Cracking the Sandbox: Testing LLM Security with SANDBOXESCAPEBENCH
The introduction of SANDBOXESCAPEBENCH marks a significant leap in evaluating the security risks posed by large language models (LLMs) in sandbox environments. This benchmark demonstrates how these…
Read the full articleYou might also wanna read
Benchmarking Frontier LLMs on Real-World CVE Patching: Mixed Results and Methodological Challenges
Benchmarking LLMs on real-world CVE patching
Deno Sandbox: Secure Environment for Running LLM-Generated Code with API Access
Instant Linux microVMs with defense-in-depth security for running untrusted code.
deno.com·5mo ago
Where to Run the LLM Agent Harness: Sandbox vs. Local Architecture Tradeoffs
Two architectures for running agent harnesses, the tradeoffs between them, and how we make skills and memories work when the harness isn't l
mendral.com·2mo ago
Security Risks of Malicious Backdoors in Large Language Models
LLM security is a critical risk for open-weight models. Learn how malicious backdoors are easily fine-tuned into AI agents to execute harmfu
pub.aimind.so·11mo ago
Security Alert: Litellm Versions 1.82.7 and 1.82.8 on PyPI Compromised - Sandboxing Limitations Discussed
> If the whole point of sandboxing is to not trust the software, it doesn't make sense for the software to do the sandboxing.
news.ycombinator.com·3mo ago
Security Analysis: AI Agent Frameworks' Code Execution Vulnerabilities and WASM Sandbox Solution
Contribute to amlalabs/amla-sandbox development by creating an account on GitHub.
github.com·5mo ago
Comments
Sign in to join the conversation.
No comments yet. Be the first.