As I was going through web application vulnerabilities during my 100 days of hacking, I came across this interesting topic Broken Access…Continue reading on Medium » (https://medium.com/@gathereisaac20/broken-access-control-overview-801602f03f00?source=rss------bug_bounty-5)
How I did Full Account Takeover (FATO) using forgot password link?
https://a-manonearth.medium.com/how-i-did-full-account-takeover-fato-using-forgot-password-link-61b8390b0731?source=rss------bug_bounty-5
https://a-manonearth.medium.com/how-i-did-full-account-takeover-fato-using-forgot-password-link-61b8390b0731?source=rss------bug_bounty-5
How I was able to takeover admin account by exploiting forgot password functionality.Continue reading on Medium » (https://a-manonearth.medium.com/how-i-did-full-account-takeover-fato-using-forgot-password-link-61b8390b0731?source=rss------bug_bounty-5)
Autotimeliner - Automagically Extract Forensic Timeline From Volatile Memory Dump
http://www.kitploit.com/2022/02/autotimeliner-automagically-extract.html
http://www.kitploit.com/2022/02/autotimeliner-automagically-extract.html
Automagically extract forensic (https://www.kitploit.com/search/label/Forensic) timeline from volatile memory dumps. Requirements Python 3 Volatility mactime (from SleuthKit) (Developed and tested on Debian (https://www.kitploit.com/search/label/Debian) 9.6 with Volatility 2.6-1 and sleuthkit 4.4.0-5)
How it works AutoTimeline automates this workflow (https://www.andreafortuna.org/dfir/forensic-timeline-creation-my-own-workflow/): Identify correct volatility (https://www.kitploit.com/search/label/Volatility) profile for the memory image. Runs the timeliner plugin (https://www.kitploit.com/search/label/Plugin) against volatile memory dump using volatility. Runs the mftparser volatility plugin, in order to extract $MFT from memory and generate a bodyfile. Runs the shellbags volatility plugin in order to generate a bodyfile of the user activity. (suggested by Matteo Cantoni (https://github.com/mcantoni)). Merges the timeliner, mftparser and shellbags output files into a single bodyfile. Sorts and filters the bodyfile using mactime and exports data as CSV. Installation Simply clone the GitHub repository: git clone https://github.com/andreafortuna/autotimeliner.git Usage Memory dump file -t TIMEFRAME, --timeframe TIMEFRAME Timeframe used to filter the timeline (YYYY-MM-DD ..YYYY-MM-DD) -p CUSTOMPROFILE, --customprofile CUSTOMPROFILE Jump image identification and use a custom memory profile">autotimeline.py [-h] -f IMAGEFILE [-t TIMEFRAME] [-p CUSTOMPROFILE]
optional arguments:
-h, --help show this help message and exit
-f IMAGEFILE, --imagefile IMAGEFILE
Memory dump file
-t TIMEFRAME, --timeframe TIMEFRAME
Timeframe used to filter the timeline (YYYY-MM-DD
..YYYY-MM-DD)
-p CUSTOMPROFILE, --customprofile CUSTOMPROFILE
Jump image identification and use a custom memory
profile
Examples Extract timeline from TargetServerMemory.raw, limited to a timeframe from 2018-10-17 to 2018-10-21: ./autotimeline.py -f TargetServerMemory.raw -t 2018-10-17..2018-10-21 Extract timeline from all images in current directory, limited to a timeframe from 2018-10-17 to 2018-10-21: ./autotimeline.py -f ./*.raw -t 2018-10-17..2018-10-21 Extract timeline from TargetServerMemory.raw, using a custom memory profile: ./autotimeline.py -f TargetServerMemory.raw -p Win2008R2SP1x64 All timelines will be saved as $ORIGINALFILENAME-timeline.csv. TODO Better image identification Better error trapping
Download Autotimeliner (https://github.com/andreafortuna/autotimeliner)
