Here's your daily roundup of the most relevant AI and ML news for February 04, 2026. Today's digest includes 1 security-focused story. We're also covering 6 research developments. Click through to read the full articles from our curated sources.
Security & Safety
1. Show HN: Quibble – Adversarial AI document review using Codex and Claude
I built Quibble to get better feedback on technical documents (specs, plans, RFCs) by having two AI models argue about them. I still don't know if it's any good, so I'm sharing it here hopeful for you to try it out and give me feedback!!!It works like this:1. Codex reviews your document and raise...
Source: Hacker News - ML Security | just now
Research & Papers
2. MAGIC: A Co-Evolving Attacker-Defender Adversarial Game for Robust LLM Safety
arXiv:2602.01539v1 Announce Type: new Abstract: Ensuring robust safety alignment is crucial for Large Language Models (LLMs), yet existing defenses often lag behind evolving adversarial attacks due to their \textbf{reliance on static, pre-collected data distributions}. In this paper, we introduc...
Source: arXiv - AI | 18 hours ago
3. RedVisor: Reasoning-Aware Prompt Injection Defense via Zero-Copy KV Cache Reuse
arXiv:2602.01795v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly vulnerable to Prompt Injection (PI) attacks, where adversarial instructions hidden within retrieved contexts hijack the model's execution flow. Current defenses typically face a critical trade-off: pr...
Source: arXiv - AI | 18 hours ago
4. Beyond Suffixes: Token Position in GCG Adversarial Attacks on Large Language Models
arXiv:2602.03265v1 Announce Type: new Abstract: Large Language Models (LLMs) have seen widespread adoption across multiple domains, creating an urgent need for robust safety alignment mechanisms. However, robustness remains challenging due to jailbreak attacks that bypass alignment via adversari...
Source: arXiv - Machine Learning | 18 hours ago
5. Toward Universal and Transferable Jailbreak Attacks on Vision-Language Models
arXiv:2602.01025v1 Announce Type: cross Abstract: Vision-language models (VLMs) extend large language models (LLMs) with vision encoders, enabling text generation conditioned on both images and text. However, this multimodal integration expands the attack surface by exposing the model to image-b...
Source: arXiv - AI | 18 hours ago
6. STAC: When Innocent Tools Form Dangerous Chains to Jailbreak LLM Agents
arXiv:2509.25624v2 Announce Type: replace-cross Abstract: As LLMs advance into autonomous agents with tool-use capabilities, they introduce security challenges that extend beyond traditional content-based LLM safety concerns. This paper introduces Sequential Tool Attack Chaining (STAC), a novel ...
Source: arXiv - AI | 18 hours ago
7. Adversarial Reward Auditing for Active Detection and Mitigation of Reward Hacking
arXiv:2602.01750v1 Announce Type: new Abstract: Reinforcement Learning from Human Feedback (RLHF) remains vulnerable to reward hacking, where models exploit spurious correlations in learned reward models to achieve high scores while violating human intent. Existing mitigations rely on static def...
Source: arXiv - AI | 18 hours ago
Tech & Development
8. Show HN: LLM Jailbreak Database
I vibe-coded this online DB for LLM injection prompts. It's registration/login less with some ambitious spam/bot filtering. I'm interested in trying to tune the barriers of interaction to a sweet spot where the DB gets balanced and the useful working injections are actually on top.thoughts?
Comm...
Source: Hacker News - AI | 1 hours ago
About This Digest
This digest is automatically curated from leading AI and tech news sources, filtered for relevance to AI security and the ML ecosystem. Stories are scored and ranked based on their relevance to model security, supply chain safety, and the broader AI landscape.
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