Microsoft vulnerability: Source code published for three zero-day vulnerabilities in Windows

Background A security researcher (with the pseudonym SandboxEscaper) has discovered three zero-day vulnerabilities in Microsoft Windows. Their POC and source code have been released on GitHub. Two of these are local privilege escalation (LPE) vulnerabilities. They have been tested to work on Windows 10 only. The third vulnerability is a sandbox bypass vulnerability in Internet Explorer 11 (IE11). As of this writing, no patch has been released by Microsoft for these vulnerabilities.   What is the issue? The security researcher has published three POCs: angrypolarbearbug2, bearlpe, and sandboxescape.  The first vulnerability – angrypolarbearbug2 – can be exploited by performing specially crafted DACL (discretionary access control list) operations when the Windows Error Reporting service tries to write a DACL for the given Windows Error Reporting (.wer) file. Once successfully exploited, the vulnerability gives SYSTEM privileges to the attacker. The second vulnerability – bearlpe – targets the way the Windows task scheduler service uses the SetJobFileSecurityByName() function to write DACL for the job file. For this exploit to work, one needs to have “schtasks.exe" and "schedsvc.dll" files from Windows XP. Once successfully exploited, the vulnerability gives SYSTEM privileges to the attacker. The third vulnerability – sandboxescape – bypasses the IE11 sandbox and allows an attacker to execute code in IE low protection mode. To exploit this vulnerability, an attacker needs to inject a special DLL in the IE process. According to reports, this exploit cannot be triggered remotely.   What systems are impacted? The POC has been tested on Windows 10 32-bit and 64-bit and IE11.   Zscaler coverage Advanced Threat Signatures: Win32.Exploit.Bearlpe  Win32. Exploit.CVE.2019.0863 Win32.Exploit.Polarbearescape W32/Agent.NBHI Zscaler Cloud Sandbox provides proactive coverage against exploit payloads and advanced threats like ransomware, and the Zscaler ThreatLabZ team is actively monitoring for in-the-wild exploit attempts to ensure coverage.

Link: https://www.zscaler.com/blogs/research/microsoft-vulnerability-source-code-published-three-zero-day-vulnerabilities-windows

Microsoft vulnerability: Source code published for three zero-day vulnerabilities in Windows

Background A security researcher (with the pseudonym SandboxEscaper) has discovered three zero-day vulnerabilities in Microsoft Windows. Their POC and source code have been released on GitHub. Two of these are local privilege escalation (LPE) vulnerabilities. They have been tested to work on Windows 10 only. The third vulnerability is a sandbox bypass vulnerability in Internet Explorer 11 (IE11). As of this writing, no patch has been released by Microsoft for these vulnerabilities.   What is the issue? The security researcher has published three POCs: angrypolarbearbug2, bearlpe, and sandboxescape.  The first vulnerability – angrypolarbearbug2 – can be exploited by performing specially crafted DACL (discretionary access control list) operations when the Windows Error Reporting service tries to write a DACL for the given Windows Error Reporting (.wer) file. Once successfully exploited, the vulnerability gives SYSTEM privileges to the attacker. The second vulnerability – bearlpe – targets the way the Windows task scheduler service uses the SetJobFileSecurityByName() function to write DACL for the job file. For this exploit to work, one needs to have “schtasks.exe" and "schedsvc.dll" files from Windows XP. Once successfully exploited, the vulnerability gives SYSTEM privileges to the attacker. The third vulnerability – sandboxescape – bypasses the IE11 sandbox and allows an attacker to execute code in IE low protection mode. To exploit this vulnerability, an attacker needs to inject a special DLL in the IE process. According to reports, this exploit cannot be triggered remotely.   What systems are impacted? The POC has been tested on Windows 10 32-bit and 64-bit and IE11.   Zscaler coverage Advanced Threat Signatures: Win32.Exploit.Bearlpe  Win32. Exploit.CVE.2019.0863 Win32.Exploit.Polarbearescape W32/Agent.NBHI Zscaler Cloud Sandbox provides proactive coverage against exploit payloads and advanced threats like ransomware, and the Zscaler ThreatLabZ team is actively monitoring for in-the-wild exploit attempts to ensure coverage.

