Saved in:
| Main Authors: | Belkhiter, Yannis, Zizzo, Giulio, Maffeis, Sergio |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.06835 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Breaking MCP with Function Hijacking Attacks: Novel Threats for Function Calling and Agentic Models
by: Belkhiter, Yannis, et al.
Published: (2026)
by: Belkhiter, Yannis, et al.
Published: (2026)
Elevating Defenses: Bridging Adversarial Training and Watermarking for Model Resilience
by: Thakkar, Janvi, et al.
Published: (2023)
by: Thakkar, Janvi, et al.
Published: (2023)
Blue Teaming Function-Calling Agents
by: Dolcetti, Greta, et al.
Published: (2026)
by: Dolcetti, Greta, et al.
Published: (2026)
Segment-Level Coherence for Robust Harmful Intent Probing in LLMs
by: He, Xuanli, et al.
Published: (2026)
by: He, Xuanli, et al.
Published: (2026)
ChineseHarm-Bench: A Chinese Harmful Content Detection Benchmark
by: Liu, Kangwei, et al.
Published: (2025)
by: Liu, Kangwei, et al.
Published: (2025)
Deep Research Brings Deeper Harm
by: Chen, Shuo, et al.
Published: (2025)
by: Chen, Shuo, et al.
Published: (2025)
Different Paths to Harmful Compliance: Behavioral Side Effects and Mechanistic Divergence Across LLM Jailbreaks
by: Kabir, Md Rysul, et al.
Published: (2026)
by: Kabir, Md Rysul, et al.
Published: (2026)
Jailbreaking Commercial Black-Box LLMs with Explicitly Harmful Prompts
by: Zhang, Chiyu, et al.
Published: (2025)
by: Zhang, Chiyu, et al.
Published: (2025)
Expected Harm: Rethinking Safety Evaluation of (Mis)Aligned LLMs
by: Chen, Yen-Shan, et al.
Published: (2026)
by: Chen, Yen-Shan, et al.
Published: (2026)
CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning
by: Yi, Biao, et al.
Published: (2025)
by: Yi, Biao, et al.
Published: (2025)
Automatic Pseudo-Harmful Prompt Generation for Evaluating False Refusals in Large Language Models
by: An, Bang, et al.
Published: (2024)
by: An, Bang, et al.
Published: (2024)
Helpful or Harmful? Exploring the Efficacy of Large Language Models for Online Grooming Prevention
by: Prosser, Ellie, et al.
Published: (2024)
by: Prosser, Ellie, et al.
Published: (2024)
HarmRLVR: Weaponizing Verifiable Rewards for Harmful LLM Alignment
by: Liu, Yuexiao, et al.
Published: (2025)
by: Liu, Yuexiao, et al.
Published: (2025)
Safety Anchor: Defending Harmful Fine-tuning via Geometric Bottlenecks
by: Lu, Guoxin, et al.
Published: (2026)
by: Lu, Guoxin, et al.
Published: (2026)
RealHarm: A Collection of Real-World Language Model Application Failures
by: Jeune, Pierre Le, et al.
Published: (2025)
by: Jeune, Pierre Le, et al.
Published: (2025)
Step-Tagging: Toward controlling the generation of Language Reasoning Models through step monitoring
by: Belkhiter, Yannis, et al.
Published: (2025)
by: Belkhiter, Yannis, et al.
Published: (2025)
Latent Fusion Jailbreak: Blending Harmful and Harmless Representations to Elicit Unsafe LLM Outputs
by: Xing, Wenpeng, et al.
Published: (2025)
by: Xing, Wenpeng, et al.
Published: (2025)
TRACES: Tagging Reasoning Steps for Adaptive Cost-Efficient Early-Stopping
by: Belkhiter, Yannis, et al.
Published: (2026)
by: Belkhiter, Yannis, et al.
Published: (2026)
GRAID: Synthetic Data Generation with Geometric Constraints and Multi-Agentic Reflection for Harmful Content Detection
by: Rad, Melissa Kazemi, et al.
Published: (2025)
by: Rad, Melissa Kazemi, et al.
Published: (2025)
HarmfulSkillBench: How Do Harmful Skills Weaponize Your Agents?
by: Jiang, Yukun, et al.
Published: (2026)
by: Jiang, Yukun, et al.
Published: (2026)
Token-Level Privacy in Large Language Models
by: Harel, Re'em, et al.
Published: (2025)
by: Harel, Re'em, et al.
Published: (2025)
Virus: Harmful Fine-tuning Attack for Large Language Models Bypassing Guardrail Moderation
by: Huang, Tiansheng, et al.
