Bot & Agent Control
Core concepts
Bot management separates good automation (search engine crawlers, monitoring, partner integrations) from bad automation (scrapers, credential stuffing, carding, scalpers). Detection blends signatures (declared user-agent and verified crawler identity), behavioral analysis (request cadence, navigation patterns, mouse/keyboard telemetry where collected), and client interrogation (JavaScript or SDK challenges that legitimate browsers can solve).
Know the action ladder: allow, monitor, challenge (proof-of-work or JS challenge), and deny. Challenges are the key concept - they let you avoid hard-blocking ambiguous traffic by forcing the client to prove it is a real browser. Verified bots are matched against published source ranges and reverse DNS, so a spoofed Googlebot user-agent fails verification. Agent/bot categories (e.g., scrapers vs. API clients vs. AI agents) let you treat different automation differently.
Traps to watch
- Treating a user-agent string as proof of identity - it is trivially spoofed; verification is what matters.
- Assuming a challenge blocks all bots - sophisticated bots may solve or bypass it; pair with behavioral and rate signals.
- Forgetting that aggressive bot rules can hit legitimate APIs or monitoring agents; scope by path and category.
- Confusing monitor (log only) with challenge (client must respond).
Rule of thumb
Match the action to confidence: high confidence bad → deny; ambiguous → challenge; known good → allow. Verify claimed crawlers before allow-listing them.
Worked example: Traffic claims to be a major search crawler but originates from an unlisted IP with no reverse-DNS match. Verification fails, so it is not treated as a verified bot and falls to challenge or deny per policy.