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Porch Pirate started as a tool to quickly uncover Postman secrets, and has slowly begun to evolve into a multi-purpose reconaissance / OSINT framework for Postman. While existing tools are great proof of concepts, they only attempt to identify very specific keywords as "secrets", and in very limited locations, with no consideration to recon beyond secrets. We realized we required capabilities that were "secret-agnostic", and had enough flexibility to capture false-positives that still provided offensive value.
Porch Pirate enumerates and presents sensitive results (global secrets, unique headers, endpoints, query parameters, authorization, etc), from publicly accessible Postman entities, such as:
FreshRSS python3 -m pip install porch-pirateThe Porch Pirate client can be used to nearly fully conduct reviews on public Postman entities in a quick and simple fashion. There are intended workflows and particular keywords to be used that can typically maximize results. These methodologies can be located on our blog: Plundering Postman with Porch Pirate.
Porch Pirate supports the following arguments to be performed on collections, workspaces, or users.
--globals--collections--requests--urls--dump--raw--curlporch-pirate -s "coca-cola.com"By default, Porch Pirate will display globals from all active and inactive environments if they are defined in the workspace. Provide a -w argument with the workspace ID (found by performing a simple search, or automatic search dump) to extract the workspace's globals, along with other information.
porch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8When an interesting result has been found with a simple search, we can provide the workspace ID to the -w argument with the --dump command to begin extracting information from the workspace and its collections.
porch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8 --dumpPorch Pirate can be supplied a simple search term, following the --globals argument. Porch Pirate will dump all relevant workspaces tied to the results discovered in the simple search, but only if there are globals defined. This is particularly useful for quickly identifying potentially interesting workspaces to dig into further.
porch-pirate -s "shopify" --globalsPorch Pirate can be supplied a simple search term, following the --dump argument. Porch Pirate will dump all relevant workspaces and collections tied to the results discovered in the simple search. This is particularly useful for quickly sifting through potentially interesting results.
porch-pirate -s "coca-cola.com" --dumpA particularly useful way to use Porch Pirate is to extract all URLs from a workspace and export them to another tool for fuzzing.
porch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8 --urlsPorch Pirate will recursively extract all URLs from workspaces and their collections related to a simple search term.
porch-pirate -s "coca-cola.com" --urlsporch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8 --collectionsporch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8 --requestsporch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8 --rawporch-pirate -w WORKSPACE_IDporch-pirate -c COLLECTION_IDporch-pirate -r REQUEST_IDporch-pirate -u USERNAME/TEAMNAMEPorch Pirate can build curl requests when provided with a request ID for easier testing.
porch-pirate -r 11055256-b1529390-18d2-4dce-812f-ee4d33bffd38 --curlporch-pirate -s coca-cola.com --proxy 127.0.0.1:8080p = porchpirate()
print(p.search('coca-cola.com'))p = porchpirate()
print(p.collections('4127fdda-08be-4f34-af0e-a8bdc06efaba'))p = porchpirate()
collections = json.loads(p.collections('4127fdda-08be-4f34-af0e-a8bdc06efaba'))
for collection in collections['data']:
requests = collection['requests']
for r in requests:
request_data = p.request(r['id'])
print(request_data)p = porchpirate()
print(p.workspace_globals('4127fdda-08be-4f34-af0e-a8bdc06efaba'))Other library usage examples can be located in the examples directory, which contains the following examples:
dump_workspace.pyformat_search_results.pyformat_workspace_collections.pyformat_workspace_globals.pyget_collection.pyget_collections.pyget_profile.pyget_request.pyget_statistics.pyget_team.pyget_user.pyget_workspace.pyrecursive_globals_from_search.pyrequest_to_curl.pysearch.pysearch_by_page.pyworkspace_collections.py
During the reconnaissance phase, an attacker searches for any information about his target to create a profile that will later help him to identify possible ways to get in an organization.
CloudPulse is a powerful tool that simplifies and enhances the analysis of SSL certificate data. It leverages the extensive repository of SSL certificates obtained from the AWS EC2 machines available at Trickest Cloud. With CloudPulse , security researchers can efficiently explore SSL certificate details, uncover potential vulnerabilities, and gather valuable insights for a variety of security-related tasks.
