Company
Careers
Services
We emulate attackers to locate the critical exposures that hackers, ransomware, cybercriminals, and nation states will leverage to compromise your organization.
Use Cases
Every organization has digital assets to protect. Which of these scenarios sounds like you?
Customers
We are fanatical about delivering security solutions and fixated on customer success.
Put the customer first and everything else will work out. Our lifetime NPS of 02 reflects this core value commitment to our customers.
Several customers have jumped on camera to share their Praetorian experience. Check out their success stories.
Our customers love getting on camera for us!
Resources
We build innovative, sustainable solutions that solve real-world problems for our customers and ourselves.
Learn about our offerings, their methodologies, and the outcomes you can expect.
Our whitepapers blend data and thought leadership across a range of security matters, to help you understand an issue, solve a problem, or make a decision.
Keep up-to-date on cybersecurity industry trends and the latest tools & techniques from the world’s foremost cybersecurity experts.
Praetorian is committed to opensourcing as much of our research as possible.
Train a machine learning classifier to identify architectures.
We see huge benefits of machine learning in the field of computer security. Do you?
Much of the work we do on a daily basis can be automated and classified by a machine, leaving us to focus on more interesting and challenging problems. One stunning example is the automated binary exploitation and patching research funded by DARPA for the Cyber Grand Challenge. Problems like these are the stepping stones that will lead us to a future of automated computer security.
The crux of the challenge is to build a classifier that can automatically identify and categorize the instruction set architecture of a random binary blob. Train a machine learning classifier to identify the architecture of a binary blob given a list of possible architectures. We currently support twelve architectures, including: avr, alphaev56, arm, m68k, mips, mipsel, powerpc, s390, sh4, sparc, x86_64, and xtensa.
Need some help? Read our Machine Learning Tutorial.
Icon/Info When your classifier has solved 500 challenges in a row, send your resume along with all hash values you collected and any code used in the challenges to: careers@praetorian.com Please remember to document your solutions and provide code where applicable.
When your classifier has solved 500 challenges in a row, send your resume along with all hash values you collected and any code used in the challenges to: careers@praetorian.com
Please remember to document your solutions and provide code where applicable.
The challenge API is documented below and all requests are sent to https://mlb.praetorian.com/. You’ll receive a ‘session’ cookie in your first request. Use this to track your progress while solving the challenge.
https://mlb.praetorian.com/
GET
/challenge
Retrieve a new challenge. Consists of a binary blob and six possible target architectures.
Response: {"binary": "__base64_encoded_blob__", "target": ["arm", "avr", ... ] }
{"binary": "__base64_encoded_blob__", "target": ["arm", "avr", ... ] }
POST
/solve
Attempt to solve a challenge by guessing the instruction set architecture of the binary blob. The server will respond with your current consecutive wins and the actual architecture of the binary. If you have solved over 500 challenges, the server will also send a hash for submission to careers@praetorian.com
Request: {"target": "arm"}
{"target": "arm"}
Response: {"correct": 17, "target": "arm", "hash": "R0VUIC9lYXN0ZXItZWdnIEhUVFAvMS4w"}
{"correct": 17, "target": "arm", "hash": "R0VUIC9lYXN0ZXItZWdnIEhUVFAvMS4w"}
To help get you started, we’ve included this example code to help you communicate with the “Machine Learning Binaries” technical challenge.
Please use Chrome, Safari, Firefox, or Edge to view this site.