Hive Security
Offensive thinking. Defensive expertise.
Hive Security is a cybersecurity research blog focused on the intersection of red team operations and blue team defense. We believe that understanding how attacks work is the only way to build meaningful defenses.
The content here covers penetration testing techniques, Active Directory exploitation, malware analysis, threat hunting methodologies, SIEM engineering, and anything else that lives at the sharp end of security work.
What you'll find here
- In-depth technical writeups on offensive techniques
- Practical blue team guidance and detection logic
- Tool development and automation for security workflows
- Analysis of real-world threats and attack chains
- CTF writeups and challenge walkthroughs
Philosophy
No fluff. No vendor content. No "top 10 tips" listicles. Every article here is written for practitioners who already know the basics and want to go deeper. If you're looking for introductory content, you'll find better resources elsewhere.
Security is adversarial. The best defenders think like attackers — and the best attackers understand what defenders are looking for. That gap is where most of the interesting work happens.
Use of artificial intelligence
Hive Security uses generative AI tools, including Claude and Codex, to assist with research, drafting, editing, code review, and illustration. AI output is treated as unverified working material, not as an authoritative source.
Before publication, articles undergo substantive human review and editorial approval. Material factual claims are checked against appropriate sources, with primary and official sources preferred where available. Hive Security retains editorial control and assumes responsibility for the decision to publish the final content.
Material uses of AI that could affect a reader's interpretation are disclosed with the relevant content. Realistic synthetic or materially manipulated images, audio, and video are clearly identified and are not presented as authentic evidence of a person, event, or security incident. AI-generated illustrations are identified in their captions.
Confidential information, credentials, private indicators, customer data, and unnecessary personal data are not intentionally submitted to generative AI services.
Found an error? Contact us. Confirmed material errors are corrected and may be noted in the affected article.
This policy is reviewed as applicable regulation, tools, and editorial practices evolve. Last updated: 4 August 2026.