Link: https://www.zscaler.com/blogs/research/microsoft-vulnerability-source-code-published-three-zero-day-vulnerabilities-windows

VulnX – CMS And Vulnerabilites Detector And An Intelligent Auto Shell Injector

Vulnx is a cms and vulnerabilites detection, an intelligent auto shell injector, fast cms detection of target and fast scanner and informations gathering like subdomains, ipaddresses, country, org, timezone, region, ans and more …Instead of injecting shell and checking it works like all the other tools do, vulnx analyses the response with and recieve if shell success uploaded or no. vulnx is searching for urls with dorks.FeaturesDetect cms (wordpress, joomla, prestashop, drupal, opencart, magento, lokomedia)Target informations gatheringsTarget Subdomains gatheringMulti-threading on demandChecks for vulnerabilitesAuto shell injectorExploit dork searcherExploitsJoomlaCom Jce Com Jwallpapers Com Jdownloads Com Weblinks Com Fabrik Com Jdownloads IndexCom Foxcontact Com Blog Com Users Com Ads Manager Com SexycontactformCom Media Mod_simplefileuploadCom Facileforms WordPressSimple Ads Manager InBoundio Marketing WPshop eCommerce Synoptic Showbiz Pro Job Manager Formcraft PowerZoom Download Manager CherryFramework Catpro Blaze SlideShow Wysija-Newsletters DrupalAdd Admin Drupal BruteForcer Drupal Geddon2 PrestaShopattributewizardpro columnadverts soopamobile pk_flexmenu pk_vertflexmenu nvn_export_orders megamenu tdpsthemeoptionpanel psmodthemeoptionpanelmasseditproduct blocktestimonialsoopabannersVtermslideshow simpleslideshow productpageadverts homepageadvertisehomepageadvertise2jro_homepageadvertiseadvancedslider cartabandonmentpro cartabandonmentproOldvideostab wg24themeadministrationfieldvmegamenu wdoptionpanel OpencartOpencart BruteForceAvailable command line optionsREAD VULNX WIKIusage: vulnx [options] -u –url url target to scan -D –dorks search webs with dorks -o –output specify output directory -t –timeout http requests timeout -c –cms-info search cms info[themes,plugins,user,version..] -e –exploit searching vulnerability & run exploits -w –web-info web informations gathering -d –domain-info subdomains informations gathering -l, –dork-list list names of dorks exploits –threads number of threadsDockerVulnX can be launched in docker.$ git clone https://github.com/anouarbensaad/VulnX.git$ cd VulnX$ docker build -t vulnx ./docker/$ docker run -it –name vulnx vulnx:latest -u http://exemple.commake a local volume to view the results into a logfile$ docker run -it –name vulnx -v “$PWD/logs:/VulnX/logs" vulnx:latest -u http://exemple.comInstall VulnX$ git clone https://github.com/anouarbensaad/VulnX.git$ cd VulnX$ chmod + x install.sh$ ./install.shNow run vulnxexample command with options : settimeout=3 , cms-gathering = all , -d subdomains-gathering , run –exploitsvulnx -u http://example.com –timeout 3 -c all -d -w –exploitexample command for searching dorks : -D or –dorks , -l –list-dorksvulnx –list-dorks return table of exploits name. vulnx -D blaze return urls found with blaze dorkVulnX Wiki • How To Use • Compatibility Download VulnX

Link: http://feedproxy.google.com/~r/PentestTools/~3/ARM75rpuTUo/vulnx-cms-and-vulnerabilites-detector.html

