Managed Rulesets
  • 05 Oct 2024
  • 1 Minute to read
  • Contributors
  • Dark
    Light

Managed Rulesets

  • Dark
    Light

Article summary

In addition to LimaCharlie's powerful custom detection & response capabilities, we also offer native integration with several managed rulesets. LimaCharlie currently offers:

A Word on Managed Rulesets

While managed rulesets can help your organizations achieve detection and response capabilities quickly, not all detections are suitable for every environment.

Ensure that you are fine-tuning managed rulesets within your environment via enabling/disabling rules or via False Positive controls.

Managed rulesets offer several advantages, such as:

  • Providing out-of-the-box coverage for common threats, reducing the time and effort to develop in-house rules.

  • Curated rulesets are maintained and updated by their respective parties, often covering the latest threats.

  • A foundation for building complex detection logic utilizing managed rulesets as inspiration.

Every environment is unique, and we recommend choosing rulesets that benefit your need(s) and/or use case(s).

What's the difference between Sigma and Soteria rules?

Sigma is an open source project that aims at creating a generic query language for security and D&R rules. It looks up known anomalies and Common Vulnerabilities and Exposures (CVEs).

As Sigma is an open source project,

  • applying the Sigma ruleset is free

  • there will be a higher rate of false positives

Soteria is a US-based MSSP that has been using LimaCharlie for a long time. They developed a corpus of hundreds of behavioral signatures for Windows / Mac / Linux (signature not in terms of a hash, but in terms of a rule that describes a behavior). With one click, you can apply their rules in a managed way. When Soteria updates the rules for their customers, you will get those updates in real time as well.

As Soteria is a managed ruleset,

  • applying the Soteria ruleset costs $0.5 per endpoint per month

  • the rate of false positives is much lower


Was this article helpful?


What's Next