Security Vulnerabilities
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the Chatflow configuration file upload settings can be modified to allow the application/javascript MIME type. This lets an attacker upload .js files even though the frontend doesn’t normally allow JavaScript uploads. This enables attackers to persistently store malicious Node.js web shells on the server, potentially leading to Remote Code Execution (RCE). This vulnerability is fixed in 3.1.0.
CVSS Score
7.1
EPSS Score
0.001
Published
2026-04-23
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, a Server-Side Request Forgery (SSRF) protection bypass vulnerability exists in the Custom Function feature. While the application implements SSRF protection via HTTP_DENY_LIST for axios and node-fetch libraries, the built-in Node.js http, https, and net modules are allowed in the NodeVM sandbox without equivalent protection. This allows authenticated users to bypass SSRF controls and access internal network resources (e.g., cloud provider metadata services) This vulnerability is fixed in 3.1.0.
CVSS Score
7.1
EPSS Score
0.0
Published
2026-04-23
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, a Server-Side Request Forgery (SSRF) vulnerability exists in FlowiseAI's POST/GET API Chain components that allows unauthenticated attackers to force the server to make arbitrary HTTP requests to internal and external systems. By injecting malicious prompt templates, attackers can bypass the intended API documentation constraints and redirect requests to sensitive internal services, potentially leading to internal network reconnaissance and data exfiltration. This vulnerability is fixed in 3.1.0.
CVSS Score
7.1
EPSS Score
0.001
Published
2026-04-23
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the core security wrappers (secureAxiosRequest and secureFetch) intended to prevent Server-Side Request Forgery (SSRF) contain multiple logic flaws. These flaws allow attackers to bypass the allow/deny lists via DNS Rebinding (Time-of-Check Time-of-Use) or by exploiting the default configuration which fails to enforce any deny list. This vulnerability is fixed in 3.1.0.
CVSS Score
7.1
EPSS Score
0.0
Published
2026-04-23
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, Flowise contains an authentication bypass vulnerability that allows an unauthenticated attacker to obtain OAuth 2.0 access tokens associated with a public chatflow. By accessing a public chatflow configuration endpoint, an attacker can retrieve internal workflow data, including OAuth credential identifiers, which can then be used to refresh and obtain valid OAuth 2.0 access tokens without authentication. This vulnerability is fixed in 3.1.0.
CVSS Score
7.7
EPSS Score
0.001
Published
2026-04-23
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, The CSVAgent allows providing a custom Pandas CSV read code. Due to lack of sanitization, an attacker can provide a command injection payload that will get interpolated and executed by the server. This vulnerability is fixed in 3.1.0.
CVSS Score
9.4
EPSS Score
0.003
Published
2026-04-23
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, there is a remote code execution vulnerability in AirtableAgent.ts caused by lack of input verification when using Pandas. The user’s input is directly applied to the question parameter within the prompt template and it is reflected to the Python code without any sanitization. This vulnerability is fixed in 3.1.0.
CVSS Score
8.3
EPSS Score
0.003
Published
2026-04-23
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the specific flaw exists within the run method of the CSV_Agents class. The issue results from the lack of proper sandboxing when evaluating an LLM generated python script. An attacker can leverage this vulnerability to execute code in the context of the user running the server. Using prompt injection techniques, an unauthenticated attacker with the ability to send prompts to a chatflow using the CSV Agent node may convince an LLM to respond with a malicious python script that executes attacker controlled commands on the Flowise server. This vulnerability is fixed in 3.1.0.
CVSS Score
9.2
EPSS Score
0.003
Published
2026-04-23
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the specific flaw exists within the run method of the Airtable_Agents class. The issue results from the lack of proper sandboxing when evaluating an LLM generated python script. Using prompt injection techniques, an unauthenticated attacker with the ability to send prompts to a chatflow using the Airtable Agent node may convince an LLM to respond with a malicious python script that executes attacker controlled commands on the flowise server. This vulnerability is fixed in 3.1.0.
CVSS Score
9.2
EPSS Score
0.002
Published
2026-04-23
LeRobot through 0.5.1 contains an unsafe deserialization vulnerability in the async inference pipeline where pickle.loads() is used to deserialize data received over unauthenticated gRPC channels without TLS in the policy server and robot client components. An unauthenticated network-reachable attacker can achieve arbitrary code execution on the server or client by sending a crafted pickle payload through the SendPolicyInstructions, SendObservations, or GetActions gRPC calls.
CVSS Score
9.3
EPSS Score
0.001
Published
2026-04-23