Malware Analysis
Can AdversaryGraph Tell the Story of a Malware PCAP?
Twenty malware PCAP tests with real AdversaryGraph screenshots, short reports, IOC checks, official-answer comparisons, and downloadable evidence.
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1200km research library
Security research articles, available locally.
Browse the complete local archive of technical articles, including 87 permitted full mirrors from TrainSec.net. Every card opens the locally hosted article on 1200km.com; the original publication remains the source and attribution link.
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- Preserved images
- 2,361
- Code/config blocks
- 3,571
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280 articles found
Malware Analysis
AdversaryGraph vs Ten Malware PCAPs: What the Evidence Actually Shows
Ten live-instance malware-PCAP tests with 20 original screenshots, ten full reports, 52 enrichment lookups, packet-level proofs and explicit limits on the 87/88 selected-indicator score.
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- 5
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- 3
AI Security
AI Agent vs. Human with Wireshark: Six Malware PCAPs Put to the Test
This experiment measures how Daybreak Blue at extra-high reasoning investigated six malicious packet captures, where it succeeded, what it missed, and how its work compares with a trained human analyst.
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Malware Analysis
Course Review — TrainSec Malware Analyst Professional — Level 1
A practical review of TrainSec's Malware Analyst Professional Level 1 course, its learning path, workload, lab depth, and companion research guides.
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- 1
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AI Security
AI Security Course, Module 00 — Chapter 4
Trace an LLM request from structured messages to generated output, then place authorization, validation, and forensic evidence at the boundaries that actually enforce security.
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Malware Analysis
AIDebug 3.1 Full Release Review: From Binary Intake to String Intelligence
Review AIDebug 3.1 from evidence-first binary intake through PE and ELF triage, String Intelligence, disassembly, Ghidra, optional AI analysis, controlled debugging, history, and reports.
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Malware Analysis
Strings Analysis for Malware Analysis: Turning Binary Text into Defensible Hypotheses
Turn extracted binary text into defensible malware-analysis hypotheses with evidence-first triage, AIDebug String Intelligence, cross-references, and validation.
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- 14
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Malware Analysis
PE File Structure for Malware Analysis: A Practical Guide
Map Windows Portable Executable files from disk to memory with an evidence-led guide to headers, sections, imports, exports, resources, relocations, TLS, mitigations, signatures, debug data, .NET metadata, and AIDebug inspection.
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Malware Analysis
Assembly for Malware Analysis: A Practical x86/x64 Guide
Learn to recover meaning from x86 and x64 assembly with real AIDebug examples covering registers, memory, flags, calling conventions, control flow, Windows API behavior, decompilation, and a repeatable malware-analysis workflow.
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AI Security
AI Security Course, Module 00 — Chapter 3: Neural Networks and Optimization
This chapter explains neural-network computation, optimization, reproducibility, attacker access, adversarial claims, and defensible evidence for security practitioners without a calculus prerequisite
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Malware Analysis
How to Build a Safe Malware Analysis Lab with FLARE-VM, REMnux, and INetSim
This guide turns lessons 2–4 of TrainSec's Malware Analyst Professional — Level 1 into a repeatable lab-preparation procedure. The course demonstrates the topology and deployment process; this version adds explicit co…
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Malware Analysis
What Is Malware?
Malware is software or code intentionally used to compromise the confidentiality, integrity, or availability of devices, applications, networks, or data.
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AI Security
AI Security Course, Module 00 — Part 2
Data, features, labels, parameters, training, validation, testing, and inference become an evidence-preserving workflow for AI security engineering.
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AI Security
AI Security Course, Module 00 — Part 1: Introduction, AI/ML Taxonomy
Before securing an AI system, build a precise vocabulary for AI, machine learning, models, data, and the boundaries between them.
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AI Security
I’m Building an AI Security Engineering Course
A practical, evidence-grounded path from AI fundamentals to secure agentic systems and modern AI security engineering.
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CTI
AdversaryGraph
AdversaryGraph is a self-hosted security intelligence workbench that connects observables, ATT&CK, malware findings, detection validation, and reporting.
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Detection Engineering
Newest Detection Engineering Techniques: From Rules to Validated Security Telemetry
Practical detection engineering methods for identity, cloud, CI/CD, runtime, telemetry validation, and AI-era threats.
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- 25
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AI Security
When AI Coding Agents Say Yes Too Easily: Testing Suspicious Cybersecurity Prompts in Cursor
A controlled comparison of how AI coding models respond to the same suspicious cybersecurity prompt inside Cursor.
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- 11
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CTI
Comprehensive Cyber Intelligence Research: Attacks Against Embedded Systems, Hardware, Firmware…
Evidence-led cyber intelligence research into attacks against embedded systems, hardware, firmware, edge devices, and their vendors.
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- 49
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CTI
AdversaryGraph v5.0: From CTI Mapping to Attack Simulation and SIEM Validation
How can a security team move from threat intelligence to detection engineering without losing the evidence trail?
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CTI
AdversaryGraph v4.0: I Added a Full Malware Analysis Workbench to My Self-Hosted CTI Platform
You upload a sample to one tool for hash reputation. You open another tool for strings. You use a disassembler for functions. You check imports somewhere else. You copy indicators into a CTI platform. You build ATT&CK…
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CTI
From Log to Report: Using AdversaryGraph!
The harder problem is turning scattered technical evidence into a defensible investigation
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CTI
AdversaryGraph v2.5: New Name, New Release, Full AI CTI Platform Capability Map
This release marks an important transition for the project: the tool now has a new canonical name
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CTI
AdversaryGraph Usecases
AdversaryGraph v2.5: New Name, New Release, Full AI CTI Platform Capability Map
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