INCIDENT ANALYSIS REPORT: PROJECT “CHAINLEAK” Status: CRITICAL | Incident ID: 2026-CHL-01

Daily Threat Intel by CyberDudeBivash
Zero-days, exploit breakdowns, IOCs, detection rules & mitigation playbooks.

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1. Executive Summary

An unauthenticated or low-privilege attacker can weaponize a vulnerability chain (collectively dubbed “ChainLeak”) in the Chainlit AI framework to bypass security boundaries and achieve Full Cloud Account Takeover. By combining an Arbitrary File Read (CVE-2026-22218) with Server-Side Request Forgery (SSRF) (CVE-2026-22219), attackers can exfiltrate sensitive environment variables, local databases, and temporary cloud IAM credentials.

Bivash’s Bottom Line: This isn’t just an “AI bug” – it is a catastrophic infrastructure failure. If your chatbot sits on an EC2 instance with IMDSv1 enabled, you are essentially leaving the keys to your entire AWS kingdom in a public-facing chat window.

2. Technical Vulnerability Breakdown

The vulnerability resides in the backend Element management system of Chainlit, which handles files, images, and custom UI components.

CVE-2026-22218: The “Entry” (Arbitrary File Read)

Vulnerability Type: Path Traversal / Arbitrary File Read.
Mechanism: The /project/element update flow fails to sanitize the path property for custom elements.
Impact: An attacker can point this path to sensitive system files like /proc/self/environ or chainlit.db.
Result: Exposure of CHAINLIT_AUTH_SECRET (allowing session forgery) and hardcoded API keys.

CVE-2026-22219: The “Pivot” (SSRF)

Vulnerability Type: Server-Side Request Forgery (SSRF).
Mechanism: When using the SQLAlchemy data layer, the url property for elements is fetched by the server without validation.
Impact: The server can be forced to make requests to internal services or the Cloud Metadata Service (169.254.169.254).
Result: Extraction of temporary IAM Role credentials, enabling lateral movement into S3, RDS, and other cloud services.

3. The “ChainLeak” Attack Vector

Phase	Action	Tactical Goal
I. Recon	Identify public-facing Chainlit instances (port 8000/8080).	Find target footprint.
II. File Exfil	Request `/proc/self/environ` via a custom JSX element.	Harvest Environment Variables (AWS Keys, DB URLs).
III. Metadata Probe	Inject `http://169.254.169.254/latest/meta-data/iam/security-credentials/` into the URL field.	Extract temporary cloud identity tokens.
IV. Cloud Takeover	Authenticate to AWS/Azure using stolen tokens.	Complete infrastructure compromise.

4. Operational Risk Assessment

Data Integrity: HIGH. Attackers can read/write to the SQL databases used by the AI application.
Confidentiality: CRITICAL. Exposure of every user conversation, prompt, and system instruction.
Availability: HIGH. Attackers can delete cloud resources or modify AI agents to produce malicious output.

5. Remediation & Hardening (Immediate Action Required)

Immediate Fix

Update Chainlit to version 2.9.4 or higher. The patch implements strict validation for both path and url fields in the Element class.

Defensive Hardening (CyberDudeBivash’s Pro-Tips)

IMDSv2 Enforcement: On AWS, strictly disable IMDSv1. IMDSv2 requires a session token, which significantly mitigates the impact of SSRF.
Environment Secret Rotation: If you were running an older version, assume your CHAINLIT_AUTH_SECRET and OPENAI_API_KEY are compromised. Rotate them immediately.
Network Segmentation: Deploy your AI backend in a Private Subnet and use a Reverse Proxy (like Nginx) or a WAF to filter malicious /project/element traffic.
WAF Signature: Block any incoming POST requests to /project/element that contain suspicious strings like 169.254.169.254 or pathTraversal characters (../).Since the attack relies on specific HTTP parameters in the /project/element endpoint, we target the Path Traversal (Arbitrary File Read) and Outbound Calls (SSRF). 1. Detection Strategy: Path Traversal (CVE-2026-22218)The goal is to catch attempts to read critical system files like /etc/passwd or /proc/self/environ via the path parameter.Snort 3 RuleCode snippetalert http $EXTERNAL_NET any -> $HTTP_SERVERS any ( msg:"CyberDudeBivash - Chainlit Arbitrary File Read Attempt (CVE-2026-22218)"; flow:established,to_server; http_uri; content:"/project/element",fast_pattern; http_client_body; pcre:"/\"path\"\s*:\s*\"(\.\.\/|\/etc\/|\/proc\/)/i"; metadata:policy security-content, service http; reference:cve,2026-22218; classtype:web-application-attack; sid:1000001; rev:1; ) Suricata RuleCode snippetalert http $EXTERNAL_NET any -> $HTTP_SERVERS any ( msg:"CyberDudeBivash - Chainlit Arbitrary File Read Attempt (CVE-2026-22218)"; flow:established,to_server; http.uri; content:"/project/element"; http.request_body; pcre:"/\"path\"\s*:\s*\"(\.\.\/|\/etc\/|\/proc\/)/i"; reference:cve,2026-22218; classtype:web-application-attack; sid:2000001; rev:1; ) 2. Detection Strategy: SSRF to Cloud Metadata (CVE-2026-22219)This rule flags requests to the /project/element endpoint where the url parameter contains the AWS/Cloud metadata IP or local loopback addresses.Snort 3 RuleCode snippetalert http $EXTERNAL_NET any -> $HTTP_SERVERS any ( msg:"CyberDudeBivash - Chainlit SSRF Metadata Exfiltration Attempt (CVE-2026-22219)"; flow:established,to_server; http_uri; content:"/project/element",fast_pattern; http_client_body; pcre:"/\"url\"\s*:\s*\"(http|https):\/\/169\.254\.169\.254/i"; metadata:policy security-content, service http; reference:cve,2026-22219; classtype:web-application-attack; sid:1000002; rev:1; ) Suricata RuleCode snippetalert http $EXTERNAL_NET any -> $HTTP_SERVERS any ( msg:"CyberDudeBivash - Chainlit SSRF Metadata Exfiltration Attempt (CVE-2026-22219)"; flow:established,to_server; http.uri; content:"/project/element"; http.request_body; pcre:"/\"url\"\s*:\s*\"(http|https):\/\/169\.254\.169\.254/i"; reference:cve,2026-22219; classtype:web-application-attack; sid:2000002; rev:1; ) Implementation Guidance (The “CyberDudeBivash” Way)
Fast Pattern Matching: I’ve used /project/element as the fast pattern to ensure the engine doesn’t waste CPU cycles unless that specific endpoint is hit.
Regex Flexibility: The PCRE (Regex) account for variations in JSON spacing (\s*), which attackers often use to bypass poorly written rules.
False Positives: These rules are quite targeted. However, if your application legitimately allows users to point to internal URLs (rare for a chatbot framework), you may need to whitelist specific internal source IPs.

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