CVE-2026-13221 Perl versions through 5.43.9 produce silently incorrect regular expression matches when an alternation of more than 65535 fixed string branches is compiled into a trie in Perl_study_chunk

Perl versions through 5.43.9 produce silently incorrect regular expression matches when an alternation of more than 65535 fixed string branches is compiled into a trie in Perlstudychunk. When such branches are combined into a trie, the delta between the first branch and the shared tail is stored ...

CVE-2026-13221 Perl versions through 5.43.9 produce silently incorrect regular expression matches when an alternation of more than 65535 fixed string branches is compiled into a trie in Perl_study_chunk

Perl versions through 5.43.9 produce silently incorrect regular expression matches when an alternation of more than 65535 fixed string branches is compiled into a trie in Perlstudychunk. When such branches are combined into a trie, the delta between the first branch and the shared tail is stored ...

CVE-2026-13221

Perl versions through 5.43.9 produce silently incorrect regular expression matches when an alternation of more than 65535 fixed string branches is compiled into a trie in Perlstudychunk. When such branches are combined into a trie, the delta between the first branch and the shared tail is stored ...

CVE-2026-13221

Perl versions through 5.43.9 produce silently incorrect regular expression matches when an alternation of more than 65535 fixed string branches is compiled into a trie in Perlstudychunk. When such branches are combined into a trie, the delta between the first branch and the shared tail is stored ...

PT-2026-57822

Name of the Vulnerable Software and Affected Versions Perl versions prior to 5.44 Description Incorrect regular expression matches occur when an alternation of more than 65535 fixed string branches is compiled into a trie in Perl study chunk. A trie is a specialized tree-like data structure used...

Linux Distros Unpatched Vulnerability : CVE-2026-13221

The Linux/Unix host has one or more packages installed that are impacted by a vulnerability without a vendor supplied patch available. - Perl versions through 5.43.9 produce silently incorrect regular expression matches when an alternation of more than 65535 fixed string branches is compiled into...

A Robust Framework for Sybil Attack Detection in Vehicular Ad Hoc Networks

Sybil attacks create an illusion of traffic congestion by utilizing fake identities, which undermines the reliable and safe operation of vehicular ad hoc networks VANETs. Existing detection mechanisms struggle to effectively handle Sybil attacks as they are i susceptible to high false positive...

CVE-2026-48792

The connected sources confirm a vulnerability in pam_usb for Linux prior to 0.9.1: evdev.c silently ignores EACCES when opening /dev/input/event* nodes, causing pusb_has_virtual_input_device() to incorrectly report no virtual devices even if opens fail due to insufficient permissions. As a result...

EDySec: A Deep Learning-Based Explainable Dynamic Analysis Framework for Detecting Malicious Packages in PyPI Ecosystem

The security of open-source software repositories is increasingly threatened by next-gen software supply chain attacks. These attacks include multiphase malware execution, remote access activation, and dynamic payload generation. Traditional Machine Learning ML detectors struggle to detect these...

Detecting Avalanche Effect in Adversarial Settings: Spotting the Encryption Loops in Ransomware

Spotting encryption loops in binary-only ransomware is a critical reverse engineering task. Since the existence of avalanche effect, an intrinsic characteristic of any secure encryption algorithms, is unavoidable during a victim data encryption attack, it is a very promising direction to spot...

RuleForge: Automated Generation and Validation for Web Vulnerability Detection at Scale

Security teams face a challenge: the volume of newly disclosed Common Vulnerabilities and Exposures CVEs far exceeds the capacity to manually develop detection mechanisms. In 2025, the National Vulnerability Database published over 48,000 new vulnerabilities, motivating the need for automation. W...

Why Aggregate Accuracy Is Inadequate for Evaluating Fairness in Law Enforcement Facial Recognition Systems

Facial recognition systems are increasingly deployed in law enforcement and security contexts, where algorithmic decisions can carry significant societal consequences. Despite high reported accuracy, growing evidence demonstrates that such systems often exhibit uneven performance across demograph...

OpenAnt LLM-Based Vulnerability Discovery

OpenAnt from Knostic is an open source LLM-based vulnerability discovery product that helps defenders proactively find verified security flaws while minimizing both false positives and false negatives. Stage 1 detects. Stage 2 attacks. What survives is real...

PT-2026-6173

Name of the Vulnerable Software and Affected Versions Linux kernel affected versions not specified Description The Linux kernel contains a flaw in the ipvlan implementation related to address locking. The initial code assumed address changes occurred under RTNL, but this is not the case for IPv6...

Diverse LLMs Vs. Vulnerabilities: Who Detects and Fixes Them Better?

Large Language Models LLMs are increasingly being studied for Software Vulnerability Detection SVD and Repair SVR. Individual LLMs have demonstrated code understanding abilities, but they frequently struggle when identifying complex vulnerabilities and generating fixes. This study presents...

Exploit for CVE-2025-66478

monorepo-nextjs-npm-nested-versions - VULNERABLE CVE-2025-664...

Semantic Superiority Vs. Forensic Efficiency: A Comparative Analysis of Deep Learning and Psycholinguistics for Business Email Compromise Detection

Business Email Compromise BEC is a sophisticated social engineering threat that manipulates organizational hierarchies and exploits psychological vulnerabilities, leading to significant financial damage. According to the 2024 FBI Internet Crime Report, BEC accounts for over $2.9 billion in annual...

EUVD-2020-0410

Malware in sbrugna...

Tech-ASan: Two-Stage Check for Address Sanitizer

Address Sanitizer ASan is a sharp weapon for detecting memory safety violations, including temporal and spatial errors hidden in C/C++ programs during execution. However, ASan incurs significant runtime overhead, which limits its efficiency in testing large software. The overhead mainly comes fro...

Automated Alert Classification and Triage (AACT): an Intelligent System for the Prioritisation of Cybersecurity Alerts

Enterprise networks are growing ever larger with a rapidly expanding attack surface, increasing the volume of security alerts generated from security controls. Security Operations Centre SOC analysts triage these alerts to identify malicious activity, but they struggle with alert fatigue due to t...