waf-bypass

WAF 우회 도구 WAF Bypass Tool은 사전 정의된 사용자 정의 가능한 페이로드를 사용하여 모든 WAF의 False Positive 및 False Negative에 대한 보안을 분석하는 오픈 소스 도구입니다. 공격자가 하기 전에 WAF를 확인하세요. WAF Bypass Tool은 커뮤니티의 참여로 Nemesida WAF 팀이 개발했습니다. 불법적인 행위 금지 불법적인 목적으로 사용하는 것을 금지합니다. 법을 위반하지 마십시오. 이 소프트웨어 사용과 관련된 가능한 위험에 대해 당사는 책임을 지지 않습니다. 실행 방법...

waf-bypass

WAF Bypass Tool WAF Bypass Tool is an open source tool to analyze the security of any WAF for False Positives and False Negatives using predefined and customizable payloads. Check your WAF before an attacker does. WAF Bypass Tool is developed by Nemesida WAF team with the participation of...

Adversarial-Detection-Engineering-Framework

적대적 탐지 엔지니어링 ADE 프레임워크 오탐지False Negatives를 앞서 대처하세요. 위협 행위자가 악용하기 전에 탐지 로직이 어떻게 실패하는지 이해함으로써. 웹사이트 확인: https://adeframework.org/ ADE란 무엇인가? 적대적 탐지 엔지니어링ADE은 탐지 규칙의 오탐지False Negatives 에 대해 추론하는 학문입니다. ADE 프레임워크는 탐지 로직 버그Detection Logic Bugs 에 대한 현대적인 오픈소스 공식화를 제공합니다. 이는 탐지 규칙이 의도한 탐지 대상과 실제로 탐지하는 ...

perl: Perl: Incorrect regular expression processing via large regular expressions

A flaw was found in Perl. When the Perl regular expression engine processes patterns with a very large number of alternative fixed strings, an internal data field can overflow. This leads to silently incorrect regular expression matches, causing the engine to either match strings it should not...

CVE-2026-13221

A flaw was found in Perl. When the Perl regular expression engine processes patterns with a very large number of alternative fixed strings, an internal data field can overflow. This leads to silently incorrect regular expression matches, causing the engine to either match strings it should not...

perl: Perl: Incorrect regular expression processing via large regular expressions

A flaw was found in Perl. When the Perl regular expression engine processes patterns with a very large number of alternative fixed strings, an internal data field can overflow. This leads to silently incorrect regular expression matches, causing the engine to either match strings it should not...

SUSE CVE-2026-13221

Perl versions before 5.40.5-RC1, from 5.41.0 before 5.42.3-RC1, from 5.43.0 before 5.43.10 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...

CVE-2026-13221

Perl versions before 5.40.5-RC1, from 5.41.0 before 5.42.3-RC1, from 5.43.0 before 5.43.10 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...

CVE-2026-13221 Perl versions before 5.40.5-RC1, from 5.41.0 before 5.42.3-RC1, from 5.43.0 before 5.43.10 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 before 5.40.5-RC1, from 5.41.0 before 5.42.3-RC1, from 5.43.0 before 5.43.10 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...

CVE-2026-13221 Perl versions before 5.40.5-RC1, from 5.41.0 before 5.42.3-RC1, from 5.43.0 before 5.43.10 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 before 5.40.5-RC1, from 5.41.0 before 5.42.3-RC1, from 5.43.0 before 5.43.10 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...

CVE-2026-13221

Perl versions before 5.40.5-RC1, from 5.41.0 before 5.42.3-RC1, from 5.43.0 before 5.43.10 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...

CVE-2026-13221

Perl versions before 5.40.5-RC1, from 5.41.0 before 5.42.3-RC1, from 5.43.0 before 5.43.10 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...

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 before 5.40.5-RC1, from 5.41.0 before 5.42.3-RC1, from 5.43.0 before 5.43.10 produce silently incorrect regular expression matches when an...

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...