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CVE-2026-70470 – Remote Code Execution (Python Validator Bypass) – Flowise ≤ 3.1.2

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Summary

CVE-2026-70470 is a critical remote code execution vulnerability in Flowise (FlowiseAI), the open-source low-code platform for building LLM apps and AI agents. Flowise’s Python code validator can be bypassed with Unicode homoglyph characters, allowing arbitrary Python execution in Pyodide and OS command execution on the host. It carries a CVSS 4.0 base score of 9.5 (Critical).

Technical details

  • Root cause: The Python code validator relies on a JavaScript regex blacklist (CWE-184, Incomplete List of Disallowed Inputs). JavaScript’s b word boundary only recognizes ASCII characters, so a homoglyph such as __cl𝐚ss__ (using U+1D41A, "Mathematical bold small a") is not caught by patterns like b__class__b.
  • Trigger conditions: Python 3 applies NFKC normalization to identifiers at parse time, converting the homoglyph back to its ASCII form during execution. The mismatch lets forbidden identifiers slip past the blacklist and run inside Pyodide, reaching OS command execution.
  • Attack vector: Network. Users who can reach a chatflow — including unauthenticated users on public CSV Agent or Airtable Agent chatflows — can inject the malicious Python via LLM-generated responses or customReadCSV configuration parameters.
  • Impact: Arbitrary OS command execution as the Flowise process on the host, enabling credential theft, file access, network pivoting, and multi-tenant workspace compromise.

Affected software

  • Flowise (npm flowise and flowise-components) versions ≤ 3.1.2.

Severity

  • CVSS 4.0 base score: 9.5 (Critical)
  • Vector: CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H

Mitigation and recommended actions

  • Immediate: Upgrade Flowise to version 3.1.3, which fixes the validator bypass.
  • If no patch: Restrict network access to Flowise instances (authentication, IP allow-listing, VPN), avoid exposing chatflows publicly, and disable or restrict CSV Agent / Airtable Agent chatflows that permit Python execution until the upgrade is applied.

How IONIX identifies potentially affected assets

IONIX matches the following signals against data already collected when it crawled the asset; identifying the technology sends no request beyond that crawl.

  • Page title: Flowise - Build AI Agents, Visually, Flowise - Low-code LLM apps builder
  • Meta tag content: FlowiseAI, Open source generative AI development platform for building AI agents
  • Raw response body: data-rewardful="9a3a26", og:site_name, flowiseai.com

References

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Map your entire attack surface (continously)

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Dozens of threat intel feeds using agentic technology are continuously analyzed to detect the appearance of proof-of-concept code, exploit kits, and indicators of active targeting. IONIX goes further by applying AI to proactively evaluate whether emerging vulnerabilities are likely to be exploited, even before PoCs go public.

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Not all CVEs matter. IONIX filters vulnerabilities by asking attacker-centric questions: Can it be reached from the internet? Does it require authentication? Is it being exploited in the wild? This dramatically reduces noise and focuses teams on threats that can actually be weaponized.

4

Create Safe, Scalable Exploit Validations

IONIX transforms real-world PoCs into safe, non-intrusive test payloads that can be run in production environments without disruption. These simulations are precisely targeted to the systems that are vulnerable, ensuring rapid validation without unnecessary load.

5

Execute Exploit Validations

By combining context about software stack, versioning, exposure status, and reachability, IONIX ensures that only the right payloads are executed against the right assets, maximizing efficiency and minimizing risk.

6

Drive Fast and Actionable Remediation

Results are routed through integrations with ticketing, SOAR, and SIEM tools. Issues are written in plain language, bundled into remediation clusters, and prioritized based on asset criticality, exploitability, and blast radius. This shortens mean time to remediation (MTTR) and empowers teams to act with confidence.

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