Dynamic Rate Limiting for Credential Stuffing Detection
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Solution Overview
Problem
Existing methods for protecting service providers against automated attacks that use compromised credentials are inadequate, as attackers can circumvent rate limits by distributing requests across multiple IP addresses and legitimate users are often unfairly impacted, leading to a need for improved detection and mitigation strategies.
Innovation Solution
An account security system that dynamically adjusts request rate limits, blocks suspicious IP addresses, and flags potential abuses by maintaining a list of pre-identified user identifiers from security breaches, reducing the rate limit for IP addresses making multiple requests with compromised credentials, and increasing block periods exponentially.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If rate limits are applied to protect against automated attacks, then security against credential-based attacks is improved, but legitimate users sharing IP addresses are unfairly blocked and productivity deteriorates
Solution Approach 1:
The system segments the attack detection by analyzing individual request patterns rather than blocking entire IP addresses. Each request is evaluated independently based on multiple factors including user agent consistency, request timing, and credential validity, allowing legitimate users to bypass blanket IP-based rate limits while still protecting against coordinated attacks.
Solution Approach 2:
The system applies different security scrutiny levels to different requests based on their characteristics. Requests with valid credentials, consistent user agents, and normal timing patterns are processed with standard validation, while requests showing signs of automation or credential stuffing are subjected to additional verification steps or rate limiting.
2Productivity
If rate limits are increased to allow more requests, then legitimate user productivity is improved, but attackers can make more attempts and security deteriorates
Solution Approach 1:
The system dynamically adjusts rate limits based on real-time detection of attack patterns. When credential stuffing or automated attacks are detected through analysis of request patterns, the system temporarily tightens rate limits for suspicious traffic while maintaining normal throughput for legitimate users. These adjustments are automatic and adaptive to the current threat level.
Solution Approach 2:
The system changes multiple parameters simultaneously to detect and respond to attacks: request timing intervals, user agent validation strictness, credential validation depth, and rate limit thresholds. By monitoring changes in these parameters across multiple requests, the system can distinguish between legitimate high-volume traffic and malicious automated attacks.
3Reliability
If attackers distribute requests across multiple IP addresses, then they circumvent rate limits and security deteriorates, but implementing IP-based blocking unfairly impacts legitimate users and productivity worsens
Solution Approach 1:
The system segments attack detection to the individual request level rather than the IP address level. Each request is independently evaluated based on its own characteristics including user agent consistency, request timing patterns, and credential validity, allowing the system to identify and block malicious requests even when distributed across multiple IPs while preserving access for legitimate users.
Solution Approach 2:
The system merges multiple security signals from different requests into a coordinated response. By analyzing patterns across user agents, request timings, credential sets, and response patterns simultaneously, the system can detect distributed attacks that单个 IP-based rules would miss, while avoiding false positives against legitimate users with diverse but valid request patterns.
Data Source
AI summary
Methods and systems are presented for detecting and dynamically rate limiting unauthorized attempts to obtain user account information from an online service provider. An online system is configured with a request rate limit and a list of user identifiers associated with accounts at risk of being compromised. The system receives requests, each associated with a user identifier, from one or more devices. The system determines what amount of user identifiers associated with the requests match user identifiers on the list over a period of time. If the amount meets or exceeds a threshold, the system reduces the request rate limit for devices that made a request associated with user identifiers matching those on the list.