activity
20242026
most citedTracking Real-time Anomalies in Cyber-Physical Systems Through Dynamic Behavioral Analysis

3 citations · 13 across the 27 of their papers we have counts for

collaborators

31 papers

cs.RO2026

CLARO: Clutter Aware Robot Orchestrator for Open-Vocabulary Grasping using VLM Agents

Sungsu Kim, Vineet Bhat, Prashanth Krishnamurthy +2

Robots that follow natural-language instructions unlock a wide range of autonomous applications in households, warehouses, and labs. Real-world environments are diverse and often h…

cs.CR2026

Which Image Property Carries the Jailbreak? A Controlled Dissection of Image-to-Text Jailbreaks

Boyuan Chen, Yehia Dawoud, Hailemariam Mersha +4

Image-to-text jailbreaks place harmful intent in text, image content, or the relationship between them. We examine image-side factors across four published attack families on a 313…

cs.SD2026

Where Does the Audio Jailbreak Live? A Controlled Frequency-Depth Audit of AdvWave-P on Qwen2-Audio

Boyuan Chen, Minseok Kim, Sohaila Abdulsattar +4

We audit frequency and decoder-depth claims for AdvWave-P, an additive audio jailbreak, on Qwen2-Audio. The protocol masks frequency components of the perturbation in the short-tim…

cs.CR2026

How Do LLM Agents Actually Get the Flag? Trace-Level Provenance for Agentic Offensive Security Evaluation

Kimberly Milner, Minghao Shao, Nanda Rani +8

Capture-the-Flag (CTF) benchmarks are widely used to assess the offensive security capabilities of autonomous language-model agents. Evaluations rely on shallow binary judgments or…

eess.SY2026

Sandbox-Enabled Digital Twin for Cyber-Physical Systems

Meet Udeshi, Md Raz, Prashanth Krishnamurthy +2

Firmware/software in cyber-physical system (CPS) embedded devices/controllers can have vulnerabilities stemming from multiple sources such as weak security practices, outdated libr…

cs.CR2026

Long-Term and Short-Term Transistor Aging in Deep Neural Networks: Impact and Mitigation

Alireza Sarmadi, Virinchi Roy Surabhi, Prashanth Krishnamurthy +3

Deep neural networks (DNNs) are used in a variety of real-world applications including, for example, image classification and speech recognition. The inference accuracy of DNN impl…

cs.AI2026

RESCORE: LLM-Driven Simulation Recovery in Control Systems Research Papers

Vineet Bhat, Shiqing Wei, Ali Umut Kaypak +3

Reconstructing numerical simulations from control systems research papers is often hindered by underspecified parameters and ambiguous implementation details. We define the task of…

cs.SE2026

AI In Cybersecurity Education -- Scalable Agentic CTF Design Principles and Educational Outcomes

Haoran Xi, Minghao Shao, Kimberly Milner +11

Large language models are rapidly changing how learners acquire and demonstrate cybersecurity skills. However, when human--AI collaboration is allowed, educators still lack validat…

cs.CR2026

Safeguarding LLMs Against Misuse and AI-Driven Malware Using Steganographic Canaries

Md Raz, Venkata Sai Charan Putrevu, Meet Udeshi +3

AI-powered malware increasingly exploits cloud-hosted generative-AI services and large language models (LLMs) as analysis engines for reconnaissance and code generation. Simultaneo…

cs.CR2026

CTFExplorer: Evaluating LLM Offensive Agents Through Multi-Target Web CTF Benchmarking

Nanda Rani, Kimberly Milner, Minghao Shao +9

Existing benchmarks for LLM-based offensive security agents use isolated, single-target setups with a known vulnerable service and fixed objective. They measure exploitation effect…

cs.CV2025

BOP-ASK: Object-Interaction Reasoning for Vision-Language Models

Vineet Bhat, Sungsu Kim, Valts Blukis +6

Vision Language Models (VLMs) have achieved impressive performance on spatial reasoning benchmarks, yet these evaluations mask critical weaknesses in understanding object interacti…

cs.SE2025

From Trace to Line: LLM Agent for Real-World OSS Vulnerability Localization

Haoran Xi, Minghao Shao, Brendan Dolan-Gavitt +2

Large language models show promise for vulnerability discovery, yet prevailing methods inspect code in isolation, struggle with long contexts, and focus on coarse function- or file…

