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# Defending against AI-fueled social engineering

**[elastic](https://daily.dev/sources/elastic)** · 5 min read · 0 upvotes · 0 comments

## Summary

AI is lowering the cost and skill barriers for social engineering attacks, enabling spear phishing at scale, smishing, and convincing deepfakes used to impersonate trusted voices during payment verification calls. Legacy signature-based detection cannot keep pace with machine-speed lure generation. The piece argues SOC teams need behavioral analytics over unified telemetry, agentic AI-assisted investigation that correlates alerts into attack narratives, and transparent, auditable AI reasoning to counter identity-based attacks, pointing to a fuller guide for detection priorities.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.elastic.co/blog/defending-against-ai-fueled-social-engineering>

## Questions this post answers

### What percentage of phishing attacks are AI-driven according to recent research?

As much as 86% of phishing attacks analyzed were found to be AI-driven, according to KnowBe4 research cited in reporting from April 2026. This reflects how AI tools let attackers automate reconnaissance, personalization, and message generation at scale rather than crafting each phishing attempt manually.

_Security teams tracking how attackers weaponize AI can follow emerging detection guidance on daily.dev._

### Why are people more likely to fall for smishing (SMS phishing) than email phishing?

People are up to 40% more likely to fall for social engineering carried out by text or phone than by email, per Verizon's 2026 Data Breach Investigations Report. Text messages lack the authentication infrastructure built into email, leaving fewer built-in signals that would warn a recipient something is suspicious.

_Anyone hardening defenses against smishing can keep up with attacker trends via daily.dev._

### Why can't signature-based email filters keep up with AI-generated phishing campaigns?

Signature-based filters and rule-based fraud engines assume attacker patterns change slowly enough for defenders to catch up, but AI lets attackers regenerate lures, domains, and payloads at machine speed, breaking that assumption. Effective defense instead requires behavioral analytics that reason over unified identity, endpoint, email, and cloud telemetry rather than matching known artifacts.

_Teams rethinking detection architecture beyond signatures can track approaches like this on daily.dev._

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---

Tags: [#security](https://daily.dev/tags/security), [#phishing](https://daily.dev/tags/phishing), [#elk](https://daily.dev/tags/elk)

[View this post on daily.dev](https://daily.dev/posts/defending-against-ai-fueled-social-engineering-1gm1hdqda)

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