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AI-Powered Threat Detection

5 min read
AppsecSecurity Arch

Appsec

AI finds known patterns. Novel attacks and business-context risks need you.

Security Arch

AI augments scanning. You own threat model and risk appetite.

AI-Powered Threat Detection

TL;DR

  • AI can scan code, configs, and infra for known vulnerabilities. Fast, broad coverage. Good at CVE matching and pattern detection.
  • AI misses business-logic flaws, novel attacks, and context-dependent risks. You catch those.
  • Use AI to scale scanning. Don't let it replace threat modeling or manual review for critical paths.

SAST, DAST, SCA—all getting AI upgrades. More findings, faster. Also more noise. Your job is to tune the signal.

What AI Detects Well

  • Known CVEs. Dependency vulns, version matching. AI has the databases. Fast.
  • Common patterns. SQLi, XSS, hardcoded secrets. Training data is full of these. Good recall.
  • Config drift. "This bucket should be private." "This port shouldn't be open." AI compares to policy. Useful.
  • Anomaly in logs. Unusual access patterns, failed logins, lateral movement. AI spots deviations. Triage still needs humans.

What AI Misses

  • Business logic flaws. "User A can see User B's data because of this entitlement bug." AI doesn't understand your app's logic. You do.
  • Novel attack vectors. Zero-days, supply chain, AI-specific exploits. AI trains on known patterns. The new stuff slips through.
  • Context. "This CVE is in a dev-only container that never touches prod." AI flags it. You decide if it matters.
  • Chained attacks. Step 1: low. Step 2: low. Step 1 + 2: critical. AI often treats findings in isolation.
  • Compliance nuance. PCI, HIPAA, SOC2. AI can check controls; it can't interpret "spirit of the law" for your org.

How to Use AI Detection

Tier 1: AI runs first. Scalable, fast. Triage with humans. Use for broad coverage.

Tier 2: Manual review for critical paths—auth, payments, PII. AI assists; humans decide.

Tier 3: Threat modeling and red teams. AI can suggest attack trees; you validate and execute.

AI Disruption Risk for Security Engineers

Mostly Safe

SafeCritical

AI-powered threat detection scales scanning and triage. Business logic flaws, novel attacks, and risk judgment remain firmly human territory. Mostly safe for those who own the threat model.

Run SAST manually, triage every finding, manual review for critical paths. Days per scan cycle.

Click "AI-Augmented Security" to see the difference →

Quick Check

AI flagged a CVE in a dev-only container that never touches production. What should you do?

Do This Next

  1. Run AI-powered scan on a codebase you know well. Compare: what did it find that you'd already consider handled? What did it miss that you know is risky? Tune from there.
  2. Document your risk acceptance criteria for AI findings. "We accept low CVEs in dev deps with no network access." Reduces noise; AI can filter if you codify the rules.