How it works AutoTimeline automates this workflow (https://www.andreafortuna.org/dfir/forensic-timeline-creation-my-own-workflow/): Identify correct volatility (https://www.kitploit.com/search/label/Volatility) profile for the memory image. Runs the timeliner plugin (https://www.kitploit.com/search/label/Plugin) against volatile memory dump using volatility. Runs the mftparser volatility plugin, in order to extract $MFT from memory and generate a bodyfile. Runs the shellbags volatility plugin in order to generate a bodyfile of the user activity. (suggested by Matteo Cantoni (https://github.com/mcantoni)). Merges the timeliner, mftparser and shellbags output files into a single bodyfile. Sorts and filters the bodyfile using mactime and exports data as CSV. Installation Simply clone the GitHub repository: git clone https://github.com/andreafortuna/autotimeliner.git Usage Memory dump file -t TIMEFRAME, --timeframe TIMEFRAME Timeframe used to filter the timeline (YYYY-MM-DD ..YYYY-MM-DD) -p CUSTOMPROFILE, --customprofile CUSTOMPROFILE Jump image identification and use a custom memory profile">autotimeline.py [-h] -f IMAGEFILE [-t TIMEFRAME] [-p CUSTOMPROFILE]
optional arguments:
-h, --help show this help message and exit
-f IMAGEFILE, --imagefile IMAGEFILE
Memory dump file
-t TIMEFRAME, --timeframe TIMEFRAME
Timeframe used to filter the timeline (YYYY-MM-DD
..YYYY-MM-DD)
-p CUSTOMPROFILE, --customprofile CUSTOMPROFILE
Jump image identification and use a custom memory
profile
Examples Extract timeline from TargetServerMemory.raw, limited to a timeframe from 2018-10-17 to 2018-10-21: ./autotimeline.py -f TargetServerMemory.raw -t 2018-10-17..2018-10-21 Extract timeline from all images in current directory, limited to a timeframe from 2018-10-17 to 2018-10-21: ./autotimeline.py -f ./*.raw -t 2018-10-17..2018-10-21 Extract timeline from TargetServerMemory.raw, using a custom memory profile: ./autotimeline.py -f TargetServerMemory.raw -p Win2008R2SP1x64 All timelines will be saved as $ORIGINALFILENAME-timeline.csv. TODO Better image identification Better error trapping
Download Autotimeliner (https://github.com/andreafortuna/autotimeliner)
Hacking on Medium
5 Incredible Hacks that you still don’t know for Building in Minecraft!!!
It will be more interesting and easier to discover and learn those tips if you >>CLICK HERE<<
Continue reading on Medium »
5 Incredible Hacks that you still don’t know for Building in Minecraft!!!
It will be more interesting and easier to discover and learn those tips if you >>CLICK HERE<<
Continue reading on Medium »
Medium
5 Incredible Hacks that you still don’t know for Building in Minecraft!!!
It will be more interesting and easier to discover and learn those tips if you >>CLICK HERE<< to go to watch a full and shorter video on…
Hacking on Medium
Hacking Technical Interviewing
https://cdn-images-1.medium.com/max/1352/1*qOZH5br2hVHS90GniqzwaA.png
So you’re looking for a good developer, maybe even a great one to join your team. But what is a great developer?
Continue reading on Melio’s R&D blog »
Hacking Technical Interviewing
https://cdn-images-1.medium.com/max/1352/1*qOZH5br2hVHS90GniqzwaA.png
So you’re looking for a good developer, maybe even a great one to join your team. But what is a great developer?
Continue reading on Melio’s R&D blog »
Medium
Hacking Technical Interviewing
So you’re looking for a good developer, maybe even a great one to join your team. But what is a great developer?
Hacking on Medium
On My Way To 100K followers
https://cdn-images-1.medium.com/max/777/1*E_K7wzEOAnF_auSwH9uNjg.png
You can go from 1.1K to 99.9K followers really quick (you won’t make money though)!
Continue reading on Medium »
On My Way To 100K followers
https://cdn-images-1.medium.com/max/777/1*E_K7wzEOAnF_auSwH9uNjg.png
You can go from 1.1K to 99.9K followers really quick (you won’t make money though)!
Continue reading on Medium »
Medium
On My Way To 100K followers
You can go from 1.1K to 99.9K followers really quick (you won’t make money though)!
