Autogpt ClassicApplication · Agpt

CVE-2024-1880

HIGH · 7.8 CVSS v3.1 Published 2024-06-06
Fix available
A fix is available. Upgrade to 0.5.1 or later.
See remediation →
80/100
Remediation priority · High
Public exploit Zero-click Patch available

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
An OS command injection vulnerability exists in the MacOS Text-To-Speech class MacOSTTS of the significant-gravitas/autogpt project, affecting versions up to v0.5.0. The vulnerability arises from the improper neutralization of special elements used in an OS command within the `_speech` method of the MacOSTTS class. Specifically, the use of `os.system` to execute the `say` command with user-supplied text allows for arbitrary code execution if an attacker can inject shell commands. This issue is triggered when the AutoGPT instance is run with the `--speak` option enabled and configured with `TEXT_TO_SPEECH_PROVIDER=macos`, reflecting back a shell injection snippet. The impact of this vulnerability is the potential execution of arbitrary code on the instance running AutoGPT. The issue was addressed in version 5.1.0.

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
How this class of weakness works · CWE-78

User input reaches a shell or system command without being fully separated from the command itself, so an attacker can append their own instructions. Because these run with the application's privileges, it often means full control of the host. The lasting fix is to avoid the shell entirely — call APIs directly and pass arguments as data, never as concatenated strings.

General guidance for the os command injection class — the official description and references above are authoritative for this specific CVE. Want a bespoke review and a reviewed fix? Ask our team →

Affected products & versions What the vendor confirmedThe version ranges the vendor confirmed as vulnerable. If your version sits inside a range here, treat yourself as exposed until you have upgraded.

NVD · CPE data
Autogpt ClassicApplication
Affected:< 0.5.1

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
Local
Complexity
Low
Privileges
Low
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

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
Upgrade available Upgrade to 0.5.1 or later
Fixed in 0.5.1
Vendor patch github.com →
Recommended fix High confidence

5.1.0 or later

  1. Upgrade AutoGPT Classic to version 5.1.0 or later to address the OS command injection vulnerability in the MacOSTTS class
  2. If immediate upgrade is not possible, disable the --speak option or avoid using TEXT_TO_SPEECH_PROVIDER=macos configuration
  3. Review any user-supplied input that could be passed to the text-to-speech functionality

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

We can perform the upgrade in your staging environment and verify nothing breaks — typical engagement from $3,200. Get the upgrade done

Scan for this in your stack

Free · runs locally
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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-2024-1880 in production — separate from our analysis above.

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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
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  • Version or environment caveats, and links to real fixes
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