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GithubExploit
GithubExploit
โ€ขadded 2026/03/10 10:43 p.m.โ€ข212 views

rami-kali-MCP

Red Team MCP Server MCP Model Context Protocol server that...

6AI score
Exploits0
GithubExploit
GithubExploit
โ€ขadded 2025/12/06 5:33 p.m.โ€ข128 views

nim-pentest-agent

NimPentestAgent Agent autonome de pentest intelligent pour CT...

7.1AI score
Exploits0
Packet Storm News
Packet Storm News
โ€ขadded 2025/10/23 12:0 a.m.โ€ข28 views

REx86: A Local Large Language Model for Assisting in X86 Assembly Reverse Engineering

Reverse engineering RE of x86 binaries is indispensable for malware and firmware analysis, but remains slow due to stripped metadata and adversarial obfuscation. Large Language Models LLMs offer potential for improving RE efficiency through automated comprehension and commenting, but cloud-hosted...

6.8AI score
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Packet Storm News
Packet Storm News
โ€ขadded 2025/10/11 12:0 a.m.โ€ข2 views

Bridging Semantics and Structure for Software Vulnerability Detection Using Hybrid Network Models

Software vulnerabilities remain a persistent risk, yet static and dynamic analyses often overlook structural dependencies that shape insecure behaviors. Viewing programs as heterogeneous graphs, we capture control- and data-flow relations as complex interaction networks. Our hybrid framework...

6.9AI score
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Packet Storm News
Packet Storm News
โ€ขadded 2025/06/15 12:0 a.m.โ€ข4 views

I Know What You Said: Unveiling Hardware Cache Side-Channels in Local Large Language Model Inference

Large Language Models LLMs that can be deployed locally have recently gained popularity for privacy-sensitive tasks, with companies such as Meta, Google, and Intel playing significant roles in their development. However, the security of local LLMs through the lens of hardware cache side-channels...

6.7AI score
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Packet Storm News
Packet Storm News
โ€ขadded 2025/05/27 12:0 a.m.โ€ข12 views

JavaSith: a Client-Side Framework for Analyzing Potentially Malicious Extensions in Browsers, VS Code, and NPM Packages

Modern software supply chains face an increasing threat from malicious code hidden in trusted components such as browser extensions, IDE extensions, and open-source packages. This paper introduces JavaSith, a novel client-side framework for analyzing potentially malicious extensions in web...

7.1AI score
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