Hacking on Medium
QUAXAR is coming soon.
https://cdn-images-1.medium.com/max/905/1*d7dApNyzCtWOjHKYa0PZqg.jpeg
Our upgraded CTI solution fully equipped with new features will soon be unveiled.
Continue reading on S2W BLOG »
QUAXAR is coming soon.
https://cdn-images-1.medium.com/max/905/1*d7dApNyzCtWOjHKYa0PZqg.jpeg
Our upgraded CTI solution fully equipped with new features will soon be unveiled.
Continue reading on S2W BLOG »
Medium
QUAXAR, an upgraded version of our CTI solution is coming SOON
Our upgraded CTI solution fully equipped with new features will soon be unveiled.
Hacking on Medium
10 BEST Ethical Hacking Books [2022 Edition]
https://cdn-images-1.medium.com/max/600/0*igxa_rJHlE2QNl_L.jpg
Ethical hacking is the process of detecting flaws in computer systems/networks and devising countermeasures to protect such flaws. Before…
Continue reading on Medium »
10 BEST Ethical Hacking Books [2022 Edition]
https://cdn-images-1.medium.com/max/600/0*igxa_rJHlE2QNl_L.jpg
Ethical hacking is the process of detecting flaws in computer systems/networks and devising countermeasures to protect such flaws. Before…
Continue reading on Medium »
Medium
10 BEST Ethical Hacking Books [2022 Edition]
Ethical hacking is the process of detecting flaws in computer systems/networks and devising countermeasures to protect such flaws. Before…
Hacking on Medium
Identity and Access Management (IAM): Simplified
https://cdn-images-1.medium.com/max/710/0*vTAUezdEDDb5OqCu.jpg
Cloud security is crucial in today’s era as we see the increasing rate of cybercrime. Businesses are rapidly migrating to cloud to prevent…
Continue reading on Medium »
Identity and Access Management (IAM): Simplified
https://cdn-images-1.medium.com/max/710/0*vTAUezdEDDb5OqCu.jpg
Cloud security is crucial in today’s era as we see the increasing rate of cybercrime. Businesses are rapidly migrating to cloud to prevent…
Continue reading on Medium »
Medium
Identity and Access Management (IAM): Simplified
Cloud security is crucial in today’s era as we see the increasing rate of cybercrime. Businesses are rapidly migrating to cloud to prevent…
Hacking on Medium
Why Zero Trust is the Future of Corporate Cybersecurity
https://cdn-images-1.medium.com/max/1000/0*TLyvYxsmGJ45lewz
In a world driven by digital business, enterprise security needs to be continuously monitored and improved to keep up with evolving…
Continue reading on Netacea »
Why Zero Trust is the Future of Corporate Cybersecurity
https://cdn-images-1.medium.com/max/1000/0*TLyvYxsmGJ45lewz
In a world driven by digital business, enterprise security needs to be continuously monitored and improved to keep up with evolving…
Continue reading on Netacea »
Medium
Why Zero Trust is the Future of Corporate Cybersecurity
In a world driven by digital business, enterprise security needs to be continuously monitored and improved to keep up with evolving…
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KitPloit - PenTest Tools!
Autotimeliner - Automagically Extract Forensic Timeline From Volatile Memory Dump
http://2.bp.blogspot.com/-W2Z-SKv-dq4/Yd0eVCla67I/AAAAAAAA8jE/S77Wdb-UiW0Fb_NqRh5F6q-rgMTxAVwDQCK4BGAYYCw/w640-h376/autotimeliner_1-771906.gif
Automagically extract forensic timeline from volatile memory dumps.
Requirements
* Python 3
* Volatility
* mactime (from SleuthKit)
(Developed and tested on Debian 9.6 with Volatility 2.6-1 and sleuthkit 4.4.0-5)
How it works
AutoTimeline automates this workflow:
* Identify correct volatility profile for the memory image.
* Runs the timeliner plugin against volatile memory dump using volatility.
* Runs the mftparser volatility plugin, in order to extract $MFT from memory and generate a bodyfile.
