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cs.CR2026
Evaluating LLM-Generated Obfuscated XSS Payloads for Machine Learning-Based Detection
Divyesh Gabbireddy, Suman Saha
Cross-site scripting (XSS) remains a persistent web security vulnerability, especially because obfuscation can change the surface form of a malicious payload while preserving its b…
cs.CR2026
SecureCodeRL: Security-Aware Reinforcement Learning for Code Generation with Partial-Credit Rewards
Suryansh Singh Sijwali, Suman Saha
Large Language Models (LLMs) can generate plausible code, but in settings that require exact stdin/stdout behavior they frequently produce programs that compile yet fail tests, and…
cs.CR2026
Improving LLM-Assisted Secure Code Generation through Retrieval-Augmented-Generation and Multi-Tool Feedback
Vidyut Sriram, Sawan Pandita, Achintya Lakshmanan +2
Large Language Models (LLMs) can generate code but often introduce security vulnerabilities, logical inconsistencies, and compilation errors. Prior work demonstrates that LLMs bene…