LAAF: A Layered Accountability Architecture Framework for LLM Applications

Large Language Models LLMs operate in hospitals, courtrooms, banks, and public service desks, where fluent, confident outputs are treated as authoritative even when ungrounded or incorrect. When such an output contributes to harm, who is answerable, and through what mechanisms can responsibility ...

Beyond the Hype: Evaluating LLM Integration and Practical Limitations in Security Operation Centers

Large Language Models LLMs are increasingly being explored within Security Operation Centers SOCs to support text-heavy analytical work such as alert contextualization, incident summarization, and drafting investigative artifacts. Despite this interest, practitioners describe critical operational...

RedAmon 6.2.5

An autonomous AI framework that chains reconnaissance, exploitation, and post-exploitation into a single pipeline, then goes further by triaging every finding, implementing code fixes, and opening pull requests on your repository. From first packet to merged patch, with human oversight at every...

RedAmon 6.2.2

An autonomous AI framework that chains reconnaissance, exploitation, and post-exploitation into a single pipeline, then goes further by triaging every finding, implementing code fixes, and opening pull requests on your repository. From first packet to merged patch, with human oversight at every...

RedAmon 6.0.2

An autonomous AI framework that chains reconnaissance, exploitation, and post-exploitation into a single pipeline, then goes further by triaging every finding, implementing code fixes, and opening pull requests on your repository. From first packet to merged patch, with human oversight at every...

Large Language Models in Misinformation Ecosystems: Misuse, Defense, and Vulnerability

Large language models LLMs have transformed misinformation from a primarily content-centric problem into a broader ecosystem-level security challenge. When misused, LLMs create risks beyond false content generation, enabling attacks on the social contexts, evidence sources, retrieval corpora, and...

RedAmon 5.1.0

An autonomous AI framework that chains reconnaissance, exploitation, and post-exploitation into a single pipeline, then goes further by triaging every finding, implementing code fixes, and opening pull requests on your repository. From first packet to merged patch, with human oversight at every...

Evaluating the Reliability of Multiple Large Language Models in Risk Assessment: A CIS Controls Based Approach

Proper implementation of technical and administrative controls reinforces an organization's cybersecurity posture and business resilience, reduces risks, and enhances governance, ultimately elevating business maturity. The dynamics of the technological landscape and emerging threats negatively...

Explainable Autonomous Cyber Defense Using Adversarial Multi-Agent Reinforcement Learning

Autonomous agents are increasingly deployed in both offensive and defensive cyber operations, creating high-speed, closed-loop interactions in critical infrastructure environments. Advanced Persistent Threat APT actors exploit "Living off the Land" techniques and targeted telemetry perturbations ...

Applying security fundamentals to AI: Practical advice for CISOs

What to know about the era of AI The first thing to know is that AI isn’t magic The best way to think about how to effectively use and secure a modern AI system is to imagine it like a very new, very junior person. It’s very smart and eager to help but can also be extremely unintelligent. Like a...

Applying security fundamentals to AI: Practical advice for CISOs

What to know about the era of AI The first thing to know is that AI isn’t magic The best way to think about how to effectively use and secure a modern AI system is to imagine it like a very new, very junior person. It’s very smart and eager to help but can also be extremely unintelligent. Like a...

AI in Vulnerability Discovery: A Call for Human Oversight and Caution

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Don't Let the Claw Grip Your Hand: A Security Analysis and Defense Framework for OpenClaw

Code agents powered by large language models can execute shell commands on behalf of users, introducing severe security vulnerabilities. This paper presents a two-phase security analysis of the OpenClaw platform. As an open-source AI agent framework that operates locally, OpenClaw can be integrat...

Optimizing Agent Planning for Security and Autonomy

Indirect prompt injection attacks threaten AI agents that execute consequential actions, motivating deterministic system-level defenses. Such defenses can provably block unsafe actions by enforcing confidentiality and integrity policies, but currently appear costly: they reduce task completion...

WiFiPenTester: Advancing Wireless Ethical Hacking with Governed GenAI

Wireless ethical hacking relies heavily on skilled practitioners manually interpreting reconnaissance results and executing complex, time-sensitive sequences of commands to identify vulnerable targets, capture authentication handshakes, and assess password resilience; a process that is inherently...

A Safety and Security Framework for Real-World Agentic Systems

This paper introduces a dynamic and actionable framework for securing agentic AI systems in enterprise deployment. We contend that safety and security are not merely fixed attributes of individual models but also emergent properties arising from the dynamic interactions among models, orchestrator...

What AI Reveals About Web Applications— and Why It Matters

Before an attacker ever sends a payload, they've already done the work of understanding how your environment is built. They look at your login flows, your JavaScript files, your error messages, your API documentation, your GitHub repos. These are all clues that help them understand how your syste...

Leveraging Large Language Models for Cybersecurity Risk Assessment -- a Case from Forestry Cyber-Physical Systems

In safety-critical software systems, cybersecurity activities become essential, with risk assessment being one of the most critical. In many software teams, cybersecurity experts are either entirely absent or represented by only a small number of specialists. As a result, the workload for these...

LegalPwn Attack Tricks GenAI Tools Into Misclassifying Malware as Safe Code

A new security flaw, LegalPwn, exploits a weakness in generative AI tools like GitHub Copilot and ChatGPT, where malicious code is disguised as legal disclaimers. Learn why human oversight is now more critical than ever for AI security...

Organizational Adaptation to Generative AI in Cybersecurity: a Systematic Review

Cybersecurity organizations are adapting to GenAI integration through modified frameworks and hybrid operational processes, with success influenced by existing security maturity, regulatory requirements, and investments in human capital and infrastructure. This qualitative research employs...