CVE-2026-26020: AutoGPT RCE Vulnerability

CVE-2026-26020 Overview

CVE-2026-26020 is a critical Remote Code Execution (RCE) vulnerability affecting AutoGPT, a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. The vulnerability exists in versions prior to 0.6.48 and allows authenticated users to execute arbitrary Python code on the backend server by exploiting a flaw in graph validation logic.

The vulnerability stems from the BlockInstallationBlock — a development tool capable of writing and importing arbitrary Python code — being marked with disabled=True, but the graph validation mechanism failed to enforce this flag. This oversight allowed authenticated attackers to bypass the restriction by embedding the disabled block as a node within a graph, rather than calling the block's execution endpoint directly (which properly enforced the disabled flag).

Critical Impact

Authenticated attackers can achieve full Remote Code Execution on the AutoGPT backend server, potentially leading to complete system compromise, data exfiltration, lateral movement, and persistent access to AI infrastructure.

Affected Products

• AutoGPT Platform versions prior to 0.6.48
• AutoGPT Platform Beta releases before autogpt-platform-beta-v0.6.48

Discovery Timeline

• 2026-02-12 - CVE CVE-2026-26020 published to NVD
• 2026-02-12 - Last updated in NVD database

Technical Details for CVE-2026-26020

Vulnerability Analysis

This vulnerability represents a critical Authorization Bypass (CWE-285: Improper Authorization) that allows authenticated users to execute arbitrary code on the backend server. The flaw exists in the graph validation logic within the AutoGPT platform's backend architecture.

The BlockInstallationBlock is a powerful development tool designed to write and import arbitrary Python code. To prevent misuse, this block was intentionally marked as disabled=True. However, the security controls were not uniformly enforced across all code paths. While the direct block execution endpoint properly checked and enforced the disabled flag, the graph validation mechanism — responsible for validating nodes within user-created graphs — completely ignored this flag.

This inconsistency in authorization enforcement created a bypass vector. An attacker with valid authentication credentials could craft a malicious graph containing the disabled BlockInstallationBlock as a node. When the graph was processed, the system would execute the block without verifying its disabled status, effectively granting the attacker the ability to run arbitrary Python code on the backend server.

Root Cause

The root cause is inconsistent authorization enforcement across different code paths. The disabled flag on blocks was only checked at the direct execution endpoint level (/execute) but not during graph validation and node execution within the graph processing pipeline. This violated the principle of defense in depth and created an authorization bypass vulnerability.

Specifically, the backend/data/graph.py validation logic and the backend/executor/manager.py execution logic failed to verify whether a block was disabled before allowing it to be included in graphs or executed as part of graph processing.

Attack Vector

The attack requires network access and valid authentication credentials to the AutoGPT platform. An authenticated attacker exploits this vulnerability through the following steps:

1. Authenticate to the AutoGPT platform with valid credentials
2. Create a new graph workflow
3. Embed the disabled BlockInstallationBlock as a node within the graph
4. Configure the block to execute arbitrary Python code
5. Submit the graph for processing
6. The backend server executes the malicious Python code without checking the disabled flag

The security patch addresses this by adding explicit disabled flag checks in both the graph validation (graph.py) and execution manager (manager.py) components:

            # For invalid blocks, we still raise immediately as this is a structural issue
             raise ValueError(f"Invalid block {node.block_id} for node #{node.id}")

+            if block.disabled:
+                raise ValueError(
+                    f"Block {node.block_id} is disabled and cannot be used in graphs"
+                )

             node_input_mask = (
                 nodes_input_masks.get(node.id, {}) if nodes_input_masks else {}
             )

Source: GitHub Commit Change

The execution manager also received a similar fix:

     block_name=node_block.name,
 )

+    if node_block.disabled:
+        raise ValueError(f"Block {node_block.id} is disabled and cannot be executed")

     # Sanity check: validate the execution input.
     input_data, error = validate_exec(node, data.inputs, resolve_input=False)
     if input_data is None:

Source: GitHub Commit Change

Detection Methods for CVE-2026-26020

Indicators of Compromise

• Unexpected graphs containing BlockInstallationBlock nodes in the system
• Unusual Python code execution or process spawning from the AutoGPT backend service
• Anomalous network connections originating from the backend server
• Unauthorized file system modifications or new files in the AutoGPT installation directory

Detection Strategies

• Monitor graph creation and modification events for references to disabled block types, particularly BlockInstallationBlock
• Implement application-level logging to track all block executions and flag any disabled blocks that are invoked
• Deploy endpoint detection and response (EDR) solutions to identify suspicious Python process behavior on the backend server
• Review authentication logs for unusual access patterns followed by graph creation activities

Monitoring Recommendations

• Enable verbose logging for the AutoGPT graph validation and execution subsystems
• Set up alerts for any ValueError exceptions related to disabled blocks as these may indicate exploitation attempts
• Monitor backend server processes for unexpected child processes or network connections
• Implement file integrity monitoring on the AutoGPT backend server to detect unauthorized modifications

How to Mitigate CVE-2026-26020

Immediate Actions Required

• Upgrade AutoGPT Platform to version 0.6.48 or later immediately
• Audit existing graphs in the system for any unauthorized or suspicious BlockInstallationBlock references
• Review authentication logs and user activity to identify potential exploitation
• Consider temporarily restricting access to the graph creation functionality until the patch is applied

Patch Information

The vulnerability is fixed in AutoGPT Platform version 0.6.48. The patch adds explicit disabled flag validation in both the graph validation logic (backend/data/graph.py) and the execution manager (backend/executor/manager.py). Organizations should upgrade to this version or later to remediate the vulnerability.

For detailed patch information, refer to the GitHub Security Advisory GHSA-4crw-9p35-9x54 and the release notes for version 0.6.48.

Workarounds

• If immediate patching is not possible, implement network segmentation to limit access to the AutoGPT backend server
• Restrict user authentication to only trusted individuals until the patch can be applied
• Deploy a web application firewall (WAF) with custom rules to inspect and block graph submissions containing references to disabled block types
• Consider temporarily disabling the graph creation functionality in production environments

# Upgrade AutoGPT to the patched version
cd /path/to/autogpt
git fetch --tags
git checkout autogpt-platform-beta-v0.6.48

# Verify the patch is applied by checking for the disabled block validation
grep -r "block.disabled" backend/data/graph.py
grep -r "node_block.disabled" backend/executor/manager.py