Published: (2025)
by: Huang, Tiansheng, et al.
Published: (2025)
When Benign Inputs Lead to Severe Harms: Eliciting Unsafe Unintended Behaviors of Computer-Use Agents
by: Jones, Jaylen, et al.
Published: (2026)
by: Jones, Jaylen, et al.
Published: (2026)
A Generative Approach to LLM Harmfulness Mitigation with Red Flag Tokens
by: Dobre, David, et al.
Published: (2025)
by: Dobre, David, et al.
Published: (2025)
Eliciting Harmful Capabilities by Fine-Tuning On Safeguarded Outputs
by: Kaunismaa, Jackson, et al.
Published: (2026)
by: Kaunismaa, Jackson, et al.
Published: (2026)
Towards Assuring EU AI Act Compliance and Adversarial Robustness of LLMs
by: Momcilovic, Tomas Bueno, et al.
Published: (2024)
by: Momcilovic, Tomas Bueno, et al.
Published: (2024)
PrivLM-Bench: A Multi-level Privacy Evaluation Benchmark for Language Models
by: Li, Haoran, et al.
Published: (2023)
by: Li, Haoran, et al.
Published: (2023)
Root Defence Strategies: Ensuring Safety of LLM at the Decoding Level
by: Zeng, Xinyi, et al.
Published: (2024)
by: Zeng, Xinyi, et al.
Published: (2024)
Developing Assurance Cases for Adversarial Robustness and Regulatory Compliance in LLMs
by: Momcilovic, Tomas Bueno, et al.
Published: (2024)
by: Momcilovic, Tomas Bueno, et al.
Published: (2024)
GuidedBench: Measuring and Mitigating the Evaluation Discrepancies of In-the-wild LLM Jailbreak Methods
by: Huang, Ruixuan, et al.
Published: (2025)
by: Huang, Ruixuan, et al.
Published: (2025)
Where Do Backdoors Live? A Component-Level Analysis of Backdoor Propagation in Speech Language Models
by: Fortier, Alexandrine, et al.
Published: (2025)
by: Fortier, Alexandrine, et al.
Published: (2025)
Towards a Practical Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via Randomized Smoothing
by: Gibert, Daniel, et al.
Published: (2023)
by: Gibert, Daniel, et al.
Published: (2023)
EmMark: Robust Watermarks for IP Protection of Embedded Quantized Large Language Models
by: Zhang, Ruisi, et al.
Published: (2024)
by: Zhang, Ruisi, et al.
Published: (2024)
Verifiability and Privacy in Federated Learning through Context-Hiding Multi-Key Homomorphic Authenticators
by: Bottoni, Simone, et al.
Published: (2025)
by: Bottoni, Simone, et al.
Published: (2025)
ML-Bench&Guard: Policy-Grounded Multilingual Safety Benchmark and Guardrail for Large Language Models
by: Zhao, Yunhan, et al.
Published: (2026)
by: Zhao, Yunhan, et al.
Published: (2026)
Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning
by: Chua, Lynn, et al.
Published: (2024)
by: Chua, Lynn, et al.
Published: (2024)
DocMIA: Document-Level Membership Inference Attacks against DocVQA Models
by: Nguyen, Khanh, et al.
Published: (2025)
by: Nguyen, Khanh, et al.
Published: (2025)
Safety and Security Analysis of Large Language Models: Benchmarking Risk Profile and Harm Potential
by: Akiri, Charankumar, et al.
Published: (2025)
by: Akiri, Charankumar, et al.
Published: (2025)
On the Generation and Mitigation of Harmful Geometry in Image-to-3D Models
by: Liu, Yule, et al.
Published: (2026)
by: Liu, Yule, et al.
Published: (2026)
Assessing the Impact of Packing on Machine Learning-Based Malware Detection and Classification Systems
by: Gibert, Daniel, et al.
Published: (2024)
by: Gibert, Daniel, et al.
Published: (2024)
Similar Items
-
Breaking MCP with Function Hijacking Attacks: Novel Threats for Function Calling and Agentic Models
by: Belkhiter, Yannis, et al.
Published: (2026) -
Elevating Defenses: Bridging Adversarial Training and Watermarking for Model Resilience
by: Thakkar, Janvi, et al.
Published: (2023) -
Blue Teaming Function-Calling Agents
by: Dolcetti, Greta, et al.
Published: (2026) -
Segment-Level Coherence for Robust Harmful Intent Probing in LLMs
by: He, Xuanli, et al.
Published: (2026) -
ChineseHarm-Bench: A Chinese Harmful Content Detection Benchmark
by: Liu, Kangwei, et al.
Published: (2025)