IBM Langflow OSS up to 1.11.1 server-side request forgery

CVSS Meta Temp Score
CVSS is a standardized scoring system to determine possibilities of attacks. The Temp Score considers temporal factors like disclosure, exploit and countermeasures. The unique Meta Score calculates the average score of different sources to provide a normalized scoring system.
Current Exploit Price (≈)
Our analysts are monitoring exploit markets and are in contact with vulnerability brokers. The range indicates the observed or calculated exploit price to be seen on exploit markets. A good indicator to understand the monetary effort required for and the popularity of an attack.
CTI Interest Score
Our Cyber Threat Intelligence team is monitoring different web sites, mailing lists, exploit markets and social media networks. The CTI Interest Score identifies the interest of attackers and the security community for this specific vulnerability in real-time. A high score indicates an elevated risk to be targeted for this vulnerability.
4.3$5k-$25k0.78

Summaryinfo

A vulnerability has been found in IBM Langflow OSS up to 1.11.1 and classified as problematic. The impacted element is an unknown function. This manipulation causes server-side request forgery. This vulnerability is handled as CVE-2026-18545. The attack can be initiated remotely. There is not any exploit available.

Detailsinfo

A vulnerability has been found in IBM Langflow OSS up to 1.11.1 and classified as problematic. Affected by this vulnerability is an unknown part. The manipulation with an unknown input leads to a server-side request forgery vulnerability. The CWE definition for the vulnerability is CWE-918. The web server receives a URL or similar request from an upstream component and retrieves the contents of this URL, but it does not sufficiently ensure that the request is being sent to the expected destination. As an impact it is known to affect confidentiality. The summary by CVE is:

IBM Langflow OSS 1.0.0 through 1.11.1 is vulnerable to server-side request forgery (SSRF). This may allow an authenticated attacker to send unauthorized requests from the system, potentially leading to network enumeration or facilitating other attacks.

It is possible to read the advisory at ibm.com. This vulnerability is known as CVE-2026-18545 since 07/31/2026. The exploitation appears to be easy. The attack can be launched remotely. The technical details are unknown and an exploit is not publicly available. The pricing for an exploit might be around USD $5k-$25k at the moment (estimation calculated on 08/29/2026).

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

Productinfo

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Version

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Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 4.3
VulDB Meta Temp Score: 4.3

VulDB Base Score: 4.3
VulDB Temp Score: 4.3
VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA Base Score: 4.3
CNA Vector (ibm): 🔒

CVSSv2info

AVACAuCIA
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VectorComplexityAuthenticationConfidentialityIntegrityAvailability
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍

Exploitinginfo

Class: Server-side request forgery
CWE: CWE-918
CAPEC: 🔒
ATT&CK: 🔒

Physical: No
Local: No
Remote: Yes

Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒

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Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: no mitigation known
Status: 🔍

0-Day Time: 🔒

Timelineinfo

07/31/2026 CVE reserved
08/28/2026 +28 days VulDB entry created
08/29/2026 +0 days Advisory disclosed
08/29/2026 +0 days VulDB entry last update

Sourcesinfo

Vendor: ibm.com

Advisory: ibm.com
Status: Confirmed

CVE: CVE-2026-18545 (🔒)
GCVE (CVE): GCVE-0-2026-18545
GCVE (VulDB): GCVE-100-396931

Entryinfo

Created: 08/29/2026 00:19
Changes: 08/29/2026 00:19 (61)
Complete: 🔍
Cache ID: 216::103

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

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