Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:L/A:NSummary
CVE-2026-55524 is a high-severity Time-of-check Time-of-use (TOCTOU) Race Condition (CWE-367) vulnerability. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Path Interception (T1034); ranked at the 9th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to AC-25 (Reference Monitor) and AC-4 (Information Flow Enforcement) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-53606
Vulnerability Data
PraisonAI is a multi-agent teams system. In versions prior to 1.6.58, the web_crawl tool performs its SSRF check only on the initially supplied URL, allowing the protection to be bypassed so the tool connects to attacker-chosen internal destinations. The check…
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resolves the hostname once with socket.gethostbyname and rejects private/loopback/link-local results, but then passes the URL to a fetcher using httpx.Client(follow_redirects=True) (or urllib.request.urlopen when httpx is absent, which also follows redirects) that re-resolves the hostname at connect time with no further validation. This validate-here/fetch-there gap is exploitable through both HTTP redirects and DNS rebinding. If an attacker can influence URLs passed to web_crawl(), directly or through an agent/tool workflow, they can cause the PraisonAI host to fetch loopback, private-network, or cloud metadata endpoints reachable from that host, with the response body returned in the web_crawl() result. This issue has been fixed in version 1.6.58.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V15.4.2V17.2.6V1.3.6V1.5.3
Mitigating Controls (NIST 800-53 r5) AI
A reference monitor that is always invoked and analyzable structurally eliminates the non-atomic check-then-use pattern underlying TOCTOU.
Information flow enforcement can restrict which destinations the server is allowed to contact on behalf of users.
Input validation directly stops untrusted URLs from being accepted and fetched without destination checks.
Access enforcement that performs an atomic check-and-use decision directly stops the window in which a TOCTOU race can be exploited.
Process isolation limits the blast radius of a successful TOCTOU exploitation but does not remove the race itself.
Boundary protection limits the network reach of server-initiated requests even if SSRF occurs.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly include coding standards and reviews that prevent TOCTOU race conditions.
Runtime monitoring of web applications and services can detect anomalous outbound requests indicative of SSRF.
Vulnerability identification processes can discover and record SSRF flaws in web applications.
Network segmentation and egress controls can limit the damage from successful SSRF requests.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Operational threat data describing SSRF campaigns can be used to tighten outbound-request allow-lists and detection rules before attackers exploit them.
Reliable, synchronized time across systems narrows the exploitable window in which a resource state can change between a security check and its use.