Cloud Metadata Endpoint Bypass in Flowise SSRF Guard

Flowise through 3.1.4 contains a server-side request forgery vulnerability in the SSRF guard implemented in httpSecurity.ts, where the DEFAULT_DENY_LIST omits the Oracle Cloud Infrastructure metadata endpoint 192.0.0.192 and the Alibaba Cloud metadata endpoint 100.100.100.200, allowing authenticated attackers to force the server to issue arbitrary GET requests to cloud instance metadata services. Attackers can send requests to the fetch-links API endpoint with a crafted URL parameter, bypassing deny-list validation including redirect-based bypasses, to reach instance metadata services and expose instance identity data and role credentials on Oracle Cloud Infrastructure or Alibaba Cloud deployments, with unauthenticated access possible when URL-fetching nodes exist in public chatflows.

Casky was already ahead

This CVE exploits attack patterns that Casky's 331matched skills already investigate — long before this vulnerability was disclosed. Claude's reasoning model maps these techniques to MITRE ATT&CK, so practitioners who ran these skills have already seen the threat behaviour in their findings.

Analysis

Flowise versions through 3.1.4 contain a server-side request forgery (SSRF) vulnerability in their httpSecurity.ts implementation where the DEFAULT_DENY_LIST fails to include critical cloud metadata endpoints—specifically Oracle Cloud Infrastructure's 192.0.0.192 and Alibaba Cloud's 100.100.100.200. This allows authenticated attackers to bypass SSRF protections and force the server to issue arbitrary GET requests to cloud instance metadata services. The vulnerability is particularly dangerous because metadata endpoints typically expose sensitive credentials, instance identity tokens, and configuration data that attackers can leverage for lateral movement and privilege escalation. Any organization running Flowise as a deployment automation or integration platform in cloud environments is at risk of credential compromise and unauthorized cloud resource access.

Casky's 331 matching security skills leverage Claude's extended reasoning to detect the attack patterns mapped to MITRE ATT&CK techniques TA0001 (Initial Access) and TA0006 (Credential Access). Practitioners using Casky would see detections focused on anomalous fetch-links API calls with suspicious URL parameters targeting known cloud metadata IP ranges, combined with behavioral analysis of subsequent API calls attempting to access cloud credentials or assume higher-privileged identities. The platform's skills would correlate suspicious HTTP requests to 192.0.0.* and 100.100.100.* ranges originating from Flowise instances with downstream credential-use patterns, enabling security teams to identify exploitation attempts before credentials reach attacker infrastructure.

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Casky Risk Score

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EPSS Probability

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Shodan Exposure

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GreyNoise Signal

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Composite risk scoring from EPSS, CISA KEV, Shodan, and GreyNoise — 21 security APIs correlated into a single Casky Risk Score. Coming in Casky Pro. Join early access →

331 Casky skills cover this attack pattern

These skills use Claude AI's reasoning model to surface findings in the same attack categories as CVE-2026-67620.

Abuse of Public-Facing API: Mobile API Abuse

mobile security · low

Run

abusing-dpapi-for-credential-access

red teaming · high

Run

abusing-shadow-credentials-for-privesc

red teaming · high

Run

MITRE ATT&CK Techniques

TA0001 TA0006

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