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关键词追踪：prompt injection
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最近一次命中来自 LM：Prompt Injection in Automated Résumé Screening with Large Language Models: Single and Multi-Injection Settings
2026-06-15
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2026-06-16
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2026-06-17
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2026-06-18
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2026-06-19
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2026-06-20
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2026-06-21
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2026-06-25
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2026-06-26
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2026-06-27
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2026-06-28
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命中明细
按日期回看匹配到这个关键词的论文标题，并保留来源 feed 信息。
2026-06-26
Prompt Injection in Automated Résumé Screening with Large Language Models: Single and Multi-Injection Settings
Large language models (LLMs) are increasingly used to screen and rank job applicants, creating incentives for candidates to strategically manipulate algorithmic hiring systems. We…
MIRROR: Novelty-Constrained Memory-Guided MCTS Red-Teaming for Agentic RAG
Multimodal agentic retrieval-augmented generation (RAG) systems expand the attack surface beyond prompt injection to include text poisoning, image injection, direct-query attacks,…
2026-06-25
How Reliable Is Your Jailbreak Judge? Calibration and Adversarial Robustness of Automated ASR Scoring
Almost every paper on LLM jailbreaks and prompt injection reports an attack-success rate (ASR), and that number is assigned not by people but by an automated judge: either a safet…
AI Snitches Get Glitches: Towards Evading Agentic Surveillance
To better assist users with completing challenging tasks, AI agents mediate communications, access data, and interact with different APIs. Many employers (and even nation-states)…
2026-06-23
GIF: Locally Sound Geometric Information Flow Control for LLMs
Large language models increasingly mediate interactions between sensitive data, untrusted inputs, and privileged actions in agentic systems, creating security and privacy risks. T…
2026-06-18
CodeSentinel: A Three-Layer Defense Against Indirect Prompt Injection in Code Contexts
Code large language models increasingly retrieve external code context from repositories, documentation, issue threads, and coding-agent environments, creating an indirect prompt-…
2026-06-16
KVEraser: Learning to Steer KV Cache for Efficient Localized Context Erasing
Post-hoc context erasing over the KV cache is challenging because a local edit has a global consequence: once a span has been processed, its influence propagates into the cached s…
2026-06-12
Who Pays the Price? Stakeholder-Centric Prompt Injection Benchmarking for Real-world Web Agents
Web agents driven by large language models (LLMs) are increasingly deployed in real-world environments, where they operate over untrusted web content and execute actions with dire…
No Hidden Prompts Needed! You Can Game AI Peer Review with Presentation-Only Revisions
As AI-generated reviews move from experimental tools into peer-review infrastructure, most robustness concerns have focused on explicit attacks such as hidden instructions and pro…
Nous: An Attempt to Extract and Inject the Cognition Behind Prediction-Market Behavior
As LLM agents proliferate in prediction markets and collective decision-making, they risk a cognitive monoculture: agents built on shared foundation models produce correlated fore…
2026-06-11
External Experience Serving in Production LLM Systems: A Deployment-Oriented Study of Quality-Cost Trade-offs
Production LLM systems accumulate reusable operational experience, but the practical deployment issue is not merely whether such experience can help. It is how different serving s…
2026-06-10
Toward Secure LLM Agents: Threat Surfaces, Attacks, Defenses, and Evaluation
Large language model (LLM) agents are rapidly moving from conversational interfaces to software components that plan, invoke tools, maintain memory, and act on external environmen…
Training LLMs to Enforce Multi-Level Instruction Hierarchies via Gravity-Weighted Direct Preference Optimization
Production LLMs receive instructions from sources with very different levels of trust, yet attend to every token with uniform architectural privilege. This is the structural vulne…
2026-06-09
Brain-Prompt Injection: A Route-Safety Audit for BCI-LLM Agents
BCI-to-agent pipelines turn decoded neural activity into an authorization channel for tool-use agents, exposing a new attack surface we call \emph{brain-prompt injection}: signal-…
