CVE-2026-105147 SciPhi-AI CVE debrief

Who should care

Defenders responsible for SciPhi-AI R2R deployments, especially those using versions up to 3.6.6, should assess their exposure and prioritize verification and potential remediation.

Why it matters

CVE-2026-105147 is a medium-severity vulnerability in SciPhi-AI R2R that allows for hardcoded credentials, enabling remote attacks. Defenders should prioritize verification, assessment, and potential remediation to prevent credential misuse.

• Verification of SciPhi-AI R2R version and potential exposure to hardcoded credentials
• Assessment of remote attack feasibility and potential impact
• Monitoring for exploit usage and potential credential misuse
• Prioritization of authentication and secret management compensating controls

Technical summary

The SciPhi-AI R2R up to 3.6.6 is vulnerable to hardcoded credentials due to improper handling of DEFAULT_BCRYPT_SECRET_KEY/DEFAULT_NACL_SECRET_KEY in the JWT Secret Handler component. This allows for remote attacks. Defenders should verify the presence of this vulnerability in their SciPhi-AI R2R deployments, especially if they are using versions up to 3.6.6, and assess the potential impact of hardcoded credentials. The CVE record and NVD entry provide details about the vulnerability, but the vendor did not respond to the disclosure.

Defensive priority

Defenders should prioritize verifying the presence of this vulnerability in their SciPhi-AI R2R deployments, especially if they are using versions up to 3.6.6, and assess the potential impact of hardcoded credentials.

Recommended defensive actions

• Verify SciPhi-AI R2R deployments for version 3.6.6 or earlier
• Assess potential impact of hardcoded credentials
• Monitor for exploit usage
• Consider compensating controls for authentication and secret management
• Review vendor guidance for patching or mitigation
• Conduct asset inventory to identify exposed systems
• Track exceptions and retest remediated assets

Evidence notes

The CVE record and NVD entry provide details about the vulnerability, but the vendor did not respond to the disclosure. The exploit has been publicly disclosed, but there is no information on its usage.

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.