#rate-limiting

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fromInfoQ
1 day ago

GitHub Reworks Layered Defenses After Legacy Protections Block Legitimate Traffic

GitHub engineers recently traced user reports of unexpected "Too Many Requests" errors to abuse-mitigation rules that had accidentally remained active long after the incidents that prompted them. According to GitHub, the affected users were not generating high-volume traffic; they were "making a handful of normal requests" that still tripped protections. The investigation found that older incident rules were based on traffic patterns that were strongly associated with abuse at the time, but later began matching some legitimate, logged-out requests.
Information security
Artificial intelligence
fromLogRocket Blog
1 week ago

Why your AI agent needs a task queue (and how to build one) - LogRocket Blog

Task queues convert frequent, low-rate LLM failures into recoverable work while providing ordering, observability, and adaptive throttling to prevent duplication and race conditions.
#whatsapp
fromWIRED
2 months ago
Privacy technologies

A Simple WhatsApp Security Flaw Exposed 3.5 Billion Phone Numbers

fromWIRED
2 months ago
Privacy technologies

A Simple WhatsApp Security Flaw Exposed 3.5 Billion Phone Numbers

fromRubyflow
3 months ago

Beskar - Rails Security Engine for the Paranoid (vibe-coded during SOC 2 audits)

Beskar is a Rails engine that fills that gap with layered protection: WAF that detects vulnerability scanning patterns (WordPress, config files, path traversal) Impossible travel detection using geolocation and Haversine calculations Smart rate limiting that identifies attack patterns (brute force, credential stuffing, distributed attacks) Risk-based account locking with automatic responses Persistent IP banning with escalating durations Installation is deliberately simple - drop it in your Gemfile, run the installer, add one line to your User model. Runs in monitor-only mode by default so you can tune thresholds before blocking real traffic.
#ai
fromMedium
8 months ago
Artificial intelligence

Quick note on adding rate limit for AI agents using LiteLLM server

fromMedium
8 months ago
Artificial intelligence

Quick note on adding rate limit for AI agents using LiteLLM server

fromMedium
8 months ago
Artificial intelligence

Quick note on adding rate limit for AI agents using LiteLLM server

fromMedium
8 months ago
Artificial intelligence

Quick note on adding rate limit for AI agents using LiteLLM server

Artificial intelligence
fromMedium
8 months ago

Quick note on adding rate limit for AI agents using LiteLLM server

Implementing a LiteLLM proxy server helps manage request rates to prevent exceeding rate limits.
Using Docker for LiteLLM proxy setup can enhance AI agent performance.
Artificial intelligence
fromMedium
8 months ago

Quick note on adding rate limit for AI agents using LiteLLM server

Implementing a rate limiting strategy for AI agents can prevent the 409 error response from service providers like AWS Bedrock.
fromMedium
8 months ago
Artificial intelligence

Quick note on adding rate limit for AI agents using LiteLLM server

fromMedium
8 months ago
Artificial intelligence

Quick note on adding rate limit for AI agents using LiteLLM server

fromMedium
8 months ago
Artificial intelligence

Quick note on adding rate limit for AI agents using LiteLLM server

fromMedium
8 months ago
Artificial intelligence

Quick note on adding rate limit for AI agents using LiteLLM server

fromMedium
8 months ago
Artificial intelligence

Quick note on adding rate limit for AI agents using LiteLLM server

fromMedium
8 months ago
Artificial intelligence

Quick note on adding rate limit for AI agents using LiteLLM server

Artificial intelligence
fromMedium
8 months ago

Quick note on adding rate limit for AI agents using LiteLLM server

Implement a LiteLLM proxy server to manage request rate limits and prevent exceeding service limitations during continuous AI agent conversations.
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