Unsigned Plugin Code Execution in PraisonAI Manager

PraisonAI (praisonaiagents) before 1.6.78 contains a remote code execution vulnerability in the plugin manager, which loads and executes arbitrary Python (.py) files from project-level and user-home .praisonai/plugins/ directories using importlib spec_from_file_location() and exec_module() without code signing, integrity verification, or sandboxing. An attacker who can write a malicious .py file to a plugin directory (for example via path traversal, a supply chain attack, or a compromised dependency) achieves arbitrary code execution when the plugin system initializes.

Casky was already ahead

This CVE exploits attack patterns that Casky's 322matched skills already investigate — long before this vulnerability was disclosed. Claude's reasoning model maps these techniques to MITRE ATT&CK, so practitioners who ran these skills have already seen the threat behaviour in their findings.

Analysis

PraisonAI versions before 1.6.78 suffer from a critical remote code execution vulnerability in their plugin manager. The flaw stems from loading and executing arbitrary Python files directly from user-accessible directories (.praisonai/plugins/) without code signing, integrity verification, or sandboxing protections. Attackers can exploit this through multiple attack vectors—writing malicious plugins via path traversal, compromising supply chain dependencies, or leveraging already-compromised systems to place malicious .py files in predictable locations. Any organization using PraisonAI for agent-based automation, especially in development or production environments where multiple users or processes can write to the plugin directory, faces immediate risk of complete system compromise.

Casky's 322 matched skills leverage Claude's extended reasoning to detect the attack patterns underlying this vulnerability across MITRE ATT&CK's Initial Access (TA0001) and Resource Development (TA0043) techniques. Practitioners using Casky will identify suspicious indicators such as unexpected .py file creation in plugin directories, unsigned module imports via importlib, execution of code from non-standard paths, and process spawning from Python interpreters loading untrusted plugins. The platform's skill mapping surfaces detection opportunities for file integrity monitoring, code signing validation gaps, and anomalous plugin loads—enabling security teams to correlate plugin-related activity with command execution artifacts, lateral movement attempts, or persistence mechanisms. Organizations can use these findings to enforce plugin allowlisting, implement code signing requirements, and monitor plugin directory access patterns before exploitation occurs.

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Casky Risk Score

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EPSS Probability

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Shodan Exposure

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GreyNoise Signal

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Composite risk scoring from EPSS, CISA KEV, Shodan, and GreyNoise — 21 security APIs correlated into a single Casky Risk Score. Coming in Casky Pro. Join early access →

322 Casky skills cover this attack pattern

These skills use Claude AI's reasoning model to surface findings in the same attack categories as CVE-2026-61446.

Abuse of Public-Facing API: Mobile API Abuse

mobile security · low

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abusing-dpapi-for-credential-access

red teaming · high

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abusing-shadow-credentials-for-privesc

red teaming · high

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MITRE ATT&CK Techniques

TA0001 TA0043

Investigate the attack patterns behind CVE-2026-61446

Casky has 322 skills that investigate the attack patterns behind CVE-2026-61446. Run one and get CVSS-scored findings in 3 minutes.

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