PraisonAI 在模板提取过程中存在任意文件写入 (Zip Slip) 漏洞

攻击者可以利用此漏洞通过下载并解压来自外部来源（例如 GitHub）的模板归档文件，在 PraisonAI 的提取目录之外写入任意文件。由于 PraisonAI 使用 Python 的 zipfile.extractall() 函数进行解压，而未验证归档文件中的文件是否会超出目标提取目录，因此攻击者可以通过精心构造的归档文件，将恶意文件写入到系统中的敏感位置。这可能导致攻击者执行恶意代码、篡改系统文件，甚至完全控制目标系统。类似于其他 Zip Slip 漏洞，此漏洞的潜在影响非常严重，需要立即修复。

Organizations using PraisonAI for collaborative AI development and deployment are at risk, particularly those who allow users to import templates from external sources like GitHub. Shared hosting environments where multiple users share the same PraisonAI installation are also at increased risk, as a compromised template from one user could potentially affect other users.

• python: Monitor PraisonAI logs for suspicious file extraction activity, particularly attempts to write files outside the designated template directory. Look for patterns involving zipfile.extractall() and unusual file paths.

# Example: Monitor for file extraction attempts
import os
import logging

logging.basicConfig(filename='praisona.log', level=logging.INFO)

for root, _, files in os.walk('/path/to/praisona/templates'): # Replace with actual path
    for file in files:
        logging.info(f'File accessed: {os.path.join(root, file)}')

• generic web: Monitor web server access logs for requests to download template archives from external sources. Analyze the downloaded archives for suspicious filenames or directory traversal sequences. • generic web: Check PraisonAI's configuration files for any settings related to template download locations or extraction directories. Ensure these settings are properly secured and restricted.

1. 2026-04-07Disclosure

   disclosure

1. 已保留2026-04-06
2. 发布日期2026-04-07
3. 修改日期2026-04-09
4. EPSS 更新日期2026-04-15

最有效的缓解措施是立即升级到 PraisonAI 1.5.113 或更高版本。如果无法立即升级，可以考虑以下临时缓解措施：首先，禁用 PraisonAI 的模板安装功能，直到升级完成。其次，严格审查从外部来源下载的模板归档文件，确保其来源可靠且不包含恶意文件。第三，配置 Web 应用防火墙 (WAF) 或代理服务器，以阻止上传包含恶意文件的归档文件。最后，监控 PraisonAI 的日志文件，以检测任何异常的文件写入活动。