CVE-2025-59964

This CVE concerns Juniper Networks Junos OS on SRX4700 devices. A Use of Uninitialized Resource vulnerability in the PFE (Packet Forwarding Engine) can be triggered by forwarding-options sampling, allowing an unauthenticated, network-based attacker to cause a DoS. Specifically, when traffic desti...

PT-2025-41405

Name of the Vulnerable Software and Affected Versions Juniper Networks Junos OS on SRX4700 versions 24.4 through 24.4R2 Description A Use of Uninitialized Resource issue exists in the Packet Forwarding Engine PFE of Juniper Networks Junos OS on SRX4700 devices. This allows an unauthenticated,...

EUVD-2014-3335

Malware in sbrugna...

EUVD-2019-2795

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EUVD-2020-12541

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EUVD-2007-3704

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EUVD-2018-4105

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EUVD-2021-29810

Malicious code in bioql PyPI...

EUVD-2025-22661

Malicious code in bioql PyPI...

EUVD-2021-29812

Malicious code in bioql PyPI...

EUVD-2025-10512

Malicious code in bioql PyPI...

EUVD-2024-53773

Malicious code in bioql PyPI...

SecInfer: Preventing Prompt Injection Via Inference-Time Scaling

Prompt injection attacks pose a pervasive threat to the security of Large Language Models LLMs. State-of-the-art prevention-based defenses typically rely on fine-tuning an LLM to enhance its security, but they achieve limited effectiveness against strong attacks. In this work, we propose...

Efficient Decoding Methods for Language Models on Encrypted Data

Large language models LLMs power modern AI applications, but processing sensitive data on untrusted servers raises privacy concerns. Homomorphic encryption HE enables computation on encrypted data for secure inference. However, neural text generation requires decoding methods like argmax and...

ALPHA: LLM-Enabled Active Learning for Human-Free Network Anomaly Detection

Network log data analysis plays a critical role in detecting security threats and operational anomalies. Traditional log analysis methods for anomaly detection and root cause analysis rely heavily on expert knowledge or fully supervised learning models, both of which require extensive labeled dat...

postgresql: PostgreSQL optimizer statistics can expose sampled data within a view, partition, or child table

An access control bypass flaw has been discovered in PostgreSQL. The PostgreSQL optimizer statistics allow a user to read sampled data within a view that the user cannot access. Separately, statistics allow a user to read sampled data that a row security policy intended to hide...

postgresql: PostgreSQL optimizer statistics can expose sampled data within a view, partition, or child table

An access control bypass flaw has been discovered in PostgreSQL. The PostgreSQL optimizer statistics allow a user to read sampled data within a view that the user cannot access. Separately, statistics allow a user to read sampled data that a row security policy intended to hide...

MAL-2025-17225 Malicious code in cmf.mes.sampling (npm)

The package cmf.mes.sampling was found to contain malicious code...

Malicious code in cmf.mes.sampling (npm)

The package cmf.mes.sampling was found to contain malicious code...

CVE-2025-8713

CVE-2025-8713 concerns PostgreSQL: attacker can read sampled statistics data (e.g., histograms, most-common-values) from columns via optimizer statistics, potentially bypassing view ACLs and row security policies in partitioning/inheritance hierarchies. Affected: PostgreSQL versions prior to 17.6...