* Runs the shellbags volatility plugin in order to generate a bodyfile of the user activity. (suggested by Matteo Cantoni).
* Merges the timeliner, mftparser and shellbags output files into a single bodyfile.
* Sorts and filters the bodyfile using mactime and exports data as CSV.
Installation
Simply clone the GitHub repository:
Usage
Memory dump file -t TIMEFRAME, --timeframe TIMEFRAME Timeframe used to filter the timeline (YYYY-MM-DD ..YYYY-MM-DD) -p CUSTOMPROFILE, --customprofile CUSTOMPROFILE Jump image identification and use a custom memory profile">
Examples
Extract timeline from TargetServerMemory.raw, limited to a timeframe from 2018-10-17 to 2018-10-21:
Extract timeline from all images in current directory, limited to a timeframe from 2018-10-17 to 2018-10-21:
Extract timeline from TargetServerMemory.raw, using a custom memory profile:
All timelines will be saved as $ORIGINALFILENAME-timeline.csv.
TODO
* Better image identification
* Better error trapping
Download Autotimeliner
Autotimeliner - Automagically Extract Forensic Timeline From Volatile Memory Dump
http://2.bp.blogspot.com/-W2Z-SKv-dq4/Yd0eVCla67I/AAAAAAAA8jE/S77Wdb-UiW0Fb_NqRh5F6q-rgMTxAVwDQCK4BGAYYCw/w640-h376/autotimeliner_1-771906.gif
Automagically extract forensic timeline from volatile memory dumps.
Requirements
* Python 3
* Volatility
* mactime (from SleuthKit)
(Developed and tested on Debian 9.6 with Volatility 2.6-1 and sleuthkit 4.4.0-5)
How it works
AutoTimeline automates this workflow:
* Identify correct volatility profile for the memory image.
* Runs the timeliner plugin against volatile memory dump using volatility.
* Runs the mftparser volatility plugin, in order to extract $MFT from memory and generate a bodyfile.
* Runs the shellbags volatility plugin in order to generate a bodyfile of the user activity. (suggested by Matteo Cantoni).
* Merges the timeliner, mftparser and shellbags output files into a single bodyfile.
* Sorts and filters the bodyfile using mactime and exports data as CSV.
Installation
Simply clone the GitHub repository:
git clone https://github.com/andreafortuna/autotimeliner.gitUsage
Memory dump file -t TIMEFRAME, --timeframe TIMEFRAME Timeframe used to filter the timeline (YYYY-MM-DD ..YYYY-MM-DD) -p CUSTOMPROFILE, --customprofile CUSTOMPROFILE Jump image identification and use a custom memory profile">
autotimeline.py [-h] -f IMAGEFILE [-t TIMEFRAME] [-p CUSTOMPROFILE]
optional arguments:
-h, --help show this help message and exit
-f IMAGEFILE, --imagefile IMAGEFILE
Memory dump file
-t TIMEFRAME, --timeframe TIMEFRAME
Timeframe used to filter the timeline (YYYY-MM-DD
..YYYY-MM-DD)
-p CUSTOMPROFILE, --customprofile CUSTOMPROFILE
Jump image identification and use a custom memory
profile
Examples
Extract timeline from TargetServerMemory.raw, limited to a timeframe from 2018-10-17 to 2018-10-21:
./autotimeline.py -f TargetServerMemory.raw -t 2018-10-17..2018-10-21Extract timeline from all images in current directory, limited to a timeframe from 2018-10-17 to 2018-10-21:
./autotimeline.py -f ./*.raw -t 2018-10-17..2018-10-21Extract timeline from TargetServerMemory.raw, using a custom memory profile:
./autotimeline.py -f TargetServerMemory.raw -p Win2008R2SP1x64All timelines will be saved as $ORIGINALFILENAME-timeline.csv.
