内容简介:PANDAcap is a framework for streamlining the capture ofYou can read more about PANDAcap in our
PANDAcap
PANDAcap is a framework for streamlining the capture of PANDA execution traces. The main goal of PANDAcap is to make it easier to create datasets of PANDA traces . PANDAcap offers support for Docker as well as support for runtime customization of both Docker containers and the VMs used to capture the traces. It relies on the recctrl PANDA plugin to automate starting and stopping of recording. The plugin has been developed for use with PANDAcap and later merged with the PANDA mainline.
You can read more about PANDAcap in our EuroSec 2020 paper :
-
Manolis Stamatogiannakis, Herbert Bos, and Paul Groth. PANDAcap: A Framework for Streamlining Collection of Full-System Traces. In Proceedings of the 13th European Workshop on Systems Security , EuroSec '20 , Heraklion, Greece, April 2020. doi: 10.1145/3380786.3391396 , preprint: vusec.net
bibtex (paper)@inproceedings{pandacap-eurosec20, author = {Stamatogiannakis, Manolis and Bos, Herbert and Groth, Paul}, title = {{PANDAcap: A Framework for Streamlining Collection of Full-System Traces}}, booktitle = {Proceedings of the 13th European Workshop on Systems Security}, series = {EuroSec '20}, year = {2020}, month = {April}, address = {Heraklion, Greece}, url = {https://doi.org/10.1145/3380786.3391396}, doi = {10.1145/3380786.3391396}, keywords = {framework, PANDA, record and replay, docker, honeypot, dataset}, }
bibtex (dataset)@dataset{pandacap-eurosec20-dataset, author = {Stamatogiannakis, Manolis and Bos, Herbert and Groth, Paul}, title = {PANDAcap SSH Honeypot Dataset}, year = {2020}, month = {April}, publisher = {Zenodo}, version = {1.0}, url = {https://doi.org/10.5281/zenodo.3759652} doi = {10.5281/zenodo.3759652}, }
You can download the SSH Honeypot Dataset of PANDA traces described in the EuroSec paper from one of the following links:
- PANDAcap SSH Honeypot Dataset : zenodo.org , academictorrents.com
- PANDAcap SSH Honeypot VM : academictorrents.com
Note:Good documentation is hard to do. If a piece of information seems to be missing or is not clear enough, feel free to use the issue tracker or contribute a pull request .
Quickstart
- Build PANDA as usually and install it. The install path that you specify during configuration must not be different than the location you want to install PANDA inside the docker image. Make sure to include the recctrl plugin in the build.
- Inspect Makefile.vars in this repo. Documentation for the use of each variable is provided in the comments.
- If you need to override any of the variables in the file, create a new file called
Makefile.local.vars
and specify their desired values there. - Run
make
. This will build a Docker image that includes the specified PANDA build. You can check this usingmake lsimg
. - Running
make help
will you provide an overview of what actions can be performed via the Makefile. - Run
./scripts/pandacap.py --help
to get help on the PANDAcap wrapper.
Docker image
PANDAcap builds a docker image based on baseimage-docker , a minimal Ubuntu-based image with some Docker-realated enhancements. The purpose of the image is to provide a self-contained environment for recording PANDA traces.
Dockerfile overview
Instead of including fine-grained commands inside our Dockerfile, we have opted for squashing them into shell scripts which are invoked in a single bootstrapping step. This avoids creating redundant image checkpoints while building, and is also more elegant than abusing the &&
operator in the Dockerfile.
The high-level steps of creating a PANDAcap Docker image are:
- Step 1 : update Ubuntu and install PANDA runtime dependencies
- Step 2 : bootstrap the Ubuntu environment
- Step 3 : copy a precompiled version of PANDA in the container
Why a new PANDA docker image?
PANDA source code ships with a couple of Dockerfiles that can be used to create a Docker image. However these docker files are mostly intended for building PANDA in a reproducible environment. This means that a lot of build-time dependencies are dragged in the resulting image, causing unecessary bloat. We felt that for creating a dataset with PANDA, a leaner image that includes only what is required to run PANDA would be preferrable.
Makefile
:heart:
Makefile commands
While we appreciate the convenience offered by Docker, we recognize that we are probably only going to need it occasionally in our research field. For this, in addition to the functionality wrapped in the pandacap.py
script, we have packed several useful Docker-related commands in the main PANDAcap Makefile. Some of the available commands are presented below. Running make help
provides an overview of all the available commands.
- Image creation and cleanup
-
build
: Builds the docker image. It scans the specifie -
clean-docker
: Prunes unused containers and images to recover disk space. -
clean-files
: Removes intermediate files, forcing them to be created again the next file you select thebuild
target.
-
- Image/container information
lsimg lscont lsaddr
- Shell utilities
-
zsh-%
: Starts a login zsh on the container specified by%
usingdocker exec
. The specification may be either the container id or the container name. -
ssh-%
: Connects as root to the container specified by%
using ssh. The specification should be a container name. -
clean-ssh
: Removes the host keys of all container with an active network configuration from your sshauthorized_keys
file. This is useful when you modify the bootstrapping scripts and then rebuild the image. Note that this affects any and all containers with an active network configuration.
-
Makefile configuration variables
As we have mentioned above, Makefile.vars
and Makefile.local.vars
are the entry points for configuring PANDAcap. Variables defined there can be passed down and used by other parts of PANDAcap. This happens through the use of j2cli to parse the Makefile variables and render them into Jinja2 templates templates.
以上所述就是小编给大家介绍的《PANDAcap: A framework for streamlining the capture of PANDA execution traces》,希望对大家有所帮助,如果大家有任何疑问请给我留言,小编会及时回复大家的。在此也非常感谢大家对 码农网 的支持!
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