Focus on lightningai vulnerabilities and metrics.
Last updated: 08 Mar 2025, 23:25 UTC
This page consolidates all known Common Vulnerabilities and Exposures (CVEs) associated with lightningai. 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 lightningai CVEs: 3
Earliest CVE date: 23 Dec 2021, 18:15 UTC
Latest CVE date: 06 Jun 2024, 18:15 UTC
Latest CVE reference: CVE-2024-5452
30-day Count (Rolling): 0
365-day Count (Rolling): 1
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: 5.6
Max CVSS: 10.0
Critical CVEs (≥9): 1
| Range | Count |
|---|---|
| 0.0-3.9 | 1 |
| 4.0-6.9 | 1 |
| 7.0-8.9 | 0 |
| 9.0-10.0 | 1 |
These are the five CVEs with the highest CVSS scores for lightningai, sorted by severity first and recency.
A remote code execution (RCE) vulnerability exists in the lightning-ai/pytorch-lightning library version 2.2.1 due to improper handling of deserialized user input and mismanagement of dunder attributes by the `deepdiff` library. The library uses `deepdiff.Delta` objects to modify application state based on frontend actions. However, it is possible to bypass the intended restrictions on modifying dunder attributes, allowing an attacker to construct a serialized delta that passes the deserializer whitelist and contains dunder attributes. When processed, this can be exploited to access other modules, classes, and instances, leading to arbitrary attribute write and total RCE on any self-hosted pytorch-lightning application in its default configuration, as the delta endpoint is enabled by default.
Code Injection in GitHub repository pytorchlightning/pytorch-lightning prior to 1.6.0.
pytorch-lightning is vulnerable to Deserialization of Untrusted Data