Simplifies security assessments with a user-friendly interface. It allows you to effortlessly find company's asset's on aws cloud:
1- Download CloudPulse :
git clone https://github.com/yousseflahouifi/CloudPulse
cd CloudPulse/
2- Run docker compose :
docker-compose up -d
3- Run script.py script
docker-compose exec web python script.py
4 - Now go to http://:8000/search and enjoy the search engine
1- download CloudPulse :
git clone https://github.com/yousseflahouifi/CloudPulse
cd CloudPulse/
2- Setup virtual environment :
python3 -m venv myenv
source myenv/bin/activate
3- Install requirements.txt file :
pip install -r requirements.txt
4- run an instance of elasticsearch using docker :
docker run -d --name elasticsearch -p 9200:9200 -e "discovery.type=single-node" elasticsearch:6.6.1
5- update script.py and settings file to the host 'localhost':
#script.py
es = Elasticsearch([{'host': 'localhost', 'port': 9200}])
#se/settings.py
ELASTICSEARCH_DSL = {
'default': {
'hosts': 'localhost:9200'
},
}
6- Run script.py to index data in elasticsearch:
python script.py
7- Run the app:
python manage.py runserver 0:8000
Included in the CloudPulse repository is a sample data.csv file containing close to 4,000 records, which provides a glimpse of the tool's capabilities. For the full dataset, visit the Trickest Cloud repository clone the data and update data.csv file (it contains close to 9 millions data)
as an example searching for .mil data gives:
searching for tesla as en example gives :
CloudPulse heavily depends on the data.csv file, which is a sample dataset extracted from the larger collection maintained by Trickest. While the sample dataset provides valuable insights, the tool's full potential is realized when used in conjunction with the complete dataset, which is accessible in the Trickest repository here.
Users are encouraged to refer to the Trickest dataset for a more comprehensive and up-to-date analysis.
SXDork is a powerful tool that utilizes the technique of google dorking to search for specific information on the internet. Google dorking is a method of using advanced search operators and keywords to uncover sensitive information that is publicly available on the internet. SXDork offers a wide range of options to search for different types of dorks, such as domain login dork, wpadmin dork, SQL dork, configuration file dorks, logfile dorks, dashboard dork, id_rsa dorks, ftp dorks, backup file dorks, mail archive dorks, password dorks, DCIM photos dork, and CCTV dorks.
One of the key features of SXDork is its ability to search dorks using the -s flag. This function allows users to retrieve a significant amount of information related to search keywords. Users can specify specific keywords and the tool will search for all the related information available on the internet. Additionally, users can use the -r flag to set the number of results that will be displayed. The default setting is 10 results, however, users can increase or decrease the number of results as per their requirement. This feature is useful for users who are looking for specific information and want to filter through the results quickly.
SXDork also allows users to search wildcard domains and find a wide range of information. This feature is particularly useful for security researchers, penetration testers and other professionals who need to find sensitive information on the internet. With the ability to search for different types of dorks, wildcard domains and filter through results, SXDork is a powerful tool that can help users find information that is publicly available on the internet.
SXDork has the ability to search for information on multiple domains. By default, the tool searches for information on pastebin.com and controlc.com, but you can easily add more domains to search against. To do this, you can navigate to the src directory and edit the dorks.py file, where you will see an array called src that contains the default domains. Simply add more domains to this array, and the next time you run a search query, SXDork will check all the domains in the array for the keyword you are searching for. This allows you to easily find information across multiple domains.
git clone https://github.com/samhaxr/SXDork.git
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
python SXDork.py
usage: SXDork.py [-h] [-s SEARCH] [-r RESULT] [-dl DOMLOGIN] [-da DOMADMIN]
[-wp WPADMIN] [-lp LPANEL] [-sql SQLFILE] [-cnf CONFILE]
[-log LOGFILE] [-dash DASHBOARD] [-rsa IDRSA] [-ftp FTPFILE]
[-bck BACKUPFILE] [-ma MAILARCHIVE] [-pw PASSWORD]
[-pic PHOTOS] [-cam CCTVCAM]
Search keywords using google dork
optional arguments:
-h, --help show this help message and exit
-s SEARCH, --search SEARCH
Search keyword with dork
-r RESULT, --result RESULT
Number of output result
-dl DOMLOGIN, --domlogin DOMLOGIN
Search domain(s) for login pages
-da DOMADMIN, --domadmin DOMADMIN
Search domain(s) for admin panels
-wp WPADMIN, --wpadmin WPADMIN
Search domain(s) for wordpress admin
-lp LPANEL, --lpanel LPANEL
Search domain(s) for login panels
-sql SQLFILE, --sqlfile SQLFILE
Search domain(s) for sql database files
-cnf CONFILE, --confile CONFILE
Search domain(s) for configuration files
-log LOGFILE, --logfile LOGFILE
Search domain(s) for log files
-dash DASHBOARD, --dashboard DASHBOARD
Search domain(s) for the dashboard
-rsa IDRSA, --idrsa IDRSA
Search domain(s) for id_rsa pub keys
-ftp FTPFILE, --ftpfile FTPFILE
Search domain(s) for FTP files
-bck BACKUPFILE, --backupfile BACKUPFILE
Search domain(s) for backup files
-ma MAILARCHIVE, --mailarchive MAILARCHIVE
Search domain(s) for ma il archives
-pw PASSWORD, --password PASSWORD
Search domain(s) for passwords
-pic PHOTOS, --photos PHOTOS
Search domain(s) for DCIM/Photos
-cam CCTVCAM, --cctvcam CCTVCAM
Search domain(s) for CCTV/CAMs
An automatic unpacker and logger for DotNet Framework targeting files! This tool has been unveiled at Black Hat USA 2022.
