Focus on stitionai vulnerabilities and metrics.
Last updated: 08 Mar 2025, 23:25 UTC
This page consolidates all known Common Vulnerabilities and Exposures (CVEs) associated with stitionai. We track both calendar-based metrics (using fixed periods) and rolling metrics (using gliding windows) to give you a comprehensive view of security trends and risk evolution. Use these insights to assess risk and plan your patching strategy.
For a broader perspective on cybersecurity threats, explore the comprehensive list of CVEs by vendor and product. Stay updated on critical vulnerabilities affecting major software and hardware providers.
Total stitionai CVEs: 2
Earliest CVE date: 08 Jul 2024, 00:15 UTC
Latest CVE date: 24 Jul 2024, 16:15 UTC
Latest CVE reference: CVE-2024-40422
30-day Count (Rolling): 0
365-day Count (Rolling): 2
Calendar-based Variation
Calendar-based Variation compares a fixed calendar period (e.g., this month versus the same month last year), while Rolling Growth Rate uses a continuous window (e.g., last 30 days versus the previous 30 days) to capture trends independent of calendar boundaries.
Month Variation (Calendar): 0%
Year Variation (Calendar): 0%
Month Growth Rate (30-day Rolling): 0.0%
Year Growth Rate (365-day Rolling): 0.0%
Average CVSS: 0.0
Max CVSS: 0
Critical CVEs (≥9): 0
| Range | Count |
|---|---|
| 0.0-3.9 | 2 |
| 4.0-6.9 | 0 |
| 7.0-8.9 | 0 |
| 9.0-10.0 | 0 |
These are the five CVEs with the highest CVSS scores for stitionai, sorted by severity first and recency.
The snapshot_path parameter in the /api/get-browser-snapshot endpoint in stitionai devika v1 is susceptible to a path traversal attack. An attacker can manipulate the snapshot_path parameter to traverse directories and access sensitive files on the server. This can potentially lead to unauthorized access to critical system files and compromise the confidentiality and integrity of the system.
A stored Cross-Site Scripting (XSS) vulnerability exists in the stitionai/devika chat feature, allowing attackers to inject malicious payloads into the chat input. This vulnerability is due to the lack of input validation and sanitization on both the frontend and backend components of the application. Specifically, the application fails to sanitize user input in the chat feature, leading to the execution of arbitrary JavaScript code in the context of the user's browser session. This issue affects all versions of the application. The impact of this vulnerability includes the potential for stolen credentials, extraction of sensitive information from chat logs, projects, and other data accessible through the application.