Bandit – Tool Designed To Find Common Security Issues In Python Code

Bandit is a tool designed to find common security issues in Python code. To do this Bandit processes each file, builds an AST from it, and runs appropriate plugins against the AST nodes. Once Bandit has finished scanning all the files it generates a report.Bandit was originally developed within the OpenStack Security Project and later rehomed to PyCQA.InstallationBandit is distributed on PyPI. The best way to install it is with pip:Create a virtual environment (optional):virtualenv bandit-envInstall Bandit:pip install bandit# Or if you’re working with a Python 3 projectpip3 install banditRun Bandit:bandit -r path/to/your/codeBandit can also be installed from source. To do so, download the source tarball from PyPI, then install it:python setup.py install UsageExample usage across a code tree:bandit -r ~/your_repos/projectExample usage across the examples/ directory, showing three lines of context and only reporting on the high-severity issues:bandit examples/*.py -n 3 -lllBandit can be run with profiles. To run Bandit against the examples directory using only the plugins listed in the ShellInjection profile:bandit examples/*.py -p ShellInjectionBandit also supports passing lines of code to scan using standard input. To run Bandit with standard input:cat examples/imports.py | bandit -Usage:$ bandit -husage: bandit [-h] [-r] [-a {file,vuln}] [-n CONTEXT_LINES] [-c CONFIG_FILE] [-p PROFILE] [-t TESTS] [-s SKIPS] [-l] [-i] [-f {csv,custom,html,json,screen,txt,xml,yaml}] [–msg-template MSG_TEMPLATE] [-o [OUTPUT_FILE]] [-v] [-d] [-q] [–ignore-nosec] [-x EXCLUDED_PATHS] [-b BASELINE] [–ini INI_PATH] [–version] [targets [targets …]]Bandit – a Python source code security analyzerpositional arguments: targets source file(s) or directory(s) to be testedoptional arguments: -h, –help show this help message and exit -r, –recursive find and process files in subdirectories -a {file,vuln}, –aggregate {file,vuln} aggregate output by vulnerability (default) or by filename -n CONTEXT_LINES, –number CONTEXT_LINES maximum number of code lines to output for each issue -c CONFIG_FILE, –configfile CONFIG_FILE optional config file to use for selecting plugins and overriding defaults -p PROFILE, –profile PROFILE profile to use (defaults to executing all tests) -t TESTS, –tests TESTS comma-separated list of test IDs to run -s SKIPS, –skip SKIPS comma-separated list of test IDs to skip -l, –level report only issues of a given severity level or higher (-l for LOW, -ll for MEDIUM, -lll for HIGH) -i, –confidence report only issues of a given confidence level or higher (-i for LOW, -ii for MEDIUM, -iii for HIGH) -f {cs v,custom,html,json,screen,txt,xml,yaml}, –format {csv,custom,html,json,screen,txt,xml,yaml} specify output format –msg-template MSG_TEMPLATE specify output message template (only usable with –format custom), see CUSTOM FORMAT section for list of available values -o [OUTPUT_FILE], –output [OUTPUT_FILE] write report to filename -v, –verbose output extra information like excluded and included files -d, –debug turn on debug mode -q, –quiet, –silent only show output in the case of an error –ignore-nosec do not skip lines with # nosec comments -x EXCLUDED_PATHS, –exclude EXCLUDED_PATHS comma-separated list of paths (glob patterns supported) to exclude from scan (not e that these are in addition to the excluded paths provided in the config file) -b BASELINE, –baseline BASELINE path of a baseline report to compare against (only JSON-formatted files are accepted) –ini INI_PATH path to a .bandit file that supplies command line arguments –version show program’s version number and exitCUSTOM FORMATTING—————–Available tags: {abspath}, {relpath}, {line}, {test_id}, {severity}, {msg}, {confidence}, {range}Example usage: Default template: bandit -r examples/ –format custom –msg-template \ “{abspath}:{line}: {test_id}[bandit]: {severity}: {msg}" Provides same output as: bandit -r examples/ –format custom Tags can also be formatted in python string.format() style: ban dit -r examples/ –format custom –msg-template \ "{relpath:20.20s}: {line:03}: {test_id:^8}: DEFECT: {msg:>20}" See python documentation for more information about formatting style: https://docs.python.org/3.4/library/string.htmlThe following tests were discovered and loaded:———————————————– B101 assert_used B102 exec_used B103 set_bad_file_permissions B104 hardcoded_bind_all_interfaces B105 hardcoded_password_string B106 hardcoded_password_funcarg B107 hardcoded_password_default B108 hardcoded_tmp_directory