CVE-2026-67319 axios CVE debrief

Who should care

Developers and administrators using axios in applications, especially those with exposed network interfaces or handling sensitive data, should be aware of this vulnerability and take steps to mitigate it. This includes reviewing axios configurations and option objects for potential pollution and implementing compensating controls to detect and prevent silent injection attacks.

Technical summary

axios versions before 0.33.0 and 1.x before 1.18.0 are vulnerable to prototype pollution via nested option objects. This can lead to silent injection of an Authorization: Basic header and alteration of query-string serialization. The vulnerability occurs when an application passes placeholder nested objects such as auth: {} or paramsSerializer: {}, inherited username/password values can cause silent injection of an Authorization: Basic header, and inherited encode/serialize values can alter query-string serialization.

Defensive priority

Medium priority given the CVSS score of 6.3 and the potential for silent injection attacks.

Recommended defensive actions

• Inventory and check axios versions for compliance with recommended versions.
• Implement compensating controls to detect and prevent silent injection attacks.
• Monitor for and track changes to axios configurations and option objects.
• Exception tracking for unusual authentication or query-string serialization behavior.
• Retest axios configurations for vulnerability after applying recommended patches.
• Review compensating controls for exposed systems while remediation is scheduled and verified.
• Track exceptions, retest remediated assets, and close the item only after evidence is documented.

Evidence notes

axios versions before 0.33.0 and 1.x before 1.18.0 are affected by prototype pollution via nested option objects. Evidence is limited; primary official records indicate axios versions before 0.33.0 and 1.x before 1.18.0 are affected. To verify, defenders should check axios configurations and option objects for potential pollution.

Sources and references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.