TODO
* Better image identification
* Better error trapping
Download Autotimeliner
Continuing with Computer engineering degree VS online WGU degree ?
https://www.reddit.com/r/Pentesting/comments/ss9pk5/continuing_with_computer_engineering_degree_vs/
<!-- SC_OFF -->So i am studying computer engineering, i have like 1.5 years left to graduate and i hate everything about it. i can drop out easily and join an online cyber security school like WGU and prolly finish it in 6 months, but i need solid advice as this is a big step for me, is a cyber security degree from WGU valuable on the resume just like an engineering degree would ? i heard that employers wont be impressed by a degree you can get in 6 months, so is it worth the transition ? <!-- SC_ON --> submitted by /u/watermelonSoundsNice (https://www.reddit.com/user/watermelonSoundsNice)
[link] (https://www.reddit.com/r/Pentesting/comments/ss9pk5/continuing_with_computer_engineering_degree_vs/) [comments] (https://www.reddit.com/r/Pentesting/comments/ss9pk5/continuing_with_computer_engineering_degree_vs/)
https://www.reddit.com/r/Pentesting/comments/ss9pk5/continuing_with_computer_engineering_degree_vs/
<!-- SC_OFF -->So i am studying computer engineering, i have like 1.5 years left to graduate and i hate everything about it. i can drop out easily and join an online cyber security school like WGU and prolly finish it in 6 months, but i need solid advice as this is a big step for me, is a cyber security degree from WGU valuable on the resume just like an engineering degree would ? i heard that employers wont be impressed by a degree you can get in 6 months, so is it worth the transition ? <!-- SC_ON --> submitted by /u/watermelonSoundsNice (https://www.reddit.com/user/watermelonSoundsNice)
[link] (https://www.reddit.com/r/Pentesting/comments/ss9pk5/continuing_with_computer_engineering_degree_vs/) [comments] (https://www.reddit.com/r/Pentesting/comments/ss9pk5/continuing_with_computer_engineering_degree_vs/)
Autotimeliner - Automagically Extract Forensic Timeline From Volatile Memory Dump
Automagically extract forensic timeline from volatile memory dumps. Requirements Python 3 Volatility mactime (from SleuthKit) (Developed and tested on Debian 9.6 with Volatility 2.6-1 and sleuthkit 4.4.0-5) How it works AutoTimeline automates this workflow: Identify correct volatility profile for the memory image. Runs the timeliner plugin against volatile memory dump using volatility. Runs the mftparser volatility plugin, in order to extract $MFT from memory and generate a bodyfile. Runs the shellbags volatility plugin in order to generate a bodyfile of the user activity. (suggested by Matteo Cantoni). Merges the timeliner, mftparser and shellbags output files into a single bodyfile. Sorts and filters the bodyfile using mactime and exports data as CSV. Installation Simply clone the GitHub repository: git clone https://github.com/andreafortuna/autotimeliner.git Usage Memory dump file -t TIMEFRAME, --timeframe TIMEFRAME Timeframe used to filter the timeline (YYYY-MM-DD ..YYYY-MM-DD) -p CUSTOMPROFILE, --customprofile CUSTOMPROFILE Jump image identification and use a custom memory profile">autotimeline.py -h -f IMAGEFILE -t TIMEFRAME -p CUSTOMPROFILEoptional arguments: -h, --help show this help message and exit -f IMAGEFILE, --imagefile IMAGEFILE Memory dump file -t TIMEFRAME, --timeframe TIMEFRAME Timeframe used to filter the timeline (YYYY-MM-DD ..YYYY-MM-DD) -p CUSTOMPROFILE, --customprofile CUSTOMPROFILE Jump image identification and use a custom memory profile Examples Extract timeline from TargetServerMemory.raw, limited to a timeframe from 2018-10-17 to 2018-10-21: ./autotimeline.py -f TargetServerMemory.raw -t 2018-10-17..2018-10-21 Extract timeline from all images in current directory, limited to a timeframe from 2018-10-17 to 2018-10-21: ./autotimeline.py -f ./*.raw -t 2018-10-17..2018-10-21 Extract timeline from TargetServerMemory.raw, using a custom memory profile: ./autotimeline.py -f TargetServerMemory.raw -p Win2008R2SP1x64 All timelines will be saved as $ORIGINALFILENAME-timeline.csv. TODO Better image identification Better error trapping Download Autotimeliner
Read more...