The automatic detection and classification of any given file in a reliable manner is often considered the holy grail of malware analysis. The trials and tribulations to get there are plenty, which is why the creation of such a system is held in high regard. When it comes to DotNet targeting binaries, our new open-source tool DotDumper aims to assist in several of the crucial steps along the way: logging (in-memory) activity, dumping interesting memory segments, and extracting characteristics from the given sample.
In brief, manual unpacking is a tedious process which consumes a disproportional amount of time for analysts. Obfuscated binaries further increase the time an analyst must spend to unpack a given file. When scaling this, organizations need numerous analysts who dissect malware daily, likely in combination with a scalable sandbox. The lost valuable time could be used to dig into interesting campaigns or samples to uncover new threats, rather than the mundane generic malware that is widely spread. Afterall, analysts look for the few needles in the haystack.
So, what difference does DotDumper make? Running a DotNet based malware sample via DotDumper provides log files of crucial, contextualizing, and common function calls in three formats (human readable plaintext, JSON, and XML), as well as copies from useful in-memory segments. As such, an analyst can skim through the function call log. Additionally, the dumped files can be scanned to classify them, providing additional insight into the malware sample and the data it contains. This cuts down on time vital to the triage and incident response processes, and frees up SOC analyst and researcher time for more sophisticated analysis needs.
To log and dump the contextualizing function calls and their results, DotDumper uses a mixture of reflection and managed hooks, all written in pure C#. Below, key features will be highlighted and elaborated upon, in combination with excerpts of DotDumper’s results of a packed AgentTesla stealer sample, the hashes of which are below.
| Hash type | Hash value |
|---|---|
| SHA-256 | b7512e6b8e9517024afdecc9e97121319e7dad2539eb21a79428257401e5558d |
| SHA-1 | c10e48ee1f802f730f41f3d11ae9d7bcc649080c |
| MD-5 | 23541daadb154f1f59119952e7232d6b |
DotDumper is accessible through a command-line interface, with a variety of arguments. The image below shows the help menu. Note that not all arguments will be discussed, but rather the most used ones.
The minimal requirement to run a given sample, is to provide the “-file” argument, along with a file name or file path. If a full path is given, it is used. If a file name is given, the current working directory is checked, as well as the folder of DotDumper’s executable location.
Unless a directory name is provided, the “-log” folder name is set equal to the file name of the sample without the extension (if any). The folder is located in the same folder as DotDumper resides in, which is where the logs and dumped files will be saved in.
In the case of a library, or an alternative entry point into a binary, one must override the entry point using “-overrideEntry true”. Additionally, one has to provide the fully qualified class, which includes the name space using “-fqcn My.NameSpace.MyClass”. This tells DotDumper which class to select, which is where the provided function name (using “-functionName MyFunction”) is retrieved.
If the selected function requires arguments, one has to provide the number of arguments using “-argc” and the number of required arguments. The argument types and values are to be provided as “string|myValue int|9”. Note that when spaces are used in the values, the argument on the command-line interface needs to be encapsulated between quotes to ensure it is passed as a single argument.
Other less frequently used options such as “-raceTime” or “-deprecated” are safe in their default settings but might require tweaking in the future due to changes in the DotNet Framework. They are currently exposed in the command-line interface to easily allow changes, if need be, even if one is using an older version of DotDumper when the time comes.
Logging and dumping are the two core features of DotDumper. To minimize the amount of time the analysis takes, the logging should provide context to the analyst. This is done by providing the analyst with the following information for each logged function call:
Note that for each dumped file, the file name is equal to the file’s SHA-256 hash.
To clarify the above, an excerpt of a log is given below. The excerpt shows the details for the aforementioned AgentTesla sample, where it loads the second stage using DotNet’s Assembly.Load function.
First, the local system time is given, together with the original function’s return type, name, and argument(s). Second, the stack trace is given, where it shows that the sample’s main function leads to a constructor, initialises the components, and calls two custom functions. The Assembly.Load function was called from within “NavigationLib.TaskEightBestOil.GGGGGGGGGGGGGGGGGGGG(String str)”. This provides context for the analyst to find the code around this call if it is of interest.
Then, information regarding the assembly call order is given. The more stages are loaded, the more complex it becomes to see via which stages the call came to be. One normally expects one stage to load the next, but in some cases later stages utilize previous stages in a non-linear order. Additionally, information regarding the originating assembly is given to further enrich the data for the analyst.
