CVE-2016-2515 in Hawk
Summary
by MITRE
Hawk before 3.1.3 and 4.x before 4.1.1 allow remote attackers to cause a denial of service (CPU consumption or partial outage) via a long (1) header or (2) URI that is matched against an improper regular expression.
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Analysis
by VulDB Data Team • 07/24/2022
The vulnerability identified as CVE-2016-2515 affects the Hawk authentication library version 3.1.2 and earlier, as well as version 4.1.0 and earlier, representing a critical security flaw that enables remote attackers to execute denial of service attacks through carefully crafted input patterns. This vulnerability specifically targets the regular expression matching mechanisms used within the library's header and URI validation processes, creating a scenario where maliciously constructed inputs can trigger excessive computational overhead.
The technical flaw manifests when the Hawk library processes incoming HTTP headers or URIs containing specially crafted long strings that match against improperly constructed regular expressions. These regular expressions are vulnerable to catastrophic backtracking, a well-documented pattern matching issue where the regular expression engine consumes exponential time when processing certain inputs. The vulnerability stems from the library's failure to implement proper input validation and sanitization before applying regular expression matching operations, allowing attackers to craft inputs that cause the regular expression engine to perform an excessive number of operations.
This vulnerability operates under the CWE-1321 category of improper input validation, specifically targeting the regular expression denial of service weakness. The attack vector involves sending HTTP requests containing long header values or URI components that, when processed by the vulnerable Hawk library, trigger the regular expression engine to consume excessive CPU resources. The impact ranges from partial service degradation to complete system unavailability, depending on the computational resources available and the specific implementation details of the regular expressions used.
From an operational perspective, this vulnerability presents significant risk to web applications and services that rely on Hawk authentication for securing their APIs and web endpoints. Attackers can exploit this weakness by sending requests with carefully constructed header values or URI parameters that cause the service to spend excessive time processing the regular expressions. The vulnerability is particularly dangerous because it can be exploited without requiring authentication or special privileges, making it an attractive target for automated attack tools and DDoS campaigns.
The attack pattern aligns with techniques described in the MITRE ATT&CK framework under the 'Resource Exhaustion' tactic, specifically targeting system resources through inefficient regular expression processing. The vulnerability demonstrates a classic example of how seemingly benign input validation can become a security risk when not properly implemented with consideration for computational complexity. Organizations using vulnerable versions of the Hawk library should immediately implement patches or upgrades to version 3.1.3 or 4.1.1 respectively, as these releases contain fixes that address the improper regular expression usage patterns.
Mitigation strategies include not only applying the official patches but also implementing additional protective measures such as input length restrictions, rate limiting on authentication requests, and monitoring for unusual CPU consumption patterns that might indicate exploitation attempts. The fix implemented in the patched versions involves proper regular expression construction that prevents catastrophic backtracking scenarios and ensures that input validation operations complete within reasonable timeframes. Security teams should also consider implementing automated monitoring solutions that can detect and alert on potential exploitation attempts targeting this vulnerability, as the attack behavior can be identified through anomalous system resource utilization patterns.