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Resource Allocation Without LimitsWeakness · CWE-770

CVE-2025-32423

MEDIUM · 5.3 CVSS v4.0 Published 2026-06-26
Mitigation only
No fix yet — a mitigation exists. There is no fixed release. A documented workaround reduces exposure in the meantime.
See remediation →
59/100
Remediation priority · Elevated
Remotely reachable Zero-click 8 weeks old

Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.

NVD · unedited
AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. Prior to 0.6.32, there is a DoS vulnerability in ExtractTextInformationBlock. Malicious users can amplify their input. For example, if a malicious user inputs 10K of content, the server will consume 50G of memory, eventually causing memory resources to be exhausted, resulting in DoS. This vulnerability is fixed in 0.6.32.

Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.

dbcve analysis · high confidence

AutoGPT versions before 0.6.32 contain a memory amplification DoS vulnerability in the ExtractTextInformationBlock function. Attackers can submit relatively small inputs (e.g., 10KB) that cause the server to allocate massive amounts of memory (e.g., 50GB), leading to memory exhaustion and service unavailability.

MitigationUpgrade to AutoGPT 0.6.32 or later, which contains the fix for this vulnerability. If upgrading is not immediately possible, implement input size limits and memory consumption controls on the ExtractTextInformationBlock function.

Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.

CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.

From the vector
Attack vector
Network
Complexity
Low
Privileges
Low
Authentication
X
User interaction
None
Scope
X

CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.

dbcve checks

Work through these to decide whether this CVE applies to you.

  1. Identify AutoGPT installation
    Locate the AutoGPT application or service in your environment. Check for processes named 'autogpt', 'AutoGPT', or check installed packages using pip list | grep -i autogpt or similar package manager commands.
    Affected if AutoGPT is found in your environment and the version is below 0.6.32
  2. Determine installed AutoGPT version
    Run the version check command for your AutoGPT installation (commonly 'autogpt --version', 'python -m autogpt --version', or check the package version via pip show autogpt). Compare the returned version number to 0.6.32.
    Affected if The installed version is lower than 0.6.32 (e.g., 0.6.31, 0.6.30, or any earlier version)
  3. Verify ExtractTextInformationBlock is in use
    Check if your AutoGPT deployment uses the ExtractTextInformationBlock function. This may be visible in logs, configuration files, or by reviewing which plugins or features are enabled. Inspect the codebase or plugin directory for references to 'ExtractTextInformationBlock'.
    Affected if ExtractTextInformationBlock is present and enabled in your AutoGPT configuration or workflow
  4. Monitor memory usage during text extraction
    While AutoGPT is processing text input, monitor server or container memory consumption using system tools (top, htop, docker stats, or similar). Submit a modest-sized text input (around 10KB) and observe if memory spikes dramatically (approaching tens of gigabytes).
    Affected if Memory consumption spikes disproportionately relative to input size, approaching tens of gigabytes for small inputs

Your environment is affected if AutoGPT version is below 0.6.32 and the ExtractTextInformationBlock function is accessible, causing disproportionate memory allocation under normal text processing workloads.

Generated from the published advisory. Verify against your own configuration.

Check your environment

Paste your version and any relevant configuration and it will be compared against the affected criteria above. Do not include secrets or credentials.

AI-assisted, checked against the advisory. Informational, not a guarantee.

Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.

dbcve · scoped
Mitigation available No clean upgrade yet — mitigate in the meantime
Mitigation

Upgrade to AutoGPT 0.6.32 or later, which contains the fix for this vulnerability. If upgrading is not immediately possible, implement input size limits and memory consumption controls on the ExtractTextInformationBlock function.

Recommended fix High confidence

0.6.32

  1. 1. Identify the currently installed AutoGPT version in your environment
  2. 2. Upgrade AutoGPT to version 0.6.32 or later to remediate the resource exhaustion vulnerability in ExtractTextInformationBlock
  3. 3. Verify the upgrade was successful by confirming the installed version

Generated from the published advisory — verify against the referenced sources before acting.

Have this fixed Scoped from the published advisory
  • Consultation2.0 h
  • Implementation4.0 h
  • Testing4.0 h
  • Review / QA2.0 h
12.0 hours of engineering $2,080
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References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.

Primary sources

Practitioner notes

Contributed

Peer-ranked notes from engineers who’ve handled CVE-2025-32423 in production — separate from our analysis above.

No notes yet

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What this is

A place for practitioners to share what actually worked: a mitigation you’ve tested, a configuration change, a version- or environment-specific caveat, or a link to a verified patch. The most useful notes rise to the top as peers upvote them, so the signal stays high.

What belongs here
  • Verified mitigations, workarounds, and config changes
  • Version or environment caveats, and links to real fixes
  • No weaponised exploit code, or anything meant to cause harm
  • No spam, self-promotion, credentials, or personal data