Automagically extract forensic timeline from volatile memory dumps. Requirements Python 3 Volatility mactime (from SleuthKit) (Developed and tested on Debian 9.6 with Volatility 2.6-1 and sleuthkit 4.4.0-5) How it works AutoTimeline automates this workflow: Identify correct volatility profile for the memory image. Runs the timeliner plugin against volatile memory dump using volatility. Runs the mftparser volatility plugin, in order to extract $MFT from memory and generate a bodyfile. Runs the shellbags volatility plugin in order to generate a bodyfile of the user activity. (suggested by Matteo Cantoni). Merges the timeliner, mftparser and shellbags output files into a single bodyfile. Sorts and filters the bodyfile using mactime and exports data as CSV. Installation Simply clone the GitHub repository: git clone https://github.com/andreafortuna/autotimeliner.git Usage Memory dump file -t TIMEFRAME, --timeframe TIMEFRAME Timeframe used to filter the timeline (YYYY-MM-DD ..YYYY-MM-DD) -p CUSTOMPROFILE, --customprofile CUSTOMPROFILE Jump image identification and use a custom memory profile">autotimeline.py -h -f IMAGEFILE -t TIMEFRAME -p CUSTOMPROFILEoptional arguments: -h, --help show this help message and exit -f IMAGEFILE, --imagefile IMAGEFILE Memory dump file -t TIMEFRAME, --timeframe TIMEFRAME Timeframe used to filter the timeline (YYYY-MM-DD ..YYYY-MM-DD) -p CUSTOMPROFILE, --customprofile CUSTOMPROFILE Jump image identification and use a custom memory profile Examples Extract timeline from TargetServerMemory.raw, limited to a timeframe from 2018-10-17 to 2018-10-21: ./autotimeline.py -f TargetServerMemory.raw -t 2018-10-17..2018-10-21 Extract timeline from all images in current directory, limited to a timeframe from 2018-10-17 to 2018-10-21: ./autotimeline.py -f ./*.raw -t 2018-10-17..2018-10-21 Extract timeline from TargetServerMemory.raw, using a custom memory profile: ./autotimeline.py -f TargetServerMemory.raw -p Win2008R2SP1x64 All timelines will be saved as $ORIGINALFILENAME-timeline.csv. TODO Better image identification Better error trapping Download Autotimeliner
Read more...
GitHub
GitHub - andreafortuna/autotimeliner: Automagically extract forensic timeline from volatile memory dump
Automagically extract forensic timeline from volatile memory dump - andreafortuna/autotimeliner
How to exploit 'gateway.php' for a CTF?
https://www.reddit.com/r/Pentesting/comments/ss9tls/how_to_exploit_gatewayphp_for_a_ctf/
<!-- SC_OFF -->I am trying to solve a CTF which is supposed to be basic. It has this login page called 'gateway.php'. I am not able to figure out how to exploit it. I understand that a "Authentication Bypass" attack is what I need to do, but I don't know how to. All help will be highly appreciated. <!-- SC_ON --> submitted by /u/elpasolol (https://www.reddit.com/user/elpasolol)
[link] (https://www.reddit.com/r/Pentesting/comments/ss9tls/how_to_exploit_gatewayphp_for_a_ctf/) [comments] (https://www.reddit.com/r/Pentesting/comments/ss9tls/how_to_exploit_gatewayphp_for_a_ctf/)
https://www.reddit.com/r/Pentesting/comments/ss9tls/how_to_exploit_gatewayphp_for_a_ctf/
<!-- SC_OFF -->I am trying to solve a CTF which is supposed to be basic. It has this login page called 'gateway.php'. I am not able to figure out how to exploit it. I understand that a "Authentication Bypass" attack is what I need to do, but I don't know how to. All help will be highly appreciated. <!-- SC_ON --> submitted by /u/elpasolol (https://www.reddit.com/user/elpasolol)
[link] (https://www.reddit.com/r/Pentesting/comments/ss9tls/how_to_exploit_gatewayphp_for_a_ctf/) [comments] (https://www.reddit.com/r/Pentesting/comments/ss9tls/how_to_exploit_gatewayphp_for_a_ctf/)