I

I made a cloud security product that actually saves time

Hacker News

I made a cloud security product that actually saves time

I have been a Cloud Security Consultant for over 13 years and all that experience I put into building ARGOS Cloud Security. Probably the most common thing I've seen was teams spending loads of time manually investigating alerts from security products. Detecting security issues is not what it’s ever been about, but about the investigation of these detected issues. If you don’t have time to investigate everything, then what’s the point? Organizations spend time and money on security consultants to help them investigate their environments, but these are often only point-in-time engagements, where, once done, nothing "reusable" is left behind. The cloud environment might be in slightly better shape, but maybe only for a short period, before the next contractor must come in to start the process all over again. I, and many others I've worked with, always believed that the most difficult part of cloud security is distinguishing security issues from "just best practice violations". Using an "everything must be compliant" approach never really works and usually means things just don't get done. If everything is red, what do you do? So, people spend immense amounts of time trying to figure out what cloud misconfigurations are actual security issues, what else is put at risk because of something that is misconfigured, and how it can be fixed. All that information is important to eventually prioritize and fix issues. ARGOS investigates the things it finds, that's what it does. It's not about "finding more", it's about understanding what misconfiguration is exposing a cloud system to the internet and what else in your cloud environment is that misconfiguration indirectly putting at risk. One awesome side-effect of this is that we even draw something like an architecture diagram of the environment "around the misconfigured resource". This specifically is something I know most past customers of mine lacked. Architecture diagrams were hard to come by, and never up to date. It's easy to try out if you have access to a cloud environment like Azure or AWS, GCP is in a very early version right now. 20 minutes or less even is all it takes to get everything going, including a one-click Slack integration. First results should be in your dashboard minutes later and are continuously and automatically updated. Really looking forward to people's feedback. Thanks all!

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Indie HackersFits the IH revenue-focused audience · Strong signals: including, organizations · Missing: supports, reddit linkedin, podcasting
92%92% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: slack, using · Missing: mac, agents, macos
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released
62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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