Vulnerabilities (CVE)

Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. Running Auto-GPT version prior to 0.4.3 by cloning the git repo and executing `docker compose run auto-gpt` in the repo root uses a different docker-compose.yml file from the one suggested in the official docker set up instructions. The docker-compose.yml file located in the repo root mounts itself into the docker container without write protection. This means that if malicious custom pyt ... Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. Running Auto-GPT version prior to 0.4.3 by cloning the git repo and executing `docker compose run auto-gpt` in the repo root uses a different docker-compose.yml file from the one suggested in the official docker set up instructions. The docker-compose.yml file located in the repo root mounts itself into the docker container without write protection. This means that if malicious custom python code is executed via the `execute_python_file` and `execute_python_code` commands, it can overwrite the docker-compose.yml file and abuse it to gain control of the host system the next time Auto-GPT is started. The issue has been patched in version 0.4.3.

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Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. When Auto-GPT is executed directly on the host system via the provided run.sh or run.bat files, custom Python code execution is sandboxed using a temporary dedicated docker container which should not have access to any files outside of the Auto-GPT workspace directory. Before v0.4.3, the `execute_python_code` command (introduced in v0.4.1) does not sanitize the `basename` arg before writi ... Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. When Auto-GPT is executed directly on the host system via the provided run.sh or run.bat files, custom Python code execution is sandboxed using a temporary dedicated docker container which should not have access to any files outside of the Auto-GPT workspace directory. Before v0.4.3, the `execute_python_code` command (introduced in v0.4.1) does not sanitize the `basename` arg before writing LLM-supplied code to a file with an LLM-supplied name. This allows for a path traversal attack that can overwrite any .py file outside the workspace directory by specifying a `basename` such as `../../../main.py`. This can further be abused to achieve arbitrary code execution on the host running Auto-GPT by e.g. overwriting autogpt/main.py which will be executed outside of the docker environment meant to sandbox custom python code execution the next time Auto-GPT is started. The issue has been patched in version 0.4.3. As a workaround, the risk introduced by this vulnerability can be remediated by running Auto-GPT in a virtual machine, or another environment in which damage to files or corruption of the program is not a critical problem.

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Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. The Auto-GPT command line UI makes heavy use of color-coded print statements to signify different types of system messages to the user, including messages that are crucial for the user to review and control which commands should be executed. Before v0.4.3, it was possible for a malicious external resource (such as a website browsed by Auto-GPT) to cause misleading messages to be printed t ... Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. The Auto-GPT command line UI makes heavy use of color-coded print statements to signify different types of system messages to the user, including messages that are crucial for the user to review and control which commands should be executed. Before v0.4.3, it was possible for a malicious external resource (such as a website browsed by Auto-GPT) to cause misleading messages to be printed to the console by getting the LLM to regurgitate JSON encoded ANSI escape sequences (`\u001b[`). These escape sequences were JSON decoded and printed to the console as part of the model's "thinking process". The issue has been patched in release version 0.4.3.

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AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to 0.6.48, an authenticated user could achieve Remote Code Execution (RCE) on the backend server by embedding a disabled block inside a graph. The BlockInstallationBlock — a development tool capable of writing and importing arbitrary Python code — was marked disabled=True, but graph validation did not enforce this flag. This allowed any authentica ... AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to 0.6.48, an authenticated user could achieve Remote Code Execution (RCE) on the backend server by embedding a disabled block inside a graph. The BlockInstallationBlock — a development tool capable of writing and importing arbitrary Python code — was marked disabled=True, but graph validation did not enforce this flag. This allowed any authenticated user to bypass the restriction by including the block as a node in a graph, rather than calling the block's execution endpoint directly (which did enforce the flag). This vulnerability is fixed in 0.6.48.

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AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to autogpt-platform-beta-v0.6.34, in SendDiscordFileBlock, the third-party library aiohttp.ClientSession().get is used directly to access the URL, but the input URL is not filtered, which will cause SSRF vulnerability. This issue has been patched in autogpt-platform-beta-v0.6.34.

AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to autogpt-platform-beta-v0.6.34, in RSSFeedBlock, the third-party library urllib.request.urlopen is used directly to access the URL, but the input URL is not filtered, which will cause SSRF vulnerability. This issue has been patched in autogpt-platform-beta-v0.6.34.

AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to autogpt-platform-beta-v0.6.44, AutoGPT Platform's block execution endpoints (both main web API and external API) allow executing blocks by UUID without checking the `disabled` flag. Any authenticated user can execute the disabled `BlockInstallationBlock`, which writes arbitrary Python code to the server filesystem and executes it via `__import_ ... AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to autogpt-platform-beta-v0.6.44, AutoGPT Platform's block execution endpoints (both main web API and external API) allow executing blocks by UUID without checking the `disabled` flag. Any authenticated user can execute the disabled `BlockInstallationBlock`, which writes arbitrary Python code to the server filesystem and executes it via `__import__()`, achieving Remote Code Execution. In default self-hosted deployments where Supabase signup is enabled, an attacker can self-register; if signup is disabled (e.g., hosted), the attacker needs an existing account. autogpt-platform-beta-v0.6.44 contains a fix.

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AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to autogpt-platform-beta-v0.6.46, the AutoGPT platform's Stagehand integration blocks log API keys and authentication secrets in plaintext using logger.info() statements. This occurs in three separate block implementations (StagehandObserveBlock, StagehandActBlock, and StagehandExtractBlock) where the code explicitly calls api_key.get_secret_value ... AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to autogpt-platform-beta-v0.6.46, the AutoGPT platform's Stagehand integration blocks log API keys and authentication secrets in plaintext using logger.info() statements. This occurs in three separate block implementations (StagehandObserveBlock, StagehandActBlock, and StagehandExtractBlock) where the code explicitly calls api_key.get_secret_value() and logs the result. This issue has been patched in autogpt-platform-beta-v0.6.46.

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AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to autogpt-platform-beta-v0.6.32, there is a DoS vulnerability in ReadRSSFeedBlock. In RSSBlock, feedparser.parser is called to obtain the XML file according to the URL input by the user, parse the XML, and finally obtain the parsed result. However, during the parsing process, there is no limit on the parsing time and the resources that can be all ... AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to autogpt-platform-beta-v0.6.32, there is a DoS vulnerability in ReadRSSFeedBlock. In RSSBlock, feedparser.parser is called to obtain the XML file according to the URL input by the user, parse the XML, and finally obtain the parsed result. However, during the parsing process, there is no limit on the parsing time and the resources that can be allocated for parsing. When a malicious user lets RSSBlock parse a carefully constructed, deep XML, it will cause memory resources to be exhausted, eventually causing DoS. This issue has been patched in autogpt-platform-beta-v0.6.32.

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AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. The autogpt before 0.6.32 is vulnerable to Regular Expression Denial of Service due to the use of regex at Code Extraction Block. The two Regex are used containing the corresponding dangerous patterns \s+[\s\S]*? and \s+(.*?). They share a common characteristic — the combination of two adjacent quantifiers that can match the same space character (\s). A ... AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. The autogpt before 0.6.32 is vulnerable to Regular Expression Denial of Service due to the use of regex at Code Extraction Block. The two Regex are used containing the corresponding dangerous patterns \s+[\s\S]*? and \s+(.*?). They share a common characteristic — the combination of two adjacent quantifiers that can match the same space character (\s). As a result, an attacker can supply a long sequence of space characters to trigger excessive regex backtracking, potentially leading to a Denial of Service (DoS). This vulnerability is fixed in 0.6.32.

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AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Versions prior to autogpt-platform-beta-v0.4.2 contains a server-side request forgery (SSRF) vulnerability inside component (or block) `Send Web Request`. The root cause is that IPV6 address is not restricted or filtered, which allows attackers to perform a server side request forgery to visit an IPV6 service. autogpt-platform-beta-v0.4.2 fixes the iss ... AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Versions prior to autogpt-platform-beta-v0.4.2 contains a server-side request forgery (SSRF) vulnerability inside component (or block) `Send Web Request`. The root cause is that IPV6 address is not restricted or filtered, which allows attackers to perform a server side request forgery to visit an IPV6 service. autogpt-platform-beta-v0.4.2 fixes the issue.

