iRobot, the leading global consumer robot company, designs and builds robots that empower people to do more both inside and outside of the home. This program is testing iRobot's web applications, mobile applications, cloud APIs, and cloud-connected robots for vulnerabilities.

NOTE! [Please Read Fully Before Beginning Or Engaging In Any Testing]

1. Please DO NOT use automated vulnerability scanners when testing against the in-scope targets (Zap/Burp/Acunetix/Nikto/Nessus/etc) - all of these tools have already been run, and are run on a recurring basis internally. Running any tools of this nature is largely an inefficient use of your time and resources.
2. However, you ARE encouraged to run any custom scripts or fuzzers that you have developed (e.g. niche file or directly wordlists, etc); however, please keep your requests using these tools to UNDER 50 requests per SECOND.
3. In short, we strongly encourage researchers to perform manual testing by hand - this is where you're much more likely to achieve success, and a much better use of your time and resources, as opposed to running common tools that have already been used extensively against the in-scope targets, etc.
4. Please be aware that Submissions found using pirated software will not be rewarded.
5. Good luck, and happy hunting!

Additionally, please be aware that this program does not accept out of scope submissions. Testing targets that are out of scope is strictly prohibited.

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What you can expect from us

We are committed to working with you as transparently and efficiently as
possible.

• We will acknowledge receipt of your vulnerability report with 10 working days
• We strive to support you and work with you to solve the reported issue within 180 working days.
• Support will be provided on a best-effort basis, including for discontinued products.

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Ratings/Rewards

For the initial prioritization/rating of findings, this program will use the Bugcrowd Vulnerability Rating Taxonomy. However, it is important to note that in some cases a vulnerability priority will be modified due to its likelihood or impact. In any instance where an issue is downgraded, a full, detailed explanation will be provided to the researcher - along with the opportunity to appeal, and make a case for a higher priority.