Slice: SAST + LLM Interprocedural Context Extractor
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Articles tagged with: #sast
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SaMOSA: Sandbox for Malware Orchestration and Side-Channel Analysis
arXiv:2508.14261v1 Announce Type: new Abstract: Cyber-attacks on operational technology (OT) and cyber-physical systems (CPS) have increased tremendously in recent years with the proliferation of malware targeting Linux-based embedded devices of OT and CPS systems. Comprehensive malware detection requires dynamic analysis of execution behavior in addition to static analysis of binaries. Safe execution of malware in a manner that captures relevant behaviors via side-channels requires a sandbox...
CodeRabbit's Production Servers RCE Vulnerability Enables Write Access on 1M Repositories
A critical remote code execution (RCE) vulnerability in CodeRabbit's production infrastructure that provided unauthorized access to over one million code repositories, including private ones. The vulnerability, discovered in December 2024 and responsibly disclosed in January 2025, exploited the platform's static analysis tool integration to leak sensitive API credentials and gain write access to GitHub repositories
Hexora: Static analysis of malicious Python code
I've released a new tool that helps to audit Python dependencies and highlight potentially malicious parts of the code. I'm looking for a feedback and suggestions for new rules. submitted by /u/rushter_ [link] [comments]
Enhancing GraphQL Security by Detecting Malicious Queries Using Large Language Models, Sentence Transformers, and Convolutional Neural Networks
arXiv:2508.11711v1 Announce Type: new Abstract: GraphQL's flexibility, while beneficial for efficient data fetching, introduces unique security vulnerabilities that traditional API security mechanisms often fail to address. Malicious GraphQL queries can exploit the language's dynamic nature, leading to denial-of-service attacks, data exfiltration through injection, and other exploits. Existing solutions, such as static analysis, rate limiting, and general-purpose Web Application Firewalls,...
Code Vulnerability Detection Across Different Programming Languages with AI Models
arXiv:2508.11710v1 Announce Type: new Abstract: Security vulnerabilities present in a code that has been written in diverse programming languages are among the most critical yet complicated aspects of source code to detect. Static analysis tools based on rule-based patterns usually do not work well at detecting the context-dependent bugs and lead to high false positive rates. Recent developments in artificial intelligence, specifically the use of transformer-based models like CodeBERT and...
Effective SAST automation to improve SDLC
What ways we can maximize the results with better outcome and eliminate fasle positives and also is there a way we simulate the findings, that helps Triage the vulnerability found through sast faster? submitted by /u/jyoswap [link] [comments]