Contextual Threat Intelligence: Moving Beyond Static Blacklists

Jean-Vincent QUILICHINIJean-Vincent QUILICHINI
Cover Image for Contextual Threat Intelligence: Moving Beyond Static Blacklists

For years, the standard defense against malicious traffic was the blacklist. If an IP was bad, it went on a list. Firewalls downloaded the list and blocked the IP. Simple.

But today's threat landscape is too dynamic for static lists. IPs rotate, legitimate sites get compromised, and attackers use residential proxies to hide in plain sight. To stay ahead, analysts need Contextual Threat Intelligence.

The Problem with Binary Decisions

A binary "Good/Bad" decision fails because it lacks nuance.

  • Shared Hosting: An IP might host 100 legitimate websites and 1 phishing site. Blocking the IP blocks everyone.
  • Compromised Devices: A residential IP might be part of a botnet today but clean tomorrow after the user runs an antivirus scan.
  • Ephemeral Infrastructure: Cloud IPs change hands in minutes. A blacklist updated daily is already obsolete.

What is Context?

Context answers the "Why?" and "How?" behind an indicator.

  • Associated Domains: What domains are resolving to this IP right now? Are they high-risk?
  • ASN/ISP: Is this IP belonging to a consumer ISP (Verizon, Comcast) or a cloud provider (AWS, DigitalOcean)? A login attempt from a cloud server is suspicious; a login from a residential IP is normal.
  • Behavioral History: Has this IP been seen scanning ports? Brute-forcing SSH? Or just sending spam?
  • Passive DNS: What used to be here?

The Graph Approach

Imagine threat intelligence not as a list, but as a graph.

  • Node A: Malicious File Hash
  • Node B: C2 Domain
  • Node C: Hosting IP

By seeing the connections, you can pivot. "This file talks to this domain, which resolves to this IP." Now you can block the IP proactively, even if it hasn't attacked you yet.

Leveraging isMalicious for Context

isMalicious doesn't just give you a "Yes/No." It provides the metadata you need to make intelligent decisions.

  • Confidence Scores: How sure are we?
  • Threat Types: Is it a scanner? A bot? A phisher?
  • Geolocation: Does it match your user's expected profile?

Conclusion

Stop playing whack-a-mole with static blacklists. Embrace contextual intelligence to understand the nature of the threat, not just its address. This reduces false positives and catches sophisticated attacks that slip through simple filters.

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