CyberSecBulletin
CVE-2026-24780NVD status: Analyzed

AutoGPT: Improper Control of Generation of Code

Published Updated By the CyberSecBulletin desk

CVE-2026-24780 is a high-severity improper control of generation of code vulnerability in AutoGPT from Significant-Gravitas, with a CVSS 3.1 base score of 8.8 out of 10. It can be exploited remotely over the network by an attacker with a low-privileged account, without any action from a user. Affected AutoGPT versions: >= 0.1.0, < 0.6.44. The record does not name a fixed version, so check the vendor advisory. There is no confirmed exploitation so far. EPSS estimates a 1.26% chance of exploitation within 30 days, higher than 70% of scored CVEs.

Next patch cycle

High severity with no evidence of exploitation so far.

What to do

  1. Update Autogpt Platform to 0.6.44 or a later version.
  2. Read the advisory on github.com for workarounds and exact fixed builds.

Affected products and versions

VendorProductAffected versionsFixed in
Significant-GravitasAutoGPT>= 0.1.0, < 0.6.44Not stated
AgptAutogpt Platform0.1.0 up to, but not including, 0.6.440.6.44

Version data comes from the organisation that assigned the CVE. Confirm against the vendor advisory before deciding you are unaffected.

How the severity score breaks down

Attack vector
NetworkCan be exploited remotely over a network, including the internet.
Attack complexity
LowNo special conditions are needed; the attack works reliably.
Privileges required
LowA basic user account is enough.
User interaction
NoneNo action by a victim is required.
Scope
UnchangedImpact stays within the vulnerable component.
Confidentiality
HighAll data handled by the component can be read.
Integrity
HighData or code can be modified at will.
Availability
HighThe component can be taken down completely.

Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H. Scored by NVD.

Scoring systemScoreSeverityScored by
CVSS 4.08.6HighCNA (github.com)
CVSS 3.18.8HighNVD

Official description

AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to autogpt-platform-beta-v0.6.44, AutoGPT Platform's block execution endpoints (both main web API and external API) allow executing blocks by UUID without checking the `disabled` flag. Any authenticated user can execute the disabled `BlockInstallationBlock`, which writes arbitrary Python code to the server filesystem and executes it via `__import__()`, achieving Remote Code Execution. In default self-hosted deployments where Supabase signup is enabled, an attacker can self-register; if signup is disabled (e.g., hosted), the attacker needs an existing account. autogpt-platform-beta-v0.6.44 contains a fix.

Source: the CVE record as published by its numbering authority, via NVD and CVE.org.

The underlying weakness: Improper Control of Generation of Code

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 developers prevent this class of flaw

  • Refactor your program so that you do not have to dynamically generate code.
  • 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.
  • 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.

More Improper Control of Generation of Code vulnerabilities (CWE-94)

Timeline

  1. CVE record published.
  2. CISA published its SSVC assessment (exploitation: poc, automatable: yes, technical impact: total).
  3. Record last changed materially (score, affected products, status or references).

References

Other vulnerabilities in AutoGPT

All AutoGPT vulnerabilities

Recent Improper Control of Generation of Code vulnerabilities

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