CVE-2022-0342

Improper Authentication (CWE-287)

Published: Mar 28, 2022 / Updated: 32mo ago

Zyxel has released patches for products affected by the authentication bypass vulnerability. An authentication bypass vulnerability caused by the lack of a proper access control mechanism has been found in the CGI program of some firewall versions.

2056751 - ET MALWARE Observed Win32/Lumma Stealer Related Domain (captaitwik .sbs in TLS SNI) (malware.rules) 2056753 - ET MALWARE Observed Win32/Lumma Stealer Related Domain (deepymouthi .sbs in TLS SNI) (malware.rules)

CVE-2022-244622 No description provided CVE-2021-26084 In affected versions of Confluence Server and Data Center, an OGNL injection vulnerability exists that would allow an unauthenticated attacker to execute arbitrary code on a Confluence Server or Data Center instance. CVE-2022-26134 In affected versions of Confluence Server and Data Center, an OGNL injection vulnerability exists that would allow an unauthenticated attacker to execute arbitrary code on a Confluence Server or Data Center instance.

The post CPAI-2022-2139 appeared first on Check Point Software .

The following is the information on Yara and Snort rules (week 5, October 2024) collected and shared by the AhnLab TIP service. 5 YARA Rules Detection name Description Source PK_EDD_prncpal Phishing Kit impersonating Employment Development Department California (EDD) https://github.com/t4d/PhishingKit-Yara-Rules PK_Eika_oio Phishing Kit impersonating Eika Bank https://github.com/t4d/PhishingKit-Yara-Rules PK_Huntington_code0t17 Phishing Kit impersonating Huntington bank https://github.com/t4d/PhishingKit-Yara-Rules PK_LeBonCoin_2022 Phishing […] 게시물 Weekly Detection Rule (YARA and Snort) Information – Week 5, October 2024 이 ASEC 에 처음 등장했습니다.

2056751 - ET MALWARE Observed Win32/Lumma Stealer Related Domain (captaitwik .sbs in TLS SNI) (malware.rules) 2056753 - ET MALWARE Observed Win32/Lumma Stealer Related Domain (deepymouthi .sbs in TLS SNI) (malware.rules)

Code Execution and Injection, which is the most common category of vulnerabilities across the dataset, refers to flaws and weaknesses in software that permit attackers to run malicious or arbitrary code. Some common types of vulnerabilities in this category include unauthorized users accessing or reading files they shouldn’t be able to, often due to misconfigurations or design flaws, sending data over the network without proper encryption, which can lead to information interception, and systems not sufficiently encrypting or masking sensitive data, making it easily accessible.

Coming back to our static analysis methodology, here’s a simplified outline that can be used to quickly audit a large codebase with the help of Semgrep: Read the documentation, especially about past vulnerabilities, to uncover attack surface and interesting paths. My Semgrep ruleset (as well as some other tools I’ve released in the past) should help with the bottom-up approach, by isolating hotspots in code where bugs are likely to manifest.