Interesting empirical research: “Black Box Warfare: Human Judgment and Military Decision-Making in the Age of AI.” Abstract: How is AI transforming decision-making in modern conflict? This study provides a unique empirical window into that question by deploying a high-fidelity replica of an AI decision-support system (DSS) used in military targeting. After reconstructing the interface and function

A recent study examining the integration of artificial intelligence into military decision-making processes has revealed nuanced insights into how personnel interact with AI decision-support systems, particularly in high-stakes combat scenarios. The research, titled "Black Box Warfare: Human Judgment and Military Decision-Making in the Age of AI," utilized a high-fidelity replica of an AI decision-support system (DSS) currently employed in military targeting operations.
The study aimed to understand the impact of AI on combat decisions, specifically addressing concerns about potential automation bias. Researchers reconstructed the interface and functionality of a real-world military AI system to conduct their experiments.
Two experiments were performed involving a significant sample size of 2,015 Israeli military personnel. Participants were presented with various combat scenarios to assess their reactions to AI-generated recommendations.
Contrary to prevailing assumptions that military personnel might exhibit automation bias—an over-reliance on automated systems—the study found strong evidence of algorithmic aversion. This aversion was particularly pronounced in scenarios that involved a high potential for collateral damage.
However, the research also identified a mitigating factor: the integration of explainable AI (XAI) features. When AI recommendations were accompanied by explanations for their rationale, algorithmic aversion was reduced. This feature promoted more thoughtful evaluations of the algorithmic recommendations by the military personnel.
The findings suggest that trust in military AI is not static but rather a dynamic variable. It appears to be influenced by several factors, including individual predispositions of the user, the perceived operational stakes of the situation, and the specific informational features presented within the AI interface.
This empirical evidence challenges some widespread assumptions regarding the adoption of AI in warfare. The study underscores the continued importance of human agency in critical military decision-making, even as AI systems become more integrated into operational processes.
The research provides critical insights into the practical integration of AI in military contexts, moving beyond theoretical concerns to offer data-driven observations on human-AI interaction in combat environments. The paper was posted on August 11, 2026.
A weakness has been identified in Tenda CP3 27.5.57.101. This issue affects some unknown processing of the file Net/NetCheckPing.cpp. This manipulation of the argument interface_name/host causes os command injection. The attack can be initiated remotely.
A security flaw has been discovered in Tenda CP3 27.5.57.101. This vulnerability affects the function SystemAsh of the file Apis/system.c of the component Kylin. The manipulation of the argument AlarmVoiceURL results in os command injection. It is possible to launch the attack remotely.

OpenAI has announced a $1 billion commitment to provide subsidized access to its Daybreak AI cybersecurity tools for under-resourced critical infrastructure defenders. The initiative, named Daybreak for Frontline Defenders, will offer AI models, training, and technical support over the next six months, prioritizing water and wastewater utilities, electric grid operators, and local government entities. This move aims to equip organizations with limited budgets and staff against increasingly sophisticated cyber threats.

Attackers are exploiting a new unpatched vulnerability in Magento Open Source and Adobe Commerce that lets them run malicious code on an online store's server without logging in, Dutch e-commerce security company Sansec said in an advisory published on September 5. Sansec, which discovered the flaw and named it StyleSmuggler, said attacks started on September 4. "Sansec is publishing early
In BPF instructions that load/store a value from/to a scratch memory register the register index is an unsigned 32-bit integer and must not exceed 15, but libpcap BPF interpreter does not validate the value. In particular uncommon use cases a crafted filter program can cause the interpreter to try reading and writing the OS process memory in the 16GiB starting at the current stack frame on 64-bit architectures and in the entire address space on 32-bit architectures.

Attackers are exploiting two new PaperCut flaws to steal credentials and gain privileged access in education-sector attacks across the U.S. and Europe. Attackers are exploiting two recelty disclosed PaperCut flaws, CVE-2026-81578 and CVE-2026-82078, in attacks targeting schools and other education organizations in the U.S. and Europe, as reported by TheHackerNews. Arctic Wolf researchers observed