B110 try_except_pass B112 try_except_continue B201 flask_debug_true B301 pickle B302 marshal B303 md5 B304 ciphers B305 cipher_modes B306 mktemp_q B307 eval B308 mark_safe B309 httpsconnection B310 urllib_urlopen B311 random B312 telnetli b B313 xml_bad_cElementTree B314 xml_bad_ElementTree B315 xml_bad_expatreader B316 xml_bad_expatbuilder B317 xml_bad_sax B318 xml_bad_minidom B319 xml_bad_pulldom B320 xml_bad_etree B321 ftplib B322 input B323 unverified_context B324 hashlib_new_insecure_functions B325 tempnam B401 import_telnetlib B402 import_ftplib B403 import_pickle B404 import_subprocess B405 import_xml_etree B406 import_xml_sax B407 import_xml_expat B408 import_xml_minidom B409 import_xml_pulldom B410 import_lxml B411 import_xmlrpclib B412 import_httpoxy B413 import_pycrypto B501 request_with_no_cert_validation B502 ssl_with_bad_version B503 ssl_with_bad_defaults B504 ssl_with_no_version B505 weak_cryptographic_key B506 yaml_load B507 ssh_no_host_key_verification B601 paramiko_ calls B602 subprocess_popen_with_shell_equals_true B603 subprocess_without_shell_equals_true B604 any_other_function_with_shell_equals_true B605 start_process_with_a_shell B606 start_process_with_no_shell B607 start_process_with_partial_path B608 hardcoded_sql_expressions B609 linux_commands_wildcard_injection B610 django_extra_used B611 django_rawsql_used B701 jinja2_autoescape_false B702 use_of_mako_templates B703 django_mark_safe BaselineBandit allows specifying the path of a baseline report to compare against using the base line argument (i.e. -b BASELINE or –baseline BASELINE).bandit -b BASELINEThis is useful for ignoring known vulnerabilities that you believe are non-issues (e.g. a cleartext password in a unit test). To generate a baseline report simply run Bandit with the output format set to json (only JSON-formatted files are accepted as a baseline) and output file path specified:bandit -f json -o PATH_TO_OUTPUT_FILE Version control integrationUse pre-commit. Once you have it installed, add this to the .pre-commit-config.yaml in your repository (be sure to update rev to point to a real git tag/revision!):repos:- repo: https://github.com/PyCQA/bandit rev: ” # Update me! hooks: – id: banditThen run pre-commit install and you’re ready to go. ConfigurationAn optional config file may be supplied and may include:lists of tests which should or shouldn’t be runexclude_dirs – sections of the path, that if matched, will be excluded from scanning (glob patterns supported)overridden plugin settings – may provide different settings for some plugins Per Project Command Line ArgsProjects may include a .bandit file that specifies command line arguments that should be supplied for that project. The currently supported arguments are:targets: comma separated list of target dirs/files to run bandit onexclude: comma separated list of excluded pathsskips: comma separated list of tests to skiptests: comma separated list of tests to runTo use this, put a .bandit file in your project’s directory. For example:[bandit]exclude: /test[bandit]tests: B101,B102,B301 ExclusionsIn the event that a line of code triggers a Bandit issue, but that the line has been reviewed and the issue is a false positive or acceptable for some other reason, the line can be marked with a # nosec and any results associated with it will not be reported.For example, although this line may cause Bandit to report a potential security issue, it will not be reported:self.process = subprocess.Popen(‘/bin/echo’, shell=True) # nosec Vulnerability TestsVulnerability tests or "plugins" are defined in files in the plugins directory.Tests are written in Python and are autodiscovered from the plugins directory. Each test can examine one or more type of Python statements. Tests are marked with the types of Python statements they examine (for example: function call, string, import, etc).Tests are executed by the BanditNodeVisitor object as it visits each node in the AST.Test results are maintained in the BanditResultStore and aggregated for output at the completion of a test run. Writing TestsTo write a test:Identify a vulnerability to build a test for, and create a new file in examples/ that contains one or more cases of that vulnerability.Consider the vulnerability you’re testing for, mark the function with one or more of the appropriate decorators: – @checks(‘Call’) – @checks(‘Import’, ‘ImportFrom’) – @checks(‘Str’)Create a new Python source file to contain your test, you can reference existing tests for examples.The function that you create should take a parameter "context" which