PRISM: Recovering Instruction Sets from Language Model Activations
As LLMs are deployed as agents, reliable monitoring requires knowing not only what they output, but which instructions are steering their behavior. This is difficult when models i…
2026-06-05
GuardNet: Ensemble Strategies of Shallow Neural Networks for Robust Prompt Injection and Jailbreak Detection
Large Language Models (LLMs) have transformed natural language processing, but they remain vulnerable to Prompt Injection (PI) and Jailbreak (JB) attacks. In addition, benchmark e…
2026-06-04
What If Prompt Injection Never Left? Exploring Cross-Session Stored Prompt Injection in Agentic Systems
Modern agentic systems transform LLMs from session-bounded assistants into stateful systems that persist and evolve shared world state across sessions through memories, filesystem…
Caught in the Act(ivation): Toward Pre-Output and Multi-Turn Detection of Credential Exfiltration by LLM Agents
LLM agents often place sensitive credentials in the same context window as untrusted retrieved content, creating a direct path for indirect prompt injection to induce credential e…
From Untrusted Input to Trusted Memory: A Systematic Study of Memory Poisoning Attacks in LLM Agents
Memory is a core component of AI agents, enabling them to accumulate knowledge across interactions and improve performance. However, persistent memory introduces the risk of memor…
2026-06-03
From Control Boundary to Insurance Claim: Reconstructing AI-Mediated Losses Through the CER Framework
AI losses that arise through an insured organization's generative or agentic AI system require state reconstruction, not merely event reconstruction, because the relevant state ch…
2026-06-02
AgentRedBench: Dynamic Redteaming and Integration-Aware Defense for LLM Agents over SaaS Integrations
Indirect prompt injection in tool-use agents is a concrete production threat: LLM agents read from integrations (third-party services such as Gmail, Salesforce, or Jira accessed t…
2026-05-28
LACUNA: Safe Agents as Recursive Program Holes
LLM agents increasingly act by writing code, yet a split persists between the runtime that drives the agent and the code the model writes. The runtime owns the loop, context, and…
2026-05-27
Prompt Injection Detection is Regime-Dependent: A Deployment-Aware Evaluation with Interpretable Structural Signals
Prompt injection poses a critical threat to the safe deployment of large language models, yet existing detection approaches are typically evaluated under limited settings that do…
2026-05-26
How Agentic AI Coding Assistants Become the Attacker's Shell
Agentic AI coding assistants can edit files, run commands, and access the internet on behalf of developers. However, their reliance on unvetted external artifacts introduces a new…
2026-05-19
An Empirical Study of Privacy Leakage Chains via Prompt Injection in Black-Box Chatbot Environments
LLM-based chatbot agents increasingly process user requests by combining natural-language reasoning with external tools such as web browsing. These capabilities improve usability,…
Overeager Coding Agents: Measuring Out-of-Scope Actions on Benign Tasks
Coding agents now run autonomously with shell, file, and network privileges. When a user issues a benign request, the agent sometimes does more than asked: it deletes unrelated fi…
2026-05-14
Sleeper Channels and Provenance Gates: Persistent Prompt Injection in Always-on Autonomous AI Agents
Always-on AI agents (OpenClaw, Hermes Agent) run as a single persistent process under the owner's identity, folding messaging, memory, self-authored skills, scheduling, and shell…
2026-05-12
RUBEN: Rule-Based Explanations for Retrieval-Augmented LLM Systems
This paper demonstrates RUBEN, an interactive tool for discovering minimal rules to explain the outputs of retrieval-augmented large language models (LLMs) in data-driven applicat…
2026-05-08
Constraining Host-Level Abuse in Self-Hosted Computer-Use Agents via TEE-Backed Isolation
Self-hosted computer-use agents (SHCUAs), such as OpenClaw, combine natural-language interaction with direct access to host-side resources, including browsers, files, scripts, sys…
2026-04-14
Detecting Safety Violations Across Many Agent Traces
To identify safety violations, auditors often search over large sets of agent traces. This search is difficult because failures are often rare, complex, and sometimes even adversa…
ClawGuard: A Runtime Security Framework for Tool-Augmented LLM Agents Against Indirect Prompt Injection
Tool-augmented Large Language Model (LLM) agents have demonstrated impressive capabilities in automating complex, multi-step real-world tasks, yet remain vulnerable to indirect pr…