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AutoGPT EUVDEUVD-2026-39090

| CVE-2026-33235 HIGH
Uncontrolled Resource Consumption (CWE-400)
2026-06-24 security-advisories@github.com
7.7
CVSS 3.1 · Vendor: github
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Attack ChainAIDerived

Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain

  1. Access
    Authenticate to AutoGPT instance
  2. Delivery
    Create graph with Fill Text Template block
  3. Exploit
    Inject computationally expensive Jinja2 expression
  4. Execution
    Execute block to evaluate expression
  5. Persist
    Exhaust server CPU and memory
  6. Impact
    Host hangs or crashes (service outage)

Vulnerability Assessment

Weakness
CWE
OWASP Top 10:2025
A06:2025 - Insecure Design
ASVS 5.0
V2 - Validation and Business Logic Resource consumption limits
MITRE ATT&CK

1 technique across 1 tactic: Impact

The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up.

Exploitation Conditions

Exploitation requires an authenticated low-privilege account (CVSS PR:L) that can create or run an agent graph using the Fill Text Template block - that block, which renders user-controlled Jinja2 through a SandboxedEnvironment with no execution-time or complexity limit, is the exact prerequisite. No user interaction by a victim is needed (UI:N) and no special non-default configuration is required beyond having the block available. The principal limiting factor is authentication and the impact profile: the consequence is denial of service against availability only (no confidentiality or integrity impact), and meaningful harm to others requires a shared/multi-tenant or self-hosted-shared deployment, since a single-user install would only affect the attacker's own instance.

Impact

The supplied CVSS 3.1 vector (AV:N/AC:L/PR:L/UI:N/S:C/C:N/I:N/A:H, score 7.7) indicates a network-reachable, low-complexity attack requiring only low privileges and no user interaction, with high availability impact and a changed scope - consistent with a tenant being able to degrade the whole host. PR:L confirms the attacker must be authenticated (a provisioned user able to create or run a graph containing the block), which meaningfully limits exposure compared to a pre-auth flaw. There is no EPSS score, KEV listing, or POC in the provided data, so likelihood signals are weak: this is a real availability priority for multi-tenant or shared self-hosted deployments (where one user can take down service for all), but a lower priority for single-user installations where the attacker would only be harming themselves. No data is internally conflicting; the main missing signals are EPSS probability and any independent confirmation of exploitation, neither of which is available here.

Exploit ScenarioDerived

An authenticated user on a shared or multi-tenant AutoGPT instance creates or edits an agent graph containing a Fill Text Template block and supplies a computationally expensive Jinja2 expression (for example one that forces enormous iteration or memory allocation). When the block executes, server CPU and memory are saturated, hanging or crashing the host and producing a service outage for all co-tenants until an administrator manually intervenes. No public exploit code is identified at time of analysis, and the network vector with low attack complexity makes the attack trivial to perform once authenticated.

This Week Schedule remediation this week. Why: HIGH severity (CVSS 7.0-8.9).
Patch available 0.3% exploitation probability (EPSS)

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AnalysisAIv1 – Jun 24, 2026

Uncontrolled resource consumption in the AutoGPT platform (versions before 0.6.52) lets an authenticated user crash the server through the Fill Text Template block. The block's Jinja2 SandboxedEnvironment blocks dangerous attribute access but enforces no CPU, memory, or execution-time limits, so a crafted expression can exhaust server resources and hang or crash the host. There is no public exploit identified at time of analysis and the issue is not in CISA KEV, but the bug is straightforward to trigger and the vendor has shipped a fix in 0.6.52.

RemediationAI

Upgrade to the vendor-released patch: AutoGPT platform version 0.6.52 (autogpt-platform-beta-v0.6.52), which fixes the issue per advisory GHSA-ppw9-h7rv-gwq9; download the release at https://github.com/Significant-Gravitas/AutoGPT/releases/tag/autogpt-platform-beta-v0.6.52. If immediate upgrade is not possible, compensating controls for shared deployments include restricting or disabling the Fill Text Template block for untrusted users (trade-off: breaks legitimate templating workflows), running each tenant's agent execution under per-process CPU/memory and timeout limits via cgroups or container resource limits so a runaway template cannot starve the host (trade-off: legitimate heavy jobs may be killed), and limiting account provisioning to trusted users to reduce the attacker population (trade-off: slows onboarding). These mitigations reduce blast radius but do not remove the underlying lack of execution limits, so patching to 0.6.52 remains the durable fix.