cs.CR2025

Binary Diff Summarization using Large Language Models

Meet Udeshi, Venkata Sai Charan Putrevu, Prashanth Krishnamurthy +4

Security of software supply chains is necessary to ensure that software updates do not contain maliciously injected code or introduce vulnerabilities that may compromise the integr…

cs.CR2025

Ransomware 3.0: Self-Composing and LLM-Orchestrated

Md Raz, Meet Udeshi, P. V. Sai Charan +3

Using automated reasoning, code synthesis, and contextual decision-making, we introduce a new threat that exploits large language models (LLMs) to autonomously plan, adapt, and exe…

cs.CR2025

SCAMPER -- Synchrophasor Covert chAnnel for Malicious and Protective ERrands

Prashanth Krishnamurthy, Ramesh Karri, Farshad Khorrami

We note that constituent fields (notably the fraction-of-seconds timestamp field) in the data payload structure of the synchrophasor communication protocol (IEEE C37.118 standard)…

cs.CR2025

An Orchestrated Sandbox for Side-Channel Analysis of Cyber-Physical Systems Malware

Meet Udeshi, Venkata Sai Charan Putrevu, Prashanth Krishnamurthy +2

Embedded devices powering cyber-physical systems (CPS) are increasingly internet-exposed, placing critical infrastructure under active threat. Dynamic analysis of embedded malware…

cs.CR2025

Towards Effective Offensive Security LLM Agents: Hyperparameter Tuning, LLM as a Judge, and a Lightweight CTF Benchmark

Minghao Shao, Nanda Rani, Kimberly Milner +9

Recent advances in LLM agentic systems have improved the automation of offensive security tasks, particularly for Capture the Flag (CTF) challenges. We systematically investigate t…

cs.RO2025

MapleGrasp: Mask-guided Feature Pooling for Language-driven Efficient Robotic Grasping

Vineet Bhat, Naman Patel, Prashanth Krishnamurthy +2

Robotic manipulation of unseen objects via natural language commands remains challenging. Language driven robotic grasping (LDRG) predicts stable grasp poses from natural language…

cs.CR2025

CRAKEN: Cybersecurity LLM Agent with Knowledge-Based Execution

Minghao Shao, Haoran Xi, Nanda Rani +9

Large Language Model (LLM) agents can automate cybersecurity tasks and can adapt to the evolving cybersecurity landscape without re-engineering. While LLM agents have demonstrated…

cs.RO2025

3D CAVLA: Leveraging Depth and 3D Context to Generalize Vision Language Action Models for Unseen Tasks

Vineet Bhat, Yu-Hsiang Lan, Prashanth Krishnamurthy +2

Robotic manipulation in 3D requires effective computation of N degree-of-freedom joint-space trajectories that enable precise and robust control. To achieve this, robots must integ…

cs.CR2025

Enabling Deep Visibility into VxWorks-Based Embedded Controllers in Cyber-Physical Systems for Anomaly Detection

Prashanth Krishnamurthy, Ramesh Karri, Farshad Khorrami

We propose the DIVER (Defensive Implant for Visibility into Embedded Run-times) framework for real-time deep visibility into embedded control devices in cyber-physical systems (CPS…

cs.AI2025★ 1 cited

D-CIPHER: Dynamic Collaborative Intelligent Multi-Agent System with Planner and Heterogeneous Executors for Offensive Security

Meet Udeshi, Minghao Shao, Haoran Xi +9

Large Language Models (LLMs) have been used in cybersecurity such as autonomous security analysis or penetration testing. Capture the Flag (CTF) challenges serve as benchmarks to a…

cs.CR2025

Real-Time Multi-Modal Subcomponent-Level Measurements for Trustworthy System Monitoring and Malware Detection

Farshad Khorrami, Ramesh Karri, Prashanth Krishnamurthy

With increasingly sophisticated cyber-adversaries able to access a wider repertoire of mechanisms to implant malware such as ransomware, CPU/GPU keyloggers, and stealthy kernel roo…

cs.CR2025

SHIELD: A Host-Independent Framework for Ransomware Detection using Deep Filesystem Features

Md Raz, Venkata Sai Charan Putrevu, Prashanth Krishnamurthy +2

Ransomware's escalating sophistication necessitates tamper-resistant, off-host detection solutions that capture deep disk activity beyond the reach of a compromised operating syste…