About redteams.ai
redteams.ai is an independent, ad-supported knowledge base focused on the security of large language models, AI agents, and the systems built around them. The site is written for offensive security practitioners, AI/ML engineers, and the security researchers who sit between those two worlds. We publish technical guides, walkthroughs, incident summaries, and reference material covering the practice of red-teaming modern AI systems.
Who runs the site
The site is operated by a single individual editor working under the name redteams.ai, with occasional unpaid contributions from named guest authors. The operator's professional background is in offensive security and applied machine learning; the editorial perspective draws from hands-on penetration testing of AI-integrated applications, internal red-team work against generative-AI features in production systems, and engagement with the open security-research community. There are no investors, no paid sponsorships embedded in editorial content, and no vendor relationships that influence what we cover or how we cover it.
What we publish
Our editorial output is organised into three primary surfaces:
- Long-form articles— in-depth treatments of a specific attack class, defensive control, or operational practice. These typically run several thousand words, include code, and link out to primary sources (academic papers, vendor advisories, original disclosures).
- The blog— shorter pieces covering breaking incidents, career advice, perspectives on industry developments, and our own opinions on contested questions in the field. The blog is where our voice is most explicit.
- Reference material — a glossary, an incident log, a technique navigator, and curated external resources. These are maintained as living documents and updated as the field evolves.
Editorial standards
Our content methodology is described in full on the methodology page. In short: drafts are produced with AI assistance and then reviewed by a human editor before publication; primary sources are cited inline; we revisit articles when the underlying techniques, tools, or defences meaningfully change; and the “Last updated” date on each article reflects the most recent substantive edit. We do not publish vendor press-release rewrites and we do not accept paid placements.
We make mistakes, sometimes serious ones. If you find a technical error, a misattribution, or a citation that has not aged well, please write to contact@redteams.ai. We aim to acknowledge corrections within a few working days and publish a short note describing what changed.
Why this is ad-supported
The site is funded by display advertising served through Google AdSense. Advertising lets us keep every article free to read and independent of any single sponsor, vendor relationship, or paywall. Advertising decisions never influence what we cover or how we cover it — ad placement is purely contextual and is not coordinated with the editorial process. Readers who would prefer to support the site directly can do so via contributions, which currently take the form of technical pull requests, corrections, and source suggestions rather than financial support.
Use of AI assistance
We use large language models to accelerate drafting and to keep coverage across the field broad. We disclose this openly because the site is, after all, about AI security: pretending otherwise would be absurd. The role of the model is essentially the same as that of a well-read research assistant: it produces drafts, summarises sources, and proposes structure. The human editor checks facts, verifies code, removes hallucinated citations, prunes filler, and decides what gets published. Pages that have not yet been through full human review are flagged accordingly and are excluded from our public sitemap.
Audience and scope
redteams.ai assumes a working knowledge of software engineering and information security. We do not write for an absolute beginner audience — readers are expected to be comfortable with Python, with the command line, and with the general shape of a web application or a backend service. We do not assume prior expertise in machine learning; concepts specific to language models are introduced as needed, often via the glossary.
We cover the offensive side of AI security in detail because we believe defenders cannot reason about systems they do not understand adversarially. All material on the site is published for the purposes of authorised testing, education, and defensive research. Readers are expected to operate within the law and within the scope of any engagement they hold. We do not assist with unauthorised access to systems and we do not respond to requests for help with attacks against third-party targets without evidence of authorisation.
Contact
For editorial corrections, source suggestions, takedown requests, legal notices, and partnership enquiries, write to contact@redteams.ai. Privacy and data-protection requests are handled per our privacy policy. Operator details and the postal address are available on the imprint page.