Skip to content

Latest commit

 

History

History
24 lines (21 loc) · 3.61 KB

attack-surface.md

File metadata and controls

24 lines (21 loc) · 3.61 KB

Attack Surface Analysis for serbanghita/mobile-detect

Attack Surface: Regular Expression Denial of Service (ReDoS)

  • Description: Maliciously crafted User-Agent strings can exploit inefficient regular expressions used within the mobile-detect library for parsing and device detection. This can lead to excessive CPU consumption, causing significant performance degradation or complete denial of service.
    • Mobile-Detect Contribution: mobile-detect's core functionality relies on regular expressions to analyze User-Agent strings. Vulnerable regular expression patterns within the library's code are the direct source of this ReDoS attack surface. If the library uses poorly designed regex patterns, it becomes susceptible to exploitation.
    • Example: An attacker sends a sustained flood of HTTP requests to the application, each containing a carefully crafted User-Agent string. These strings are specifically designed to trigger worst-case scenario matching in the regular expressions used by mobile-detect. This causes the server's CPU to spike dramatically as it gets bogged down in computationally expensive regex operations, eventually leading to application unresponsiveness or server crash.
    • Impact:
      • Severe application slowdown or complete unresponsiveness.
      • Denial of service (DoS) for legitimate users, rendering the application unavailable.
      • Potential server resource exhaustion and infrastructure instability.
      • Financial losses due to service disruption and potential reputational damage.
    • Risk Severity: High to Critical (depending on the exploitability of the ReDoS vulnerability and the application's infrastructure resilience. In scenarios where successful ReDoS leads to complete service outage, it is Critical).
    • Mitigation Strategies:
      • Developers:
        • Crucially, library maintainers must ensure mobile-detect uses ReDoS-resistant and thoroughly optimized regular expressions. Application developers have limited direct control over this aspect within the library itself. Report potential ReDoS vulnerabilities to the library maintainers.
        • Implement robust request timeouts at the application level. This limits the processing time for individual requests, preventing a single malicious request from monopolizing server resources for an extended period during ReDoS exploitation.
        • Employ rate limiting to restrict the number of requests from a single IP address or user within a defined timeframe. This can help mitigate the impact of a flood of malicious requests aimed at triggering ReDoS.
        • Implement Web Application Firewall (WAF) rules to detect and block suspicious User-Agent patterns that are known to trigger ReDoS vulnerabilities (if such patterns are identifiable).
        • Continuously monitor server CPU usage, memory consumption, and application response times. Unusual spikes or degradation can be indicators of a ReDoS attack attempt. Implement alerting mechanisms to notify administrators of potential issues.
      • Users:
        • Users cannot directly mitigate ReDoS vulnerabilities in the library or application. Mitigation primarily relies on secure development practices and infrastructure protection.
        • If experiencing persistent application slowness or unresponsiveness, especially when it recovers after some time, it could be a sign of a DoS attack, which should be reported to application administrators.