CVE Catalog

CVE-2026-55523

HighCVSS 7.7
Published: Updated: Translated: NVD NIST

Exploitation Probability (EPSS)

Low risk
0.34%

27th percentile - higher than 27% of all known CVEs

Summary

PraisonAI versions 1.5.128 through 1.6.57 contain an SSRF vulnerability in the web_crawl() function. Despite initial URL validation, redirect targets are not checked, allowing an attacker to access internal resources via a public URL that redirects to loopback or private networks. This is an incomplete fix for previous SSRF vulnerabilities.

Risk Assessment

The risk includes the ability to make requests to internal services and cloud metadata, which could lead to data confidentiality breaches or further attacks on the internal network.

Recommendation

Upgrade PraisonAI to version 1.6.58, which contains a complete fix eliminating the SSRF bypass.

Other vulnerabilities in PraisonAI

See all
Original NVD description (English source)

PraisonAI is a multi-agent teams system. In versions 1.5.128 through 1.6.57, the praisonaiagents.tools.web_crawl_tools.web_crawl() function is vulnerable to server-side request forgery. While it validates the initially supplied URL and blocks direct loopback and private destinations, its default httpx fallback uses httpx.Client(follow_redirects=True) and does not revalidate intermediate or final redirect targets. An attacker who can influence a URL passed to web_crawl(), directly or through an agent or tool workflow, can supply an attacker-controlled public URL that passes the initial host check and then redirects to loopback, private-network, or cloud metadata endpoints reachable from the host, with the redirected response body returned in the web_crawl() result. This constitutes an incomplete fix and patch bypass for the previously disclosed web_crawl SSRF class (GHSA-qq9r-63f6-v542 / CVE-2026-40160 and GHSA-8f4v-xfm9-3244), since the guard validates only the requested URL and not the destination actually fetched after redirection. This issue has been fixed in version 1.6.58.

Vulnerability data from NVD (NIST) · CISA KEV · EPSS