CVE-2026-10564: CWE-918 Server-Side Request Forgery (SSRF) in IBM Langflow OSS
IBM Langflow OSS 1.0.0 through 1.9.6 contains a Server-Side Request Forgery (SSRF). The legacy RSSReaderComponent in rss.py and SearXNG component in searxng.py make unvalidated HTTP requests to user-controlled URLs, bypassing SSRF protections introduced in version 1.9.3. An authenticated attacker can exploit this to access internal resources including cloud metadata services (AWS/Azure/GCP IMDS), potentially exfiltrating IAM credentials and enumerating internal networks. The vulnerability can also be triggered through prompt injection in agentic workflows due to tool_mode=True exposure.
AI Analysis
Technical Summary
CVE-2026-10564 is a Server-Side Request Forgery (SSRF) vulnerability affecting IBM Langflow OSS versions 1.0.0 through 1.9.6. The issue arises from the legacy RSSReaderComponent in rss.py and the SearXNG component in searxng.py, which perform HTTP requests to URLs controlled by users without proper validation. This bypasses SSRF protections introduced in version 1.9.3. An authenticated attacker can exploit this to access internal resources, including cloud metadata services from AWS, Azure, and GCP, potentially exfiltrating IAM credentials and enumerating internal networks. Additionally, the vulnerability can be triggered through prompt injection in agentic workflows due to exposure of tool_mode=True. IBM Langflow OSS is a cloud-hosted service, and IBM manages remediation on the server side.
Potential Impact
The vulnerability allows an authenticated attacker to perform SSRF attacks that can access internal resources, including cloud metadata services for AWS, Azure, and GCP. This can lead to exfiltration of sensitive IAM credentials and internal network enumeration. The impact includes confidentiality loss (high), limited integrity impact (low), and no availability impact. The vulnerability can also be triggered through prompt injection in specific workflows, increasing the attack surface.
Mitigation Recommendations
IBM Langflow OSS is a cloud-hosted service, and IBM manages remediation server-side. Users should verify with IBM's official advisory for confirmation of patch deployment and any required actions. Since patchAvailable is true and the service is cloud-based, IBM likely has applied the fix. No additional user action may be required unless stated by IBM.
CVE-2026-10564: CWE-918 Server-Side Request Forgery (SSRF) in IBM Langflow OSS
Description
IBM Langflow OSS 1.0.0 through 1.9.6 contains a Server-Side Request Forgery (SSRF). The legacy RSSReaderComponent in rss.py and SearXNG component in searxng.py make unvalidated HTTP requests to user-controlled URLs, bypassing SSRF protections introduced in version 1.9.3. An authenticated attacker can exploit this to access internal resources including cloud metadata services (AWS/Azure/GCP IMDS), potentially exfiltrating IAM credentials and enumerating internal networks. The vulnerability can also be triggered through prompt injection in agentic workflows due to tool_mode=True exposure.
CVSS v3.1
Score 8.2high
Affected software
cpe:2.3:a:ibm:langflow_oss:1.0.0:*:*:*:*:*:*:*cpe:2.3:a:ibm:langflow_oss:1.9.6:*:*:*:*:*:*:*Run on your own infrastructure? Check whether these packages are installed with threat-finder — our free open-source scanner.
Weaknesses
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2026-10564 is a Server-Side Request Forgery (SSRF) vulnerability affecting IBM Langflow OSS versions 1.0.0 through 1.9.6. The issue arises from the legacy RSSReaderComponent in rss.py and the SearXNG component in searxng.py, which perform HTTP requests to URLs controlled by users without proper validation. This bypasses SSRF protections introduced in version 1.9.3. An authenticated attacker can exploit this to access internal resources, including cloud metadata services from AWS, Azure, and GCP, potentially exfiltrating IAM credentials and enumerating internal networks. Additionally, the vulnerability can be triggered through prompt injection in agentic workflows due to exposure of tool_mode=True. IBM Langflow OSS is a cloud-hosted service, and IBM manages remediation on the server side.
Potential Impact
The vulnerability allows an authenticated attacker to perform SSRF attacks that can access internal resources, including cloud metadata services for AWS, Azure, and GCP. This can lead to exfiltration of sensitive IAM credentials and internal network enumeration. The impact includes confidentiality loss (high), limited integrity impact (low), and no availability impact. The vulnerability can also be triggered through prompt injection in specific workflows, increasing the attack surface.
Mitigation Recommendations
IBM Langflow OSS is a cloud-hosted service, and IBM manages remediation server-side. Users should verify with IBM's official advisory for confirmation of patch deployment and any required actions. Since patchAvailable is true and the service is cloud-based, IBM likely has applied the fix. No additional user action may be required unless stated by IBM.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- ibm
- Date Reserved
- 2026-06-01T16:26:04.641Z
- Cvss Version
- 3.1
- State
- PUBLISHED
- Remediation Level
- null
- Is Cloud Service
- true
Threat ID: 6a44256027e9c797195589b7
Added to database: 06/30/2026, 20:21:53 UTC
Last enriched: 07/08/2026, 12:35:12 UTC
Last updated: 08/14/2026, 08:13:20 UTC
Views: 92
Community Reviews
0 reviewsCrowdsource mitigation strategies, share intel context, and vote on the most helpful responses. Sign in to add your voice and help keep defenders ahead.
Want to contribute mitigation steps or threat intel context? Sign in or create an account to join the community discussion.
Actions
Updates to AI analysis require Pro Console access. Upgrade inside Console → Billing.
External Links
Need more coverage?
Upgrade to Pro Console for AI refresh and higher limits.
For incident response and remediation, OffSeq services can help resolve threats faster.
Latest Threats
Check if your credentials are on the dark web
Instant breach scanning across billions of leaked records. Free tier available.