CVE-2026-50274 in dd-trace-go
Summary
by MITRE • 07/17/2026
Datadog dd-trace-go is a Go client library for Datadog application performance monitoring, profiling, and security monitoring. Prior to 2.8.1, Datadog tracing libraries that implement W3C baggage propagation parse incoming baggage HTTP headers without enforcing DD_TRACE_BAGGAGE_MAX_ITEMS or DD_TRACE_BAGGAGE_MAX_BYTES limits on the extract path. A remote, unauthenticated attacker can send a request whose baggage header contains an arbitrarily large number of comma-separated key-value pairs or a single very large value, causing unbounded CPU and memory consumption and enabling a remote denial of service against HTTP services with baggage propagation enabled. This issue is fixed in version 2.8.1.
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Analysis
by VulDB Data Team • 07/17/2026
The vulnerability exists within Datadog's dd-trace-go library, specifically affecting versions prior to 2.8.1, where the implementation of W3C baggage propagation fails to enforce critical resource limits during header parsing operations. This flaw manifests when the tracing library processes incoming HTTP requests containing baggage headers that have not been properly constrained by the DD_TRACE_BAGGAGE_MAX_ITEMS or DD_TRACE_BAGGAGE_MAX_BYTES environment variables. The absence of these enforcement mechanisms creates a pathway for malicious actors to exploit the system through crafted HTTP requests designed to consume excessive computational resources.
The technical implementation flaw stems from the library's extract path logic which processes baggage headers without implementing bounds checking on either the number of key-value pairs or the overall size of individual values within the baggage data. When an attacker sends a request containing a large number of comma-separated key-value pairs or a single extremely large value, the tracing library attempts to parse and store all this information in memory without any resource limitations. This unbounded parsing behavior directly leads to excessive memory allocation and CPU consumption as the system processes increasingly larger data structures.
From an operational impact perspective, this vulnerability enables remote denial of service attacks against HTTP services that have baggage propagation enabled, particularly affecting systems where Datadog tracing is implemented. The attack vector is accessible to unauthenticated remote adversaries who can exploit this weakness by crafting malicious HTTP requests with oversized baggage headers. The resulting resource exhaustion can cause service degradation or complete system unavailability, making it a critical concern for applications that rely on Datadog's APM and monitoring capabilities.
The vulnerability aligns with CWE-400, which addresses unchecked resource consumption, and represents a classic example of a denial-of-service attack through resource exhaustion. This issue also maps to ATT&CK technique T1499.004, specifically targeting network denial of service through resource consumption attacks. The flaw demonstrates poor input validation and resource management practices in the library's baggage header processing implementation.
Mitigation strategies include upgrading to Datadog dd-trace-go version 2.8.1 or later where the issue has been resolved through proper enforcement of baggage limits during header parsing operations. Organizations should also consider implementing additional monitoring for unusual resource consumption patterns in their tracing-enabled services and potentially configuring stricter environment variables to limit baggage processing parameters even before the upgrade is completed. The fix ensures that all incoming baggage headers are properly validated against configured maximum item counts and byte limits, preventing the exploitation of this resource exhaustion vulnerability while maintaining the library's core functionality.
This vulnerability highlights the importance of input validation in distributed tracing systems where external inputs can be leveraged for resource exhaustion attacks. The remediation approach demonstrates how proper bounds checking and resource management can prevent such denial-of-service scenarios, particularly in monitoring libraries that process untrusted external data through HTTP headers.