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AutoGPT versions 0.3.4 and earlier are vulnerable to a Server-Side Template Injection (SSTI) that could lead to Remote Code Execution (RCE). The vulnerability arises from the improper handling of user-supplied format strings in the `AgentOutputBlock` implementation, where malicious input is passed to the Jinja2 templating engine without adequate security measures. Attackers can exploit this flaw to execute arbitrary commands on the host system. The issue is fixed in version 0.4.0.

A command injection vulnerability exists in the workflow-checker.yml workflow of significant-gravitas/autogpt. The untrusted user input `github.head.ref` is used insecurely, allowing an attacker to inject arbitrary commands. This vulnerability affects versions up to and including the latest version. An attacker can exploit this by creating a branch name with a malicious payload and opening a pull request, potentially leading to reverse shell access or theft of sensitive tokens and keys.

AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. The AutoGPT Platform's WebSocket API transmitted node execution updates to subscribers based on the graph_id+graph_version. Additionally, there was no check prohibiting users from subscribing with another user's graph_id+graph_version. As a result, node execution updates from one user's graph execution could be received by another user within the same i ... AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. The AutoGPT Platform's WebSocket API transmitted node execution updates to subscribers based on the graph_id+graph_version. Additionally, there was no check prohibiting users from subscribing with another user's graph_id+graph_version. As a result, node execution updates from one user's graph execution could be received by another user within the same instance. This vulnerability does not occur between different instances or between users and non-users of the platform. Single-user instances are not affected. In private instances with a user white-list, the impact is limited by the fact that all potential unintended recipients of these node execution updates must have been admitted by the administrator. This vulnerability is fixed in 0.6.1.

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AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to 0.6.1, AutoGPT allows SSRF due to DNS Rebinding in requests wrapper. AutoGPT is built with a wrapper around Python's requests library, hardening the application against SSRF. The code for this wrapper can be found in autogpt_platform/backend/backend/util/request.py. The requested hostname of a URL which is being requested is validated, ensuring ... AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to 0.6.1, AutoGPT allows SSRF due to DNS Rebinding in requests wrapper. AutoGPT is built with a wrapper around Python's requests library, hardening the application against SSRF. The code for this wrapper can be found in autogpt_platform/backend/backend/util/request.py. The requested hostname of a URL which is being requested is validated, ensuring that it does not resolve to any local ipv4 or ipv6 addresses. However, this check is not sufficient, as a DNS server may initially respond with a non-blocked address, with a TTL of 0. This means that the initial resolution would appear as a non-blocked address. In this case, validate_url() will return the url as successful. After validate_url() has successfully returned the url, the url is then passed to the real request() function. When the real request() function is called with the validated url, request() will once again resolve the address of the hostname, because the record will not have been cached (due to TTL 0). This resolution may be in the "invalid range". This type of attack is called a "DNS Rebinding Attack". This vulnerability is fixed in 0.6.1.

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AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to 0.6.1, AutoGPT allows of leakage of cross-domain cookies and protected headers in requests redirect. AutoGPT uses a wrapper around the requests python library, located in autogpt_platform/backend/backend/util/request.py. In this wrapper, redirects are specifically NOT followed for the first request. If the wrapper is used with allow_redirects s ... AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to 0.6.1, AutoGPT allows of leakage of cross-domain cookies and protected headers in requests redirect. AutoGPT uses a wrapper around the requests python library, located in autogpt_platform/backend/backend/util/request.py. In this wrapper, redirects are specifically NOT followed for the first request. If the wrapper is used with allow_redirects set to True (which is the default), any redirect is not followed by the initial request, but rather re-requested by the wrapper using the new location. However, there is a fundamental flaw in manually re-requesting the new location: it does not account for security-sensitive headers which should not be sent cross-origin, such as the Authorization and Proxy-Authorization header, and cookies. For example in autogpt_platform/backend/backend/blocks/github/_api.py, an Authorization header is set when retrieving data from the GitHub API. However, if GitHub suffers from an open redirect vulnerability (such as the made-up example of https://api.github.com/repos/{owner}/{repo}/issues/comments/{comment_id}/../../../../../redirect/?url=https://joshua.hu/), and the script can be coerced into visiting it with the Authorization header, the GitHub credentials in the Authorization header will be leaked. This allows leaking auth headers and private cookies. This vulnerability is fixed in 0.6.1.

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A Server-Side Request Forgery (SSRF) vulnerability was identified in the Requests utility of significant-gravitas/autogpt versions prior to v0.4.0. The vulnerability arises due to a hostname confusion between the `urlparse` function from the `urllib.parse` library and the `requests` library. A malicious user can exploit this by submitting a specially crafted URL, such as `http://localhost:\@google.com/../`, to bypass the SSRF check and perform an SSRF attack.

A vulnerability in significant-gravitas/autogpt version 0.5.1 allows an attacker to bypass the shell commands denylist settings. The issue arises when the denylist is configured to block specific commands, such as 'whoami' and '/bin/whoami'. An attacker can circumvent this restriction by executing commands with a modified path, such as '/bin/./whoami', which is not recognized by the denylist.

AutoGPT, a component of significant-gravitas/autogpt, is vulnerable to an improper neutralization of special elements used in an OS command ('OS Command Injection') due to a flaw in its shell command validation function. Specifically, the vulnerability exists in versions v0.5.0 up to but not including 5.1.0. The issue arises from the application's method of validating shell commands against an allowlist or denylist, where it only checks the first word of the command. This allows an attacker to b ... AutoGPT, a component of significant-gravitas/autogpt, is vulnerable to an improper neutralization of special elements used in an OS command ('OS Command Injection') due to a flaw in its shell command validation function. Specifically, the vulnerability exists in versions v0.5.0 up to but not including 5.1.0. The issue arises from the application's method of validating shell commands against an allowlist or denylist, where it only checks the first word of the command. This allows an attacker to bypass the intended restrictions by crafting commands that are executed despite not being on the allowlist or by including malicious commands not present in the denylist. Successful exploitation of this vulnerability could allow an attacker to execute arbitrary shell commands.

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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 t ... 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.

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A Cross-Site Request Forgery (CSRF) vulnerability in significant-gravitas/autogpt version v0.5.0 allows attackers to execute arbitrary commands on the AutoGPT server. The vulnerability stems from the lack of protections on the API endpoint receiving instructions, enabling an attacker to direct a user running AutoGPT in their local network to a malicious website. This site can then send crafted requests to the AutoGPT server, leading to command execution. The issue is exacerbated by CORS being en ... A Cross-Site Request Forgery (CSRF) vulnerability in significant-gravitas/autogpt version v0.5.0 allows attackers to execute arbitrary commands on the AutoGPT server. The vulnerability stems from the lack of protections on the API endpoint receiving instructions, enabling an attacker to direct a user running AutoGPT in their local network to a malicious website. This site can then send crafted requests to the AutoGPT server, leading to command execution. The issue is exacerbated by CORS being enabled for arbitrary origins by default, allowing the attacker to read the response of all cross-site queries. This vulnerability was addressed in version 5.1.

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AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents. In v0.6.15 and below, the external API's get_graph_execution_results endpoint has an authorization bypass vulnerability. While it correctly validates user access to the graph_id, it fails to verify ownership of the graph_exec_id parameter, allowing authenticated users to access any execution results by providing arbitrary execution IDs. The internal API implements proper validation fo ... AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents. In v0.6.15 and below, the external API's get_graph_execution_results endpoint has an authorization bypass vulnerability. While it correctly validates user access to the graph_id, it fails to verify ownership of the graph_exec_id parameter, allowing authenticated users to access any execution results by providing arbitrary execution IDs. The internal API implements proper validation for both parameters. This is fixed in v0.6.16.

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