additional feature to support supervised network traffi...

animl (>=1.1.2, <=1.1.4), annopro (>=0.1.0rc1, <=0.2.0) +65 more potentially affected by CVE-2026-12482 via keras (2.6.0)

keras PYPI version 2.6.0 is affected by a known vulnerability. The following packages have a transitive dependency on keras and may be impacted: - animl =1.1.2, =0.1.0rc1, =0.47.0, =1.0.1, =0.0.9, =0.0.3, =2.2.0, =2.4.1, =1.0.0rc1, =4.5.2, =0.48.1, =1.1.3, =0.2.4, =0.2.10 and more Source cves:...

TSAI-MetaFraud: A Benchmark Dataset for Financial Fraud Transaction and Behavioral Risk Detection in Metaverse Ecosystems

The emergence of metaverse platforms has created virtual economies that introduce new challenges related to fraud, bot activity, and illicit financial behavior. Despite growing interest in trustworthy metaverse analytics, existing datasets typically focus on user behavior, authentication, or...

alwakeupword (1.0.0), armadillin (>=0.0.2, <=0.53.0) +33 more potentially affected by CVE-2022-23577 via tensorflow (>=2.6.0, <=2.6.2)

tensorflow PYPI version =2.6.0, =0.0.2, =1.0.1, =0.0.9, =0.2.0, =4.5.2, =1.1.2, =0.2.0, =0.0.1, =0.1.5, =1.0.3, =1.0.6 and more Source cves: CVE-2022-23577 Source advisory: OSV:PYSEC-2026-3135...

alwakeupword (1.0.0), armadillin (>=0.0.2, <=0.53.0) +33 more potentially affected by CVE-2022-23583 via tensorflow (>=2.6.0, <=2.6.2)

tensorflow PYPI version =2.6.0, =0.0.2, =1.0.1, =0.0.9, =0.2.0, =4.5.2, =1.1.2, =0.2.0, =0.0.1, =0.1.5, =1.0.3, =1.0.6 and more Source cves: CVE-2022-23583 Source advisory: OSV:PYSEC-2026-3191...

PYSEC-2026-1406 GluonCV Arbitrary File Write via TarSlip

A vulnerability in the ImageClassificationDataset.fromcsv API of the dmlc/gluon-cv repository, version 0.10.0, allows for arbitrary file write. The function downloads and extracts tar.gz files from URLs without proper sanitization, making it susceptible to a TarSlip vulnerability. Attackers can...

GluonCV Arbitrary File Write via TarSlip

A vulnerability in the ImageClassificationDataset.fromcsv API of the dmlc/gluon-cv repository, version 0.10.0, allows for arbitrary file write. The function downloads and extracts tar.gz files from URLs without proper sanitization, making it susceptible to a TarSlip vulnerability. Attackers can...

Refuel Autolab Eval Injection vulnerability

An arbitrary code execution vulnerability exists in versions 0.0.8 and newer of the Refuel Autolabel library because of the way its classification tasks handle provided CSV files. If a victim user creates a classification task using a maliciously crafted CSV file containing Python code, the code...

Refuel Autolab Eval Injection vulnerability

An arbitrary code execution vulnerability exists in versions 0.0.8 and newer of the Refuel Autolabel library because of the way its multilabel classification tasks handle provided CSV files. If a user creates a multilabel classification task using a maliciously crafted CSV file containing Python...

PYSEC-2026-1870 Refuel Autolab Eval Injection vulnerability

An arbitrary code execution vulnerability exists in versions 0.0.8 and newer of the Refuel Autolabel library because of the way its classification tasks handle provided CSV files. If a victim user creates a classification task using a maliciously crafted CSV file containing Python code, the code...

aggmap (>=1.1.1, <=1.2.1), animl (>=1.1.2, <=1.1.4) +54 more potentially affected by CVE-2023-25673 via tensorflow-gpu (>=2.0.0, <=2.10.1)

tensorflow-gpu PYPI version =2.0.0, =1.1.1, =1.1.2, =0.0.1, =0.0.9, =0.2.1, =0.1.0, =0.0.4, =1.1.1, =1.1.0, =0.1.1, =0.3.2 and more Source cves: CVE-2023-25673 Source advisory: OSV:PYSEC-2026-956...

animl (>=1.1.2, <=1.1.4), audio-classification-models (1.0.1) +50 more potentially affected by CVE-2022-41897 via tensorflow-gpu (>=2.0.0, <=2.8.3)

tensorflow-gpu PYPI version =2.0.0, =1.1.2, =0.0.1, =0.0.9, =0.2.1, =0.1.0, =0.0.4, =1.1.1, =1.1.0, =0.1.1, =0.1.0, =0.1.7 and more Source cves: CVE-2022-41897 Source advisory: OSV:PYSEC-2026-984...

animl (>=1.1.2, <=1.1.4), audio-classification-models (1.0.1) +44 more potentially affected by CVE-2022-35989 via tensorflow-gpu (>=2.0.0, <=2.7.0)

tensorflow-gpu PYPI version =2.0.0, =1.1.2, =0.0.1, =0.0.9, =0.0.4, =1.1.1, =1.1.0, =0.1.1, =0.1.0, =0.1.5, =0.2.0, =0.2.1 and more Source cves: CVE-2022-35989 Source advisory: OSV:PYSEC-2026-1011...

animl (>=1.1.2, <=1.1.4), audio-classification-models (1.0.1) +44 more potentially affected by CVE-2022-35999 via tensorflow-gpu (>=2.0.0, <=2.7.0)

tensorflow-gpu PYPI version =2.0.0, =1.1.2, =0.0.1, =0.0.9, =0.0.4, =1.1.1, =1.1.0, =0.1.1, =0.1.0, =0.1.5, =0.2.0, =0.2.1 and more Source cves: CVE-2022-35999 Source advisory: OSV:PYSEC-2026-946...

HilEnT: Hilbert, Entropy Transformed Image Based Malware Detection

With the increasing threat of malware across various software related domains, malware detection and classification is critical to determine the response actions. Different strategies have been adopted to address the challenge of malware detection. With the advent of deep learning techniques,...

ThreatVisionAI: A Hybrid CNN-ViT Framework for Image-Based Malware Classification

Traditional malware detection methods struggle to generalize to obfuscated or previously unseen threats. This paper introduces ThreatVisionAI, a hybrid malware family classification framework that integrates a raw-image CNN, a wavelet-based CNN, and a Vision Transformer ViT to capture complementa...

A Multi-Task Mixture of Experts Framework for Malware Classification, Packing Detection, and Family Attribution

Malware classification remains a challenging problem due to its inherent heterogeneity, the presence of packed binaries, and the diverse distribution of malware families. Traditional single-model detection mechanisms often fail to generalize across such diverse data, leading to degraded...