activity
20242026
most citedMALADE: Orchestration of LLM-powered Agents with Retrieval Augmented Generation for Pharmacovigilance

6 citations · 6 across the 1 of their papers we have counts for

collaborators

8 papers

cs.CR2026

Agent Security is a Systems Problem

Mihai Christodorescu, Earlence Fernandes, Ashish Hooda +11

We take the position that agent security must be approached as a systems problem: the AI model powering the agent must be treated as an untrusted component, and security invariants…

cs.CR2026

Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions

Sarthak Choudhary, Atharv Singh Patlan, Nils Palumbo +3

We present Sparse Backdoor, a supply-chain attack that plants a provably undetectable backdoor in pre-trained image classifiers, including convolutional networks and Vision Transfo…

cs.CR2026

Dependency-Aware Privacy for Multi-turn Agents

Divyam Anshumaan, Sarthak Choudhary, Nils Palumbo +1

LLM agents release private data across multi-service interactions. Existing prompt sanitizers based on metric differential privacy treat each release independently, so adversaries…

cs.CR2026

Formal Policy Enforcement for Real-World Agentic Systems

Nils Palumbo, Sarthak Choudhary, Jihye Choi +3

Security policy enforcement in contemporary agentic systems predominantly consists of embedding natural-language policies within an agent's system prompt and delegating compliance…

cs.CR2025

How Not to Detect Prompt Injections with an LLM

Sarthak Choudhary, Divyam Anshumaan, Nils Palumbo +1

LLM-integrated applications and agents are vulnerable to prompt injection attacks, where adversaries embed malicious instructions within seemingly benign input data to manipulate t…

cs.CR2025

Through the Stealth Lens: Attention-Aware Defenses Against Poisoning in RAG

Sarthak Choudhary, Nils Palumbo, Ashish Hooda +2

Retrieval-augmented generation (RAG) systems are vulnerable to attacks that inject poisoned passages into the retrieved context, even at low corruption rates. We show that existing…