AutoGPT: Uncontrolled Resource Consumption
CVE-2026-33235 is a high-severity uncontrolled resource consumption vulnerability in AutoGPT from Significant-Gravitas, with a CVSS 3.1 base score of 7.7 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, < 0.6.52. The record does not name a fixed version, so check the vendor advisory. There is no confirmed exploitation so far. EPSS estimates a 0.38% chance of exploitation within 30 days, which is low compared with other CVEs.
High severity with no evidence of exploitation so far.
What to do
- Check which version of AutoGPT you run against the affected versions below, and install the vendor's latest release.
- Read the advisory on github.com for workarounds and exact fixed builds.
Affected products and versions
| Vendor | Product | Affected versions | Fixed in |
|---|---|---|---|
| Significant-Gravitas | AutoGPT | >= 0.1.0, < 0.6.52 | Not stated |
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
- ChangedThe attack can reach beyond the vulnerable component into other systems.
- Confidentiality
- NoneNo data is disclosed.
- Integrity
- NoneNothing can be modified.
- Availability
- HighThe component can be taken down completely.
Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:N/I:N/A:H. Scored by CNA (github.com).
Official description
AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. In versions prior to 0.6.52, the Fill Text Template block is vulnerable to a Denial of Service (DoS) attack. While the backend implements a SandboxedEnvironment to prevent unauthorized attribute access (e.g., blocking __class__), it fails to limit the computational complexity or execution time of the expressions. An attacker can input computationally expensive Python/Jinja2 expressions that consume the server's CPU and memory, leading to a complete system hang or crash. In multi-tenant or self-hosted environments, this results in a complete service outage and "noisy neighbor" effects that require manual administrative intervention to recover. This issue has been fixed in version 0.6.52.
Source: the CVE record as published by its numbering authority, via NVD and CVE.org.
The underlying weakness: Uncontrolled Resource Consumption
The product does not properly control the allocation and maintenance of a limited resource.
How developers prevent this class of flaw
- Ensure that protocols have specific limits of scale placed on them.
- Ensure that all failures in resource allocation place the system into a safe posture.
More Uncontrolled Resource Consumption vulnerabilities (CWE-400)
Timeline
- CVE record published.
- CISA published its SSVC assessment (exploitation: poc, automatable: no, technical impact: partial).
- Record last changed materially (score, affected products, status or references).
References
Patches and release notes
Other vulnerabilities in AutoGPT
- 8.2 High severity
- 8.5 High severity
- 8.8 High severity
- 8.7 High severity
- 7.1 High severity
- 8.7 High severity
Recent Uncontrolled Resource Consumption vulnerabilities
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
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