Next, the parent hash is given. The parent of a stage is the previous stage, which in this example is not yet present. The newly loaded stage will have this stage as its parent. This allows the analyst to correlate events more easily.
Finally, the function’s return type and value are stored, along with the type, name, and value of each argument that is passed to the hooked function. If any variable is larger than 100 bytes in size, it is stored on the disk instead. A reference is then inserted in the log to reference the file, rather than showing the value. The threshold has been set to avoid hiccups in the printing of the log, as some arrays are thousands of indices in size.
Per Microsoft’s documentation, reflection is best summarized as “[…] provides objects that encapsulate assemblies, modules, and types”. In short, this allows the dynamic creation and invocation of DotNet classes and functions from the malware sample. DotDumper contains a reflective loader which allows an analyst to load and analyze both executables and libraries, as long as they are DotNet Framework based.
To utilize the loader, one has to opt to overwrite the entry point in the command-line interface, specify the class (including the namespace it resides in) and function name within a given file. Optionally, one can provide arguments to the specified function, for all native types and arrays thereof. Examples of native types are int, string, char, and arrays such as int[], string[], and char[]. All the arguments are to be provided via the command-line interface, where both the type and the value are to be specified.
Not overriding the entry point results in the default entry point being used. By default, an empty string array is passed towards the sample’s main function, as if the sample is executed without arguments. Additionally, reflection is often used by loaders to invoke a given function in a given class in the next stage. Sometimes, arguments are passed along as well, which are used later to decrypt a resource. In the aforementioned AgentTesla sample, this exact scenario plays out. DotDumper’s invoke related hooks log these occurrences, as can be seen below.
The function name in the first line is not an internal function of the DotNet Framework, but rather a call to a specific function in the second stage. The types and names of the three arguments are listed in the function signature. Their values can be found in the function argument information section. This would allow an analyst to load the second stage in a custom loader with the given values for the arguments, or even do this using DotDumper by loading the previously dumped stage and providing the arguments.
Before going into managed hooks, one needs to understand how hooks work. There are two main variables to consider here: the target function and a controlled function which is referred to as the hook. Simply put, the memory at the target function (i.e. Assembly.Load) is altered to instead to jump to the hook. As such, the program’s execution flow is diverted. The hook can then perform arbitrary actions, optionally call the original function, after which it returns the execution to the caller together with a return value if need be. The diagram below illustrates this process.
Knowing what hooks are is essential to understand what managed hooks are. Managed code is executed in a virtual and managed environment, such as the DotNet runtime or Java’s virtual machine. Obtaining the memory address where the managed function resides differs from an unmanaged language such as C. Once the correct memory addresses for both functions have been obtained, the hook can be set by directly accessing memory using unsafe C#, along with DotNet’s interoperability service to call native Windows API functionality.
Since DotDumper is written in pure C# without any external dependencies, one can easily extend the framework using Visual Studio. The code is documented in this blog, on GitHub, and in classes, in functions, and in-line in the source code. This, in combination with the clear naming scheme, allows anyone to modify the tool as they see fit, minimizing the time and effort that one needs to spend to understand the tool. Instead, it allows developers and analysts alike to focus their efforts on the tool’s improvement.
With the goal and features of DotDumper clear, it might seem as if there’s overlap with known publicly available tools such as ILSpy, dnSpyEx, de4dot, or pe-sieve. Note that there is no intention to proclaim one tool is better than another, but rather how the tools differ.
DotDumper’s goal is to log and dump crucial, contextualizing, and common function calls from DotNet targeting samples. ILSpy is a DotNet disassembler and decompiler, but does not allow the execution of the file. dnSpyEx (and its predecessor dnSpy) utilise ILSpy as the disassembler and decompiler component, while adding a debugger. This allows one to manually inspect and manipulate memory. de4dot is solely used to deobfuscate DotNet binaries, improving the code’s readability for human eyes. The last tool in this comparison, pe-sieve, is meant to detect and dump malware from running processes, disregarding the used programming language. The table below provides a graphical overview of the above-mentioned tools.
DotDumper is under constant review and development, all of which is focused on two main areas of interest: bug fixing and the addition of new features. During the development, the code was tested, but due to injection of hooks into the DotNet Framework’s functions which can be subject to change, it’s very well possible that there are bugs in the code. Anyone who encounters a bug is urged to open an issue on the GitHub repository, which will then be looked at. The suggestion of new features is also possible via the GitHub repository. For those with a GitHub account, or for those who rather not publicly interact, feel free to send me a private message on my Twitter.
Needless to say, if you've used DotDumper during an analysis, or used it in a creative way, feel free to reach out in public or in private! There’s nothing like hearing about the usage of a home-made tool!
There is more in store for DotDumper, and an update will be sent out to the community once it is available!
