41 citations · 48 across the 16 of their papers we have counts for
16 papers
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…
ReCon: A Resource-Constrained Benchmark for LLM-Based Cybersecurity Compliance Across Ingestion and Retrieval Pipelines
Rohit Negi, Rishik Jain, Soumyo V Chakarborty +2
With the increasingly aggressive cyber threat landscape for governments, businesses, and institutions, as information and/or cybersecurity implementations are increasingly under sc…
AI-Assisted Cybersecurity Policy Assessment: Evidence Grounding, Coverage Gaps, and Implications for Security Management
Bikash Saha, Sandeep Kumar Shukla
Cybersecurity policy assessment requires reviewers to determine whether organizational policies adequately address established security controls and to identify areas where further…
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…
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…
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…
AURA: A Multi-Agent Intelligence Framework for Knowledge-Enhanced Cyber Threat Attribution
Nanda Rani, Sandeep Kumar Shukla
Effective attribution of Advanced Persistent Threats (APTs) increasingly hinges on the ability to correlate behavioral patterns and reason over complex, varied threat intelligence…
MalGEN: A Testbed for Modeling and Evaluating Malware Behaviors
Bikash Saha, Sandeep Kumar Shukla
Modern cybersecurity requires systematic ways to evaluate how detection systems respond to evolving and previously unseen attack behaviors. Existing malware repositories largely ca…
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…
Generative AI in Financial Institution: A Global Survey of Opportunities, Threats, and Regulation
Bikash Saha, Nanda Rani, Sandeep Kumar Shukla
Generative Artificial Intelligence (GenAI) is rapidly reshaping the global financial landscape, offering unprecedented opportunities to enhance customer engagement, automate comple…
MaLAware: Automating the Comprehension of Malicious Software Behaviours using Large Language Models (LLMs)
Bikash Saha, Nanda Rani, Sandeep Kumar Shukla
Current malware (malicious software) analysis tools focus on detection and family classification but fail to provide clear and actionable narrative insights into the malignant acti…
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…
Automated Classification of Cybercrime Complaints using Transformer-based Language Models for Hinglish Texts
Nanda Rani, Divyanshu Singh, Bikash Saha +1
The rise in cybercrime and the complexity of multilingual and code-mixed complaints present significant challenges for law enforcement and cybersecurity agencies. These organizatio…
A Comprehensive Survey of Advanced Persistent Threat Attribution: Taxonomy, Methods, Challenges and Open Research Problems
Nanda Rani, Bikash Saha, Sandeep Kumar Shukla
Advanced Persistent Threat (APT) attribution is a critical challenge in cybersecurity and implies the process of accurately identifying the perpetrators behind sophisticated cyber…
Chasing the Shadows: TTPs in Action to Attribute Advanced Persistent Threats
Nanda Rani, Bikash Saha, Vikas Maurya +1
The current state of Advanced Persistent Threats (APT) attribution primarily relies on time-consuming manual processes. These include mapping incident artifacts onto threat attribu…
TTPXHunter: Actionable Threat Intelligence Extraction as TTPs from Finished Cyber Threat Reports
Nanda Rani, Bikash Saha, Vikas Maurya +1
Understanding the modus operandi of adversaries aids organizations in employing efficient defensive strategies and sharing intelligence in the community. This knowledge is often pr…