Affected VersionsENISA

AutoGPT 0.1.0, < 0.6.52

Affected Packages

euvd autogpt_0_1_0 fix: 0.6.52

Source: OSV (Open Source Vulnerabilities)

Affects your stack

Affects 1 package in euvd

Checking this CVE against your own stacks and servers is part of the Basic plan and up.

Technical ContextAI · show details

AutoGPT is a workflow-automation platform for building and running continuous AI agents. The vulnerable component is the Fill Text Template block, which renders user-supplied text through Jinja2. The backend uses Jinja2's SandboxedEnvironment, which is designed to prevent template injection by restricting access to unsafe Python internals (for example blocking dunder attributes like __class__). However, the sandbox only constrains *what* expressions can reach - it does not constrain *how much work* they perform. This maps to CWE-400 (Uncontrolled Resource Consumption): the root cause is the absence of computational-complexity, recursion, or wall-clock limits on template evaluation, so an attacker can submit syntactically valid but computationally explosive expressions (e.g., large range/multiplication or deeply nested loops) that the sandbox happily executes to completion.

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Severity by source

Vendor (github) PRIMARY 7.7 HIGH
AV:N/AC:L/PR:L/UI:N/S:C/C:N/I:N/A:H
vuln.today AI 7.7 HIGH

Authenticated user can run the block (PR:L), network-reachable and low-complexity (AV:N/AC:L); resource exhaustion crosses tenant boundaries (S:C) with availability-only impact (A:H).

3.1 AV:N/AC:L/PR:L/UI:N/S:C/C:N/I:N/A:H
4.0 AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:H

Primary rating from Vendor (github).

CVSS VectorVendor: github

Attack Vector
Network
Attack Complexity
Low
Privileges Required
Low
User Interaction
None
Scope
Changed
Confidentiality
None
Integrity
None
Availability
High

Lifecycle Timeline

1
Patch available
Jun 24, 2026 - 22:03 EUVD

DescriptionCVE.org

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.

Executive ViewAI

Why It Matters

AutoGPT versions before 0.6.52 contain a denial-of-service vulnerability exploitable by authenticated users, with no public exploit identified at time of analysis. Organizations using affected versions face potential service unavailability that could disrupt business automation operations. Vendor-released patch 0.6.52 is available and should be deployed immediately.

Business Impact: High
Compensating Controls

Apply vendor patch.

Threat Intelligence Overview

EPSS Score
0.3%
Top 77% exploitable
Prevalence
Medium
very popular open-source AI agent project, narrower production self-hosted footprint
Data Quality
6 sources
Confidence: High

How this decision was reached

The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.

SignalValue
Severity HIGH
CISA KEV No
Public POC No
EPSS 0.3%
Patch available Yes
Active threat No
Deciding rule
HIGH severity (CVSS 7.0-8.9)
What every action level means
Emergency Immediate action required. Criteria: CRITICAL + in CISA KEV (actively exploited) without patch, OR CRITICAL + EPSS > 30% without patch, OR CRITICAL + active threat signals without patch.
Act Now Prioritize within 24-48h. Criteria: in KEV with patch available, OR CRITICAL + public POC, OR HIGH + EPSS > 10%, OR CRITICAL + active threat, OR any CRITICAL severity.
This Week Schedule remediation this week. Criteria: HIGH severity (CVSS 7.0-8.9). Patch within normal change window.
This Month Plan within 30 days. Criteria: MEDIUM severity (CVSS 4.0-6.9), lower exploitation probability. Include in regular patch cycle.
Monitor Track and reassess. Criteria: LOW severity (CVSS 0.1-3.9), minimal exploitation risk. No immediate action needed.

SSVC AssessmentENISA

SSVC Decision
Scheduled
Exploitation
Poc
System Exposure· derived
Open
Automatable
No
Human Impact
High
Technical Impact
Partial

Priority Score

38
Low Medium High Critical
KEV: 0
EPSS: 0
CVSS: +38
PoC: 0
Weaponized: 0
Threat intel: 0
Gov advisory: 0

Attack Technique

Denial of Service attacks render applications or systems unavailable by overwhelming resources or triggering failure conditions.

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