is an instance of the context class you can query for information about the current element being examined. You can also get the raw AST node for more advanced use cases. Please see the context.py file for more.Extend your Bandit configuration file as needed to support your new test.Execute Bandit against the test file you defined in examples/ and ensure that it detects the vulnerability. Consider variations on how this vulnerability might present itself and extend the example file and the test function accordingly. Extending BanditBandit allows users to write and register extensions for checks and formatters. Bandit will load plugins from two entry-points:bandit.formattersbandit.pluginsFormatters need to accept 4 things:result_store: An instance of bandit.core.BanditResultStorefile_list: The list of files which were inspected in the scopescores: The scores awarded to each file in the scopeexcluded_files: The list of files that were excluded from the scopePlugins tend to take advantage of the bandit.checks decorator which allows the author to register a check for a particular type of AST node. For example@bandit.checks(‘Call’)def prohibit_unsafe_deserialization(context): if ‘unsafe_load’ in context.call_function_name_qual: return bandit.Issue( severity=bandit.HIGH, confidence=bandit.HIGH, text="Unsafe deserialization detected." )To register your plugin, you have two options:If you’re using setuptools directly, add something like the following to your setup call: # If you have an imaginary bson formatter in the bandit_bson module# and a function called `formatter`.entry_points={‘bandit.formatters’: [‘bson = bandit_bson:formatter’]}# Or a check for using mako templates in bandit_mako thatentry_points={‘bandit.plugins’: [‘mako = bandit_mako’]}If you’re using pbr, add something like the following to your setup.cfg file: [entry_points]bandit.formatters = bson = bandit_bson:formatterbandit.plugins = mako = bandit_mako ContributingContributions to Bandit are always welcome!The best way to get started with Bandit is to grab the source:git clone https://github.com/PyCQA/bandit.gitYou can test any changes with tox:pip install toxtox -e pep8tox -e py27tox -e py35tox -e docstox -e coverPlease make PR requests using your own branch, and not master:git checkout -b mychangegit push origin mychange Reporting BugsBugs should be reported on github. To file a bug against Bandit, visit: https://github.com/PyCQA/bandit/issues Under Which Version of Python Should I Install Bandit?The answer to this question depends on the project(s) you will be running Bandit against. If your project is only compatible with Python 2.7, you should install Bandit to run under Python 2.7. If your project is only compatible with Python 3.5, then use 3.5 respectively. If your project supports both, you could run Bandit with both versions but you don’t have to.Bandit uses the ast module from Python’s standard library in order to analyze your Python code. The ast module is only able to parse Python code that is valid in the version of the interpreter from which it is imported. In other words, if you try to use Python 2.7’s ast module to parse code written for 3.5 that uses, for example, yield from with asyncio, then you’ll have syntax errors that will prevent Bandit from working properly. Alternatively, if you are relying on 2.7’s octal notation of 0777 then you’ll have a syntax error if you run Bandit on 3.x. ReferencesBandit docs: https://bandit.readthedocs.io/en/latest/Python AST module documentation: https://docs.python.org/2/library/ast.htmlGreen Tree Snakes – the missing Python AST docs: https://greentreesnakes.readthedocs.org/en/latest/Documentation of the various types of AST nodes that Bandit currently covers or could be extended to cover: https://greentreesnakes.readthedocs.org/en/latest/nodes.htmlDownload Bandit

Link: http://feedproxy.google.com/~r/PentestTools/~3/wb0Wk6QXXFo/bandit-tool-designed-to-find-common.html

Yet Another Meltdown – A Microarchitectural Fill Buffer Data Sampling Vulnerability (CVE-2018-12130)

More than one year ago, security researchers at Google Project Zero have disclosed a series of hardware vulnerabilities affecting Intel® x86 microprocessors. Leveraging a feature of modern processors called speculative execution, as well as timing responses, this family of flaws in hardware defeats the architectural safeguards of the processor and allows unprivileged user-mode applications to […]

Link: https://labs.bitdefender.com/2019/05/yet-another-meltdown-a-microarchitectural-fill-buffer-data-sampling-vulnerability/