FALCON: Transforming Cyber Threat Intelligence into Deployable IDS Rules with Self-Reflection
arXiv:2508.18684v2 Announce Type: replace-cross Abstract: Signature-based Intrusion Detection Systems (IDS) detect malicious activity by matching network or host events against predefined rules. Security analysts manually develop these rules from Cyber Threat Intelligence (CTI). As threats evolve, this manual pipeline faces two bottlenecks. Before authoring a new rule, an analyst must reconcile the incoming CTI with the existing rule base and determine whether to create, update, or retire one. This process is challenging due to the representational differences between the CTI and Rule formats.
The increasing sophistication and volume of cyber threats, coupled with the rising demand for automated security solutions, necessitate more efficient methods for deploying threat intelligence.
This development offers a practical solution to automate and enhance the effectiveness of threat intelligence conversion into deployable security rules, thereby improving cyber defense capabilities.
The manual bottleneck in developing and updating signature-based IDS rules from cyber threat intelligence is significantly reduced, leading to more responsive and effective security systems.
- · Cybersecurity companies
- · Organizations with large IT infrastructures
- · AI developers
- · National security agencies
- · Cyber threat actors
- · Manual security analysts (whose roles may shift)
Security teams can more quickly adapt to new cyber threats with automated rule generation.
This automation may lead to a reduction in successful cyber attacks and a broader adoption of AI in cybersecurity operations.
The development of highly autonomous cyber defense systems could shift the balance of power in cyber warfare, prioritizing software and AI development over traditional human analysis.
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Read at arXiv cs.AI