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CVE-2026-86099 – Unauthenticated Path Traversal / Filesystem Destruction – Chainlit ≤ 2.12.0

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Summary

CVE-2026-86099 is a path traversal vulnerability (CWE-22) in Chainlit, the open-source Python framework for building conversational AI/LLM chat interfaces. Chainlit through version 2.12.0 fails to validate the client-supplied socket.io sessionId parameter, allowing an unauthenticated remote attacker to inject absolute or relative path sequences that escape the intended upload directory. The flaw carries a HIGH severity rating and can result in destruction of arbitrary directories accessible to the Chainlit service process.

Technical details

  • Root cause: The sessionId value supplied by a socket.io client is used, without sanitization, to construct a per-session files_dir path. That path is later passed to a recursive directory-removal (rmtree) call.
  • Trigger condition: An attacker connects over the exposed socket.io interface and supplies a crafted sessionId containing ../ or absolute path sequences.
  • Attack vector: Network, no authentication or user interaction required (AV:N, PR:N, UI:N).
  • Impact: The manipulated path can escape the upload directory, letting the attacker trigger recursive deletion of arbitrary directories reachable by the service process — resulting in a high-impact denial of service via data/file loss, with a limited integrity impact.

Affected software

  • Chainlit (PyPI package chainlit), versions 0 through 2.12.0 inclusive.

Severity

  • CVSS v4.0 base score: 8.8 (HIGH) — CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:L/VA:H/SC:N/SI:N/SA:N
  • CVSS v3.1 base score: 8.2 (HIGH) — CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:H

Mitigation and recommended actions

  • Immediate: As of publication, no Chainlit release beyond 2.12.0 has been published that fixes this issue; monitor the Chainlit GitHub repository and PyPI package for a patched release and upgrade as soon as one is available.
  • Interim workarounds: Restrict or firewall direct network access to the Chainlit socket.io endpoint to trusted clients only; run the Chainlit process with a dedicated, least-privileged account so any forced deletion is confined to non-critical directories; monitor logs for unexpected socket.io connections or sessionId values containing path traversal sequences (../, absolute paths).

How IONIX identifies potentially affected assets

IONIX matches the following signal against data already collected when it crawled the asset; identifying the technology sends no request beyond that crawl.

  • Raw HTTP response body: <meta property="og:url" content="https://github.com/Chainlit/chainlit">

References

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How IONIX’s External Exposure Management Platform Detects and Validates
Zero-Days to Shrink MTTR

1

Map your entire attack surface (continously)

IONIX uses multi-factor discovery methods, including DNS analysis, certificate mapping, metadata inspection, and more, to automatically map every internet-facing asset across your environment. This includes cloud instances, third-party platforms, shadow IT, and even forgotten infrastructure that traditional tools miss.

2

Monitor for new CVEs

Dozens of threat intel feeds using agentic technology are continuously analyzed to detect the appearance of proof-of-concept code, exploit kits, and indicators of active targeting. IONIX goes further by applying AI to proactively evaluate whether emerging vulnerabilities are likely to be exploited, even before PoCs go public.

3

Identify Potential External Exposures

Not all CVEs matter. IONIX filters vulnerabilities by asking attacker-centric questions: Can it be reached from the internet? Does it require authentication? Is it being exploited in the wild? This dramatically reduces noise and focuses teams on threats that can actually be weaponized.

4

Create Safe, Scalable Exploit Validations

IONIX transforms real-world PoCs into safe, non-intrusive test payloads that can be run in production environments without disruption. These simulations are precisely targeted to the systems that are vulnerable, ensuring rapid validation without unnecessary load.

5

Execute Exploit Validations

By combining context about software stack, versioning, exposure status, and reachability, IONIX ensures that only the right payloads are executed against the right assets, maximizing efficiency and minimizing risk.

6

Drive Fast and Actionable Remediation

Results are routed through integrations with ticketing, SOAR, and SIEM tools. Issues are written in plain language, bundled into remediation clusters, and prioritized based on asset criticality, exploitability, and blast radius. This shortens mean time to remediation (MTTR) and empowers teams to act with confidence.

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