Reward-Hacking

2 reports

All LLM Security Agentic AI Industry News Research Supply Chain Prompt Injection First Look: Security Regulatory Jailbreaks Adversarial ML Data Poisoning Model Theft AI Security Tools Security Operations

AWS Launches Multi-Turn RL for Amazon Nova

FIRST LOOK ATLAS OWASP HIGH ▲ 7.2 AWS Machine Learning Blog Jul 07, 2026

AWS has released a production-grade, event-driven multi-turn reinforcement learning training infrastructure for Amazon Nova models on SageMaker HyperPod, enabling enterprises to train agents that learn tool orchestration, error recovery, and sequential decision-making at scale. This materially expands the attack surface by introducing complex reward-routing pipelines, ephemeral compute provisioning, and environment-facing reward workers as new targets for poisoning and manipulation. Defenders must scrutinise the trust boundaries between the Nova Forge SDK, ECS reward workers, and HyperPod training pods, as a compromised reward signal can silently shape model behaviour across entire interaction sequences.

SWE-bench, WebArena Exploited via Environmental Manipulation

ATLAS OWASP CRITICAL ▲ 9.2 HN AI Security Apr 11, 2026

Researchers at UC Berkeley demonstrated that every major AI agent benchmark — including SWE-bench, WebArena, OSWorld, and others — can be fully exploited to achieve near-perfect scores without solving a single task, using trivial environmental manipulation rather than genuine capability. The attacks include pytest hook injection, config file leakage, DOM manipulation, and reward component bypassing, with zero LLM calls required in most cases. This represents a systemic integrity failure in the evaluation infrastructure underpinning AI deployment decisions across industry and research.

Reward-Hacking

AWS Launches Multi-Turn RL for Amazon Nova

SWE-bench, WebArena Exploited via Environmental Manipulation

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