CVE-2026-56834 in PraisonAI
Summary
by MITRE • 10/23/2026
PraisonAI is a multi-agent teams system. From version 3.8.1 to before version 4.6.59, PraisonAI's Dynamic Context Discovery feature exposes artifact helper tools through ctx.get_tools(). The implemented artifact tools do not enforce that the supplied artifact_path is an artifact created by the configured store or that it lives under the configured artifact base directory. Instead, artifact_head, artifact_tail, artifact_grep, and artifact_chunk wrap the caller-supplied path directly into an ArtifactRef and then read it from the host filesystem. As a result, any prompt/user/tool-caller that can influence those tool arguments can read files readable by the PraisonAI process, such as project .env files, cloud credentials, SSH keys, source files, or other local data. This issue has been patched in version 4.6.59.
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Analysis
by VulDB Data Team • 10/23/2026
The vulnerability identified within PraisonAI versions ranging from 3.8.1 to just prior to the release of version 4.6.59 represents a critical path traversal and arbitrary file read flaw rooted in insufficient input validation during dynamic context discovery operations. This security defect specifically affects the artifact helper tools exposed through the ctx.get_tools() interface, which are designed to facilitate interaction with stored artifacts within the multi-agent team system architecture. The core technical failure lies in the implementation of functions such as artifact_head, artifact_tail, artifact_grep, and artifact_chunk, which accept a user-supplied or tool-caller-provided path argument without performing rigorous validation against an allowlist or enforcing directory containment checks relative to the configured artifact base directory. Instead of verifying that the supplied artifact_path corresponds exclusively to artifacts managed by the designated store, these functions directly wrap the unvalidated input into an ArtifactRef object and subsequently pass it to underlying file system read operations on the host machine.
This architectural oversight effectively bypasses intended isolation boundaries, allowing any entity capable of influencing the arguments passed to these tools to read arbitrary files accessible by the PraisonAI process user account. In practical operational terms, this means that a malicious actor who can inject prompts or manipulate tool calls within the system context gains the ability to exfiltrate sensitive local data residing on the host filesystem. The scope of potential exposure is extensive and includes high-value targets such as project environment variable files containing database credentials or API keys, cloud provider access tokens, SSH private keys used for remote authentication, proprietary source code repositories, and other confidential configuration data stored locally. Because the vulnerability relies on direct file system reads rather than complex exploitation chains involving buffer overflows or memory corruption, it is highly reliable and easily exploitable by any user with write access to agent inputs or prompt engineering capabilities within the application layer.
From a classification perspective, this flaw aligns closely with CWE-22: Improper Limitation of a Pathname to a Restricted Directory, commonly known as path traversal, where software does not properly neutralize special elements that can cause paths to resolve to directories outside of the intended restricted directory. Furthermore, it maps directly to MITRE ATT&CK technique T1083: File and Directory Discovery, which describes adversaries using system utilities or scripts to enumerate files and folders on compromised systems for further reconnaissance and data staging. The lack of strict path canonicalization and boundary enforcement allows attackers to utilize standard relative path sequences like dot-dot-slash to escape the artifact storage root and access parent directories where sensitive operational secrets are typically stored in plaintext configuration files.
The remediation strategy implemented in version 4.6.59 addresses this issue by enforcing strict validation on all incoming file paths before they are processed by the artifact tools. This likely involves canonicalizing the provided path to resolve any symbolic links or relative navigation sequences and then verifying that the resulting absolute path remains strictly within the boundaries of the configured artifact base directory. Additionally, implementing an allowlist mechanism for artifacts created through the official store interface would provide defense-in-depth against such traversal attempts. For organizations still running affected versions, immediate mitigation requires restricting network access to PraisonAI interfaces, enforcing strict input sanitization at any proxy or gateway layer if applicable, and auditing agent prompts for injection patterns that could trigger these vulnerable